WMS This is the WMS service of the Mission Atlantic GeoNode WFS WMS GEOSERVER

NONE NONE text/xml image/png application/atom+xml application/json;type=utfgrid application/pdf application/rss+xml application/vnd.google-earth.kml+xml application/vnd.google-earth.kml+xml;mode=networklink application/vnd.google-earth.kmz application/x-gpkg application/x-sqlite3 image/geotiff image/geotiff8 image/gif image/jpeg image/png; mode=8bit image/svg+xml image/tiff image/tiff8 image/vnd.jpeg-png image/vnd.jpeg-png8 text/html; subtype=openlayers text/html; subtype=openlayers2 text/html; subtype=openlayers3 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml; subtype=gml/3.1.1 text/html text/javascript application/json XML INIMAGE BLANK JSON JSONP This is the WMS service of the Mission Atlantic GeoNode EPSG:4326 EPSG:3785 EPSG:3857 EPSG:900913 EPSG:32647 EPSG:32736 CRS:84 -180.0 180.0 -90.0 90.0 geonode:0 EPSG:4326 CRS:84 -11.677031 -5.282544 48.493025 56.275718 geonode:1 EPSG:4326 CRS:84 -11.753427 -5.270381 50.683369 56.275718 geonode:2 EPSG:4326 CRS:84 -11.631744 -5.730604 51.060653 56.260249 geonode:3 EPSG:4326 CRS:84 -10.848778 -5.280874 48.492828 55.899065 geonode:4 EPSG:4326 CRS:84 -10.486841 -6.595702 51.588693 54.289523 geonode:5 EPSG:4326 CRS:84 -10.913487 -5.312149 50.683369 55.929404 geonode:6 EPSG:4326 CRS:84 -11.642639 -5.32472 51.089702 56.26126 geonode:7 EPSG:4326 CRS:84 -10.912265 -5.306801 48.527544 55.642856 geonode:8 EPSG:4326 CRS:84 -10.362064 -5.751343 50.319732 55.235647 geonode:9 EPSG:4326 CRS:84 -11.72283 -5.584639 51.552837 56.084556 geonode:AAHA_Level1_allClasses No abstract provided Data not evaluated Atlantic Bio-geographical regions A Metadata conformant GeoTIFF WCS Marine/Coastal No limitations to public access Habitat classification AAHA_Level1_allClasses EPSG:4326 CRS:84 -66.00000000002592 29.666666666618994 -62.249999999965524 83.3333333333347 other other other other text/xml other other geonode:AAHA_Level2_allClasses No abstract provided Data not evaluated Atlantic Bio-geographical regions A Metadata conformant GeoTIFF WCS Marine/Coastal AAHA_Level2_allClasses No limitations to public access Habitat classification EPSG:4326 CRS:84 -66.00000000000003 29.6666666666666 -62.24999999999994 83.33333333333334 other other other other text/xml other other geonode:AAHA_Level3_allClasses No abstract provided Data not evaluated Atlantic Bio-geographical regions A Metadata conformant GeoTIFF WCS Marine/Coastal AAHA_Level3_allClasses No limitations to public access Habitat classification EPSG:4326 CRS:84 -66.00000000002592 29.666666666618994 -62.249999999965524 83.3333333333347 other other other other text/xml other other geonode:ALB_mean_CNRM_hist_biomass_quarter1 albacore CNRM Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_hist_biomass_quarter2 albacore CNRM Habitats and biotopes Regional quarter 2 historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_hist_biomass_quarter3 albacore CNRM Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 3 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_hist_biomass_quarter4 albacore CNRM Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 4 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_ssp126_biomass_quarter1 albacore CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_ssp126_biomass_quarter2 albacore CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional quarter 2 Habitat types and species distribution and range (Habitats Directive) EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_ssp126_biomass_quarter3 albacore CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 3 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_ssp126_biomass_quarter4 albacore CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 4 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_ssp370_biomass_quarter1 albacore CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_ssp370_biomass_quarter2 albacore CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional quarter 2 Habitat types and species distribution and range (Habitats Directive) EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_ssp370_biomass_quarter3 albacore CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 3 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_CNRM_ssp370_biomass_quarter4 albacore CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 4 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_hist_biomass_quarter1 albacore Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) GFDL quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other other text/xml other geonode:ALB_mean_GFDL_hist_biomass_quarter2 albacore Habitats and biotopes Regional quarter 2 historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_hist_biomass_quarter3 albacore Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 3 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_hist_biomass_quarter4 albacore Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 4 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_ssp126_biomass_quarter1 albacore Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) GFDL quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_ssp126_biomass_quarter2 albacore Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional quarter 2 Habitat types and species distribution and range (Habitats Directive) GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_ssp126_biomass_quarter3 albacore Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 3 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 text/xml other other other other other other geonode:ALB_mean_GFDL_ssp126_biomass_quarter4 albacore Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 4 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other text/xml other other other other other geonode:ALB_mean_GFDL_ssp370_biomass_quarter1 albacore SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) GFDL quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_ssp370_biomass_quarter2 albacore SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional quarter 2 Habitat types and species distribution and range (Habitats Directive) GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_ssp370_biomass_quarter3 albacore SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 3 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:ALB_mean_GFDL_ssp370_biomass_quarter4 albacore SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 4 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 text/xml other other other other other other geonode:AcaArc_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode No abstract provided Data not evaluated Acanella Gray 1870 AcaArc_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode Metadata conformant GeoTIFF Species distribution Marine/Coastal Species Distributions Models WCS Biota No limitations to public access ANE EPSG:4326 CRS:84 -34.670493943195595 14.199276906079788 45.71717449496695 65.1152400730628 other other other other text/xml other other geonode:Arosioetal2023_FCNN_mod_map Morphological map (10 classes) of the Irish shelf resulting from the modal aggregation (Cell statistics “MAJORITY” in ArcGIS Pro 3.1) of the qualitatively and quantitatively best Fully Convolutional Neural Networks models obtained in the study: Arosio, R., Hobley, B., Wheeler, A. J., Sacchetti, F., Conti, L. A., Furey, T. and A. Lim, 2023. Fully convolutional neural networks applied to large-scale marine morphology mapping. Frontiers in Marine Science, Sec. Ocean Observation, 10, https://doi.org/10.3389/fmars.2023.1228867 features Arosioetal2023_FCNN_mod_map EPSG:32629 CRS:84 -12.02949284357077 -5.014997906209998 48.21994136580376 56.36021651817712 other other other other text/xml other other geonode:Atl_Combine_ExtendedBG_WMS_YoolProd_TopoFromMOL_10km_WGS84_atlantic No abstract provided Atl_Combine_ExtendedBG_WMS_YoolProd_TopoFromMOL_10km_WGS84_atlantic Data not evaluated Atlantic Bio-geographical regions A GeoTIFF Metadata conformant WCS Marine/Coastal Biota No limitations to public access Habitat classification EPSG:4326 CRS:84 -66.00000000000003 29.6666666666666 -62.24999999999994 83.33333333333334 other other other other text/xml other other geonode:Day_Metridia_lucens_1960_2019 No abstract provided Day_Metridia_lucens_1960_2019 WCS GeoTIFF EPSG:4326 CRS:84 -45.0 10.0 43.0 65.0 other other other other text/xml other other geonode:Day_Pleuromamma_1960_2019 No abstract provided Day and Night zooplankton abundance maps in the North Atlantic from 1960-2019 - Pleuromamma Day_Pleuromamma_1960_2019 WCS GeoTIFF EPSG:4326 CRS:84 -45.0 10.0 43.0 65.0 other other other other other text/xml other geonode:DisLop_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode No abstract provided Data not evaluated Desmophyllum pertusum (Linnaeus 1758) Celtic Sea Metadata conformant GeoTIFF Species distribution Marine/Coastal Species Distributions Models WCS DisLop_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode No limitations to public access ANE EPSG:4326 CRS:84 -34.670493943195595 14.199276906079788 45.71717449496695 65.1152400730628 text/xml other other other other other other geonode:FinalAbundance_Deania_calcea No abstract provided FinalAbundance_Deania_calcea WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:FinalAbundance_Deania_profundorum No abstract provided FinalAbundance_Deania_profundorum WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 text/xml other other other other other other geonode:FinalAbundance_Etmopterus_pusillus No abstract provided FinalAbundance_Etmopterus_pusillus WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other text/xml other other other other geonode:FinalAbundance_Etmopterus_spinax No abstract provided FinalAbundance_Etmopterus_spinax WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:FinalAbundance_Galeorhinus_galeus No abstract provided FinalAbundance_Galeorhinus_galeus WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other text/xml other other other other other geonode:FinalAbundance_Raja_clavata No abstract provided FinalAbundance_Raja_clavata WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:Kstelliferun_density_clipped_GHO_reprojectedGeoNode No abstract provided Metadata conformant Kstelliferun_density_clipped_GHO_reprojectedGeoNode GeoTIFF Marine/Coastal Kophobelemnon stelliferum (Müller 1776) Species distribution Data non conformant WCS No limitations to public access ANE Species Distribution Model EPSG:4326 CRS:84 -34.670493943195595 14.201905726458989 45.71717449496695 65.11786889344198 other other other other text/xml other other geonode:LophReef_threhsolded_GHO_reprojectedGeoNode No abstract provided Habitats and biotopes Data not evaluated LophReef_threhsolded_GHO_reprojectedGeoNode Desmophyllum pertusum (Linnaeus 1758) GeoTIFF WGS84 (EPSG:4326) WCS Marine/Coastal Species Distributions Models Biota Pheronema carpenteri (Thomson 1869) No limitations to public access ANE EPSG:4326 CRS:84 -22.520086150546295 6.909557994566022 48.272387903546594 62.03426258864373 other other other other text/xml other other geonode:MNK_mean_CNRM_hist_biomass_D1N1 CNRM Habitats and biotopes Regional historical (1985-2014) epipelagic (D1N1) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_hist_biomass_D2N1 CNRM migrant upper mesopelagic (D2N1) Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other other other text/xml geonode:MNK_mean_CNRM_hist_biomass_D2N2 CNRM upper mesopelagic (D2N2) Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other other other text/xml geonode:MNK_mean_CNRM_hist_biomass_D3N1 CNRM Habitats and biotopes Regional highly migrant lower mesopelagic (D3N1) historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_hist_biomass_D3N2 CNRM migrant lower mesopelagic (D3N2) Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other text/xml other other other other geonode:MNK_mean_CNRM_hist_biomass_D3N3 CNRM Habitats and biotopes Regional historical (1985-2014) lower mesopelagic (D3N3) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp126_biomass_D1N1 CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional epipelagic (D1N1) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp126_biomass_D2N1 CNRM migrant upper mesopelagic (D2N1) Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp126_biomass_D2N2 CNRM upper mesopelagic (D2N2) Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other text/xml other other other other other geonode:MNK_mean_CNRM_ssp126_biomass_D3N1 CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional highly migrant lower mesopelagic (D3N1) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp126_biomass_D3N2 CNRM migrant lower mesopelagic (D3N2) Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp126_biomass_D3N3 CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional lower mesopelagic (D3N3) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp370_biomass_D1N1 CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional epipelagic (D1N1) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp370_biomass_D2N1 CNRM migrant upper mesopelagic (D2N1) SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other text/xml other other other other other geonode:MNK_mean_CNRM_ssp370_biomass_D2N2 CNRM SSP3-7.0 climate scenario projection (2015-2070) upper mesopelagic (D2N2) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp370_biomass_D3N1 CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional highly migrant lower mesopelagic (D3N1) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_CNRM_ssp370_biomass_D3N2 CNRM SSP3-7.0 climate scenario projection (2015-2070) migrant lower mesopelagic (D3N2) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other text/xml other other other other geonode:MNK_mean_CNRM_ssp370_biomass_D3N3 CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional lower mesopelagic (D3N3) Habitat types and species distribution and range (Habitats Directive) micronecton EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_hist_biomass_D1N1 Habitats and biotopes Regional historical (1985-2014) epipelagic (D1N1) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_hist_biomass_D2N1 migrant upper mesopelagic (D2N1) Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other text/xml other other other other other geonode:MNK_mean_GFDL_hist_biomass_D2N2 upper mesopelagic (D2N2) Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_hist_biomass_D3N1 Habitats and biotopes Regional highly migrant lower mesopelagic (D3N1) historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 text/xml other other other other other other geonode:MNK_mean_GFDL_hist_biomass_D3N2 migrant lower mesopelagic (D3N2) Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_hist_biomass_D3N3 Habitats and biotopes Regional historical (1985-2014) lower mesopelagic (D3N3) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp126_biomass_D1N1 Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional epipelagic (D1N1) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp126_biomass_D2N1 migrant upper mesopelagic (D2N1) Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp126_biomass_D2N2 upper mesopelagic (D2N2) Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other text/xml other other other other other geonode:MNK_mean_GFDL_ssp126_biomass_D3N1 Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional highly migrant lower mesopelagic (D3N1) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp126_biomass_D3N2 migrant lower mesopelagic (D3N2) Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp126_biomass_D3N3 Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional lower mesopelagic (D3N3) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other text/xml other other other other geonode:MNK_mean_GFDL_ssp370_biomass_D1N1 SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional epipelagic (D1N1) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp370_biomass_D2N1 migrant upper mesopelagic (D2N1) SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp370_biomass_D2N2 SSP3-7.0 climate scenario projection (2015-2070) upper mesopelagic (D2N2) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp370_biomass_D3N1 SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional highly migrant lower mesopelagic (D3N1) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 text/xml other other other other other other geonode:MNK_mean_GFDL_ssp370_biomass_D3N2 SSP3-7.0 climate scenario projection (2015-2070) migrant lower mesopelagic (D3N2) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:MNK_mean_GFDL_ssp370_biomass_D3N3 SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional lower mesopelagic (D3N3) Habitat types and species distribution and range (Habitats Directive) micronecton GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:N1_p N1_p WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other other other other text/xml other other geonode:N3_n N3_n WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other other text/xml other other other other geonode:N5_s N5_s WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other other other other text/xml other other geonode:Night_Metridia_lucens_1960_2019 No abstract provided GeoTIFF Night_Metridia_lucens_1960_2019 Vertical migrations WCS North Atlantic Zooplankton EPSG:4326 CRS:84 -45.0 10.0 43.0 65.0 other other other other text/xml other other geonode:Night_Pleuromamma_1960_2019 No abstract provided Night_Pleuromamma_1960_2019 GeoTIFF Vertical migrations WCS North Atlantic Zooplankton EPSG:4326 CRS:84 -45.0 10.0 43.0 65.0 other other other other text/xml other other geonode:O2_o O2_o WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other other other other text/xml other other geonode:O3_TA O3_TA WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other other other other text/xml other other geonode:O3_c O3_c WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other other other other text/xml other other geonode:PherCarp_threhsolded_GHO_reprojectedGeoNode No abstract provided Habitats and biotopes Data not evaluated Desmophyllum pertusum (Linnaeus 1758) PherCarp_threhsolded_GHO_reprojectedGeoNode GeoTIFF WGS84 (EPSG:4326) WCS Marine/Coastal Species Distributions Models Biota Pheronema carpenteri (Thomson 1869) No limitations to public access ANE EPSG:4326 CRS:84 -22.520086150546295 6.909557994566022 48.272387903546594 62.03426258864373 other other other other text/xml other other geonode:ProbPresence_Centrophorus_squamosus No abstract provided ProbPresence_Centrophorus_squamosus WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Centroscymnus_coelolepis No abstract provided ProbPresence_Centroscymnus_coelolepis WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Centroscymnus_owstonii No abstract provided ProbPresence_Centroscymnus_owstonii WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Centroselachus_crepidater No abstract provided ProbPresence_Centroselachus_crepidater WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Dalatias_licha No abstract provided ProbPresence_Dalatias_licha WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Deania_calcea No abstract provided ProbPresence_Deania_calcea WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Deania_profundorum No abstract provided ProbPresence_Deania_profundorum WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other text/xml other other other other geonode:ProbPresence_Dipturus_batis No abstract provided ProbPresence_Dipturus_batis WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Etmopterus_princeps No abstract provided ProbPresence_Etmopterus_princeps WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Etmopterus_pusillus No abstract provided ProbPresence_Etmopterus_pusillus WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Etmopterus_spinax No abstract provided ProbPresence_Etmopterus_spinax WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Galeorhinus_galeus No abstract provided ProbPresence_Galeorhinus_galeus WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Leucoraja_fullonica No abstract provided ProbPresence_Leucoraja_fullonica WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Raja_clavata No abstract provided ProbPresence_Raja_clavata WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:ProbPresence_Squaliolus_laticaudus No abstract provided ProbPresence_Squaliolus_laticaudus WCS GeoTIFF EPSG:32626 CRS:84 -37.47953288703462 -18.832938657364714 32.678347147923816 44.34969359604369 other other other other text/xml other other geonode:Ptot_Chl_result Ptot_Chl_result WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other other other other other other text/xml geonode:Ptot_Chl_result_depth_int Ptot_Chl_result_depth_int WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z other other other other text/xml other other geonode:Ptot_NPP_result Ptot_NPP_result WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other text/xml other other other other other geonode:Ptot_NPP_result_depth_int Ptot_NPP_result_depth_int WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z other other other other text/xml other other geonode:SKJ_mean_CNRM_hist_biomass_quarter1 skipjack CNRM Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_CNRM_hist_biomass_quarter2 skipjack CNRM Habitats and biotopes Regional quarter 2 historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_CNRM_hist_biomass_quarter3 skipjack CNRM Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 3 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_CNRM_hist_biomass_quarter4 skipjack CNRM Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 4 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_CNRM_ssp126_biomass_quarter1 skipjack CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other text/xml other other other other other geonode:SKJ_mean_CNRM_ssp126_biomass_quarter2 skipjack CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional quarter 2 Habitat types and species distribution and range (Habitats Directive) EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_CNRM_ssp126_biomass_quarter3 skipjack CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 3 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_CNRM_ssp126_biomass_quarter4 skipjack CNRM Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 4 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 text/xml other other other other other other geonode:SKJ_mean_CNRM_ssp370_biomass_quarter1 skipjack CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 text/xml other other other other other other geonode:SKJ_mean_CNRM_ssp370_biomass_quarter2 skipjack CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional quarter 2 Habitat types and species distribution and range (Habitats Directive) EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_CNRM_ssp370_biomass_quarter3 skipjack CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 3 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_CNRM_ssp370_biomass_quarter4 skipjack CNRM SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 4 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other text/xml other other other other other geonode:SKJ_mean_GFDL_hist_biomass_quarter1 skipjack Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) GFDL quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_GFDL_hist_biomass_quarter2 skipjack Habitats and biotopes Regional quarter 2 historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other other text/xml other geonode:SKJ_mean_GFDL_hist_biomass_quarter3 skipjack Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 3 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_GFDL_hist_biomass_quarter4 skipjack Habitats and biotopes Regional historical (1985-2014) Habitat types and species distribution and range (Habitats Directive) quarter 4 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_GFDL_ssp126_biomass_quarter1 skipjack Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) GFDL quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other text/xml other other other other geonode:SKJ_mean_GFDL_ssp126_biomass_quarter2 skipjack Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional quarter 2 Habitat types and species distribution and range (Habitats Directive) GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_GFDL_ssp126_biomass_quarter3 skipjack Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 3 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_GFDL_ssp126_biomass_quarter4 skipjack Habitats and biotopes SSP1-2.6 climate scenario projection (2015-2070) Regional Habitat types and species distribution and range (Habitats Directive) quarter 4 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_GFDL_ssp370_biomass_quarter1 skipjack SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) GFDL quarter 1 EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 text/xml other other other other other other geonode:SKJ_mean_GFDL_ssp370_biomass_quarter2 skipjack SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional quarter 2 Habitat types and species distribution and range (Habitats Directive) GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_GFDL_ssp370_biomass_quarter3 skipjack SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 3 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other other other other text/xml other other geonode:SKJ_mean_GFDL_ssp370_biomass_quarter4 skipjack SSP3-7.0 climate scenario projection (2015-2070) Habitats and biotopes Regional Habitat types and species distribution and range (Habitats Directive) quarter 4 GFDL EPSG:4326 CRS:84 -100.125 25.125 -50.125 60.125 other text/xml other other other other other geonode:SyrFra_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of Syringammina fragilissima fields assemblage in the North East Atlantic. This community is considered ecologically coherent according to the cluster analysis conducted by Parry et al. (2015) on image sample. Modelling its distribution complements existing work on their definition and offers a representation of the extent of the areas of the North East Atlantic where they can occur based on the best available knowledge. This work was performed at the University of Plymouth in 2021. Habitats and biotopes Data not evaluated Syringammina fragilissima Brady 1883 Metadata conformant GeoTIFF WCS Marine/Coastal Species Distributions Models SyrFra_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode No limitations to public access ANE EPSG:4326 CRS:84 -34.670493943195595 14.199276906079788 45.71717449496695 65.1152400730628 other other other other other other text/xml geonode:a__8224_SpnMeg_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode No abstract provided _8224_SpnMeg_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode WCS Habitats and biotopes GeoTIFF EPSG:4326 CRS:84 -34.670493943195595 14.199276906079788 45.71717449496695 65.1152400730628 other other other other text/xml other other geonode:a__8225_SolScl_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode No abstract provided GeoTIFF WCS Habitats and biotopes _8225_SolScl_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode EPSG:4326 CRS:84 -34.670493943195595 14.199276906079788 45.71717449496695 65.1152400730628 other other other other text/xml other other geonode:a__8254_MixCor_RF_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode No abstract provided GeoTIFF Species distribution _8254_MixCor_RF_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode WCS EPSG:4326 CRS:84 -34.670493943195595 14.199276906079788 45.71717449496695 65.1152400730628 other other other other text/xml other other geonode:a__8255_SolRee_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode No abstract provided _8255_SolRee_Ens_Cont_Preds_Thresh_200m_GHO_Masked_reprojectedGeoNode Species distribution GeoTIFF WCS EPSG:4326 CRS:84 -34.670493943195595 14.199276906079788 45.71717449496695 65.1152400730628 other other other other text/xml other other geonode:catches_sum_SP10_Pollachius_virens Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Pollachius virens GeoTIFF catches_sum_SP10_Pollachius_virens WCS Species distribution EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP11_Engraulis_encrasicolus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. catches_sum_SP11_Engraulis_encrasicolus GeoTIFF Species distribution Engraulis encrasicolus WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP12_Katsuwonus_pelamis Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. GeoTIFF Species distribution WCS catches_sum_SP12_Katsuwonus_pelamis Katsuwonus pelamis EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP18_Thunnus_albacares Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. GeoTIFF Species distribution WCS Thunnus albacares catches_sum_SP18_Thunnus_albacares EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP19_Trachurus_trachurus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Trachurus trachurus GeoTIFF Species distribution WCS catches_sum_SP19_Trachurus_trachurus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP1_Clupea_harengus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Clupea harengus catches_sum_SP1_Clupea_harengus GeoTIFF Species distribution WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP21_Merluccius_merluccius Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Merluccius merluccius catches_sum_SP21_Merluccius_merluccius GeoTIFF WCS Species distribution EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP22_Reinhardtius_hippoglossoides Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. GeoTIFF WCS Species distribution catches_sum_SP22_Reinhardtius_hippoglossoides Reinhardtius hippoglossoides EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP23_Pleuronectes_platessa Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. catches_sum_SP23_Pleuronectes_platessa Pleuronectes platessa GeoTIFF Species distribution WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP28_Thunnus_obesus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Thunnus obesus GeoTIFF Species distribution catches_sum_SP28_Thunnus_obesus WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP2_Gadus_morhua Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Gadus morhua GeoTIFF Species distribution WCS catches_sum_SP2_Gadus_morhua EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP30_Trisopterus_esmarkii Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Trisopterus esmarkii GeoTIFF Species distribution WCS catches_sum_SP30_Trisopterus_esmarkii EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP31_Sebastes_mentella Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Sebastes mentella GeoTIFF Species distribution WCS catches_sum_SP31_Sebastes_mentella EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP34_Thunnus_alalunga Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. catches_sum_SP34_Thunnus_alalunga GeoTIFF Species distribution Thunnus alalunga WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP35_Molva_molva Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. catches_sum_SP35_Molva_molva Molva molva GeoTIFF WCS Species distribution EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP36_Xiphias_gladius Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Xiphias gladius GeoTIFF Species distribution WCS catches_sum_SP36_Xiphias_gladius EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP37_Merlangius_merlangus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. catches_sum_SP37_Merlangius_merlangus GeoTIFF Species distribution WCS Merlangius merlangus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP38_Trichiurus_lepturus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Trichiurus lepturus catches_sum_SP38_Trichiurus_lepturus Species distribution WCS GeoTIFF EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP3_Scomber_scombrus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. catches_sum_SP3_Scomber_scombrus GeoTIFF Species distribution Scomber scombrus WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other other text/xml other geonode:catches_sum_SP42_Solea_solea Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Solea solea catches_sum_SP42_Solea_solea GeoTIFF Species distribution WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP50_Platichthys_flesus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Platichthys flesus GeoTIFF WCS Species distribution catches_sum_SP50_Platichthys_flesus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP53_Zeus_faber Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. catches_sum_SP53_Zeus_faber GeoTIFF Species distribution WCS Zeus faber EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP5_Mallotus_villosus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Mallotus villosus GeoTIFF Species distribution WCS catches_sum_SP5_Mallotus_villosus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP61_Lophius_piscatorius Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Lophius piscatorius GeoTIFF Species distribution WCS catches_sum_SP61_Lophius_piscatorius EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP66_Coryphaena_hippurus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Coryphaena hippurus GeoTIFF Species distribution catches_sum_SP66_Coryphaena_hippurus WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP6_Micromesistius_poutassou Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. catches_sum_SP6_Micromesistius_poutassou GeoTIFF Species distribution WCS Micromesistius poutassou EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP71_Conger_conger Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. GeoTIFF WCS Species distribution Conger conger catches_sum_SP71_Conger_conger EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP76_Thunnus_thynnus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Thunnus thynnus WCS GeoTIFF Species distribution catches_sum_SP76_Thunnus_thynnus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP8_Melanogrammus_aeglefinus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. GeoTIFF WCS Species distribution catches_sum_SP8_Melanogrammus_aeglefinus Melanogrammus aeglefinus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:catches_sum_SP9_Sprattus_sprattus Maps of potential biomass catches (tons/year) per surface unit (0.25degrees latitude x 0.25degrees longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic. To map potential catches, first, mean catches (tons/year) were calculated according to Watson (2020) Global fisheries landings (V4) database for period 2010-2015 and then the total mean catch value for each species was redistributed according to the occurrence probability value that was modelled in 3-D using Shape-Constrained Generalized Additive Models (SC-GAMs). Potential catch value of each cell integrates the catches along the water column (from surface until 1000 m depth). See Valle et al. (2024) in Ecological Modelling for more details. Sprattus sprattus catches_sum_SP9_Sprattus_sprattus GeoTIFF Species distribution WCS EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 other other other other text/xml other other geonode:decadal_abundance_cold_temperate_copepods Long term follow up Acartia spp. Aetideus armatus North Atlantic Zooplankton Calanoida Pleuromamma robusta Species distribution Metridia lucens EPSG:4326 CRS:84 -45.0 10.0 43.0 65.0 1960-01-01T00:00:00.000Z,1960-03-12T00:00:00.000Z,1312706-12-01T00:00:00.000Z,292278984-08-16T07:12:55.807Z other other other other text/xml other other geonode:decadal_abundance_pseudo_oceanic_temperate_copepods Long term follow up Rhincalanus nasutus Eucalanus crassus Centropages typicus North Atlantic Candacia armata Zooplankton Calanoida Species distribution Calanus helgolandicus EPSG:4326 CRS:84 -45.0 10.0 43.0 65.0 1960-01-01T00:00:00.000Z,1970-01-01T00:00:00.000Z,1980-01-01T00:00:00.000Z,1990-01-01T00:00:00.000Z,2000-01-01T00:00:00.000Z,2010-01-01T00:00:00.000Z other other other other text/xml other other geonode:decadal_abundance_sub_artic_copepods Long term follow up Calanoida Heterorhabdus norvegicus Euchaeta norvegica Calanus finmarchicus North Atlantic Zooplankton Scolecithricella spp. Species distribution EPSG:4326 CRS:84 -45.0 10.0 43.0 65.0 1960-01-01T00:00:00.000Z,1970-01-01T00:00:00.000Z,1980-01-01T00:00:00.000Z,1990-01-01T00:00:00.000Z,2000-01-01T00:00:00.000Z,2010-01-01T00:00:00.000Z other other other other text/xml other other geonode:decadal_abundance_warm_temperate_copepods Pleuromamma xiphias Calocalanus spp. Pleuromamma piseki Pleuromamma abdominalis Undeuchaeta plumosa Mecynocera clausi Nannocalanus minor Calanoida Euchirella rostrata Long term follow up Mesocalanus tenuicornis Euchaeta acuta Zooplankton Species distribution Heterorhabdus papilliger Pleuromamma borealis Pleuromamma gracilis Neocalanus gracilis Clausocalanus spp. North Atlantic Centropages bradyi EPSG:4326 CRS:84 -45.0 10.0 43.0 65.0 1960-01-01T00:00:00.000Z,1968170-02-01T00:00:00.000Z,292278984-08-16T07:12:55.807Z other other other other text/xml other other geonode:habitat_eez The dataset contains the shapefile of marine benthic broad habitats classified according to EUNIS classification for the Brazilian Exclusive Economic Zone region. It was developed using open access databases and GIS operations to develop two intermediate layers: (i) biological zones and (ii) substrate type. Both layers were combined to form the first continuous map of marine habitats for the entire region. habitat_eez features EPSG:4326 CRS:84 -53.373234543183834 -25.29094733519388 -37.24515427664852 8.742758415082022 other other other other text/xml other other geonode:mldr10_1 mldr10_1 WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z other other other text/xml other other other geonode:occurrence_probability_Clupea_harengus Species distribution Clupea harengus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1.577058305E9,-1.493172225E9,-1.409286145E9,-1.325400065E9,-1.241513985E9,-9764865.0,-8126465.0,-6488065.0,-95745.0,-70145.0,-63745.0,-57345.0,-50945.0,-44545.0,-950.0,-850.0,-750.0,-650.0,-550.0,-475.0,-425.0,-375.0,-325.0,-300.0,-65.0,-60.0,-55.0,-50.0,-40.0,-30.0,-20.0,-10.0,-5.0,0.0,126417.0,1.634037877E9,1.969712741E9 other other other other text/xml other other geonode:occurrence_probability_Conger_conger Species distribution Conger conger EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Coryphaena_hippurus Species distribution Coryphaena hippurus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Engraulis_encrasicolus Species distribution Engraulis encrasicolus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Gadus_morhua Species distribution Gadus morhua EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Katsuwonus_pelamis Species distribution Katsuwonus pelamis EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -2.65617409E8,-6.2193665E7,-5.5640065E7,-4.9086465E7,-650.0,-550.0,-475.0,-425.0,-375.0,-325.0,-275.0,-225.0,-175.0,-125.0,-95.0,-85.0,-75.0,-65.0,-55.0,-45.0,-35.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0,1.818587168E9,2.004185972E9 other other other other text/xml other other geonode:occurrence_probability_Lophius_piscatorius Species distribution Lophius piscatorius EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Mallotus_villosus Species distribution Mallotus villosus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Melanogrammus_aeglefinus Species distribution Melanogrammus aeglefinus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Merlangius_merlangus Species distribution Merlangius merlangus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Merluccius_merluccius Species distribution Merluccius merluccius EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Micromesistius_poutassou Species distribution Micromesistius poutassou EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 text/xml other other other other other other geonode:occurrence_probability_Molva_molva Species distribution Molva molva EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Platichthys_flesus Platichthys flesus Species distribution EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Pleuronectes_platessa Species distribution Pleuronectes platessa EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -242945.0,-230145.0,-217345.0,-204545.0,-178945.0,-153345.0,-127745.0,-121345.0,-114945.0,-102145.0,-95745.0,-82945.0,-76545.0,-70145.0,-63745.0,-50945.0,-38145.0,-425.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-75.0,-70.0,-60.0,-50.0,-45.0,-35.0,-25.0,-15.0,-10.0,-5.0,0.0,24947.0,3.2548863E7,1.819287667E9,1.852797557E9 text/xml other other other other other other geonode:occurrence_probability_Pollachius_virens Species distribution Pollachius virens EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Reinhardtius_hippoglossoides Reinhardtius hippoglossoides Species distribution EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -2.57359873E8,-8.388608E7,-6.2193665E7,-5.5640065E7,-5.2363265E7,-4.5809665E7,-3.1064065E7,-2.7787265E7,-2.6148865E7,-1.9595265E7,-1.7956865E7,-1.4680065E7,-1.1403265E7,-9764865.0,-6488065.0,-5832705.0,-5177345.0,-4849665.0,-4521985.0,-3866625.0,-3211265.0,-2883585.0,-2555905.0,-153345.0,-82945.0,-21505.0,-25.0,-20.0,-15.0,-10.0,0.0,29541.0,1.634233961E9,1.699872769E9,1.746957173E9,1.76923557E9,1.869639785E9,1.936682087E9 other other other other text/xml other other geonode:occurrence_probability_Scomber_scombrus Species distribution Scomber scombrus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -2.65289729E8,-1.50994945E8,-6.5470465E7,-6.2193665E7,-2.4510465E7,-2.2872065E7,-2.1233665E7,-1.9595265E7,-1.7956865E7,-1.6318465E7,-1900545.0,-1572865.0,-1245185.0,-917505.0,-44545.0,-38145.0,-31745.0,-25345.0,-24065.0,-22785.0,-20225.0,-18945.0,-17665.0,-16385.0,-15105.0,-13825.0,-12545.0,-11265.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-475.0,-450.0,-425.0,-400.0,-375.0,-35.0,-5.0,0.0,29557.0,1.666383873E9,1.66848933E9,1.919053167E9 text/xml other other other other other other geonode:occurrence_probability_Sebastes_mentella Species distribution Sebastes mentella EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1.97971149E9,-1.56028109E9,-1.14085069E9,-1.6318465E7,-1.4680065E7,-1.3041665E7,-6488065.0,-6160385.0,-5832705.0,-5505025.0,-5177345.0,-4849665.0,-76545.0,-38145.0,-31745.0,-25345.0,-1000.0,-950.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-15.0,-10.0,-5.0,0.0,127254.0,6.37534206E8,1.056964606E9,1.633838419E9,1.852140832E9,1.895825406E9,1.936028787E9 other other other other text/xml other other geonode:occurrence_probability_Solea_solea Species distribution Solea solea EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Sprattus_sprattus Species distribution Sprattus sprattus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Thunnus_alalunga Species distribution Thunnus alalunga EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Thunnus_albacares Thunnus albacares Species distribution EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Thunnus_obesus Thunnus obesus Species distribution EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Thunnus_thynnus Thunnus thynnus Species distribution EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Trachurus_trachurus Species distribution Trachurus trachurus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 -1000.0,-950.0,-900.0,-850.0,-800.0,-750.0,-700.0,-650.0,-600.0,-550.0,-500.0,-475.0,-450.0,-425.0,-400.0,-375.0,-350.0,-325.0,-300.0,-275.0,-250.0,-225.0,-200.0,-175.0,-150.0,-125.0,-100.0,-95.0,-90.0,-85.0,-80.0,-75.0,-70.0,-65.0,-60.0,-55.0,-50.0,-45.0,-40.0,-35.0,-30.0,-25.0,-20.0,-15.0,-10.0,-5.0,0.0 other other other other text/xml other other geonode:occurrence_probability_Trichiurus_lepturus Species distribution Trichiurus lepturus EPSG:4326 CRS:84 -98.0 68.5 -83.0 90.0 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-5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 text/xml other other other other other other geonode:thetao_con thetao_con WCS NetCDF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 1900-01-01T00:00:00.000Z -5500.0,-5000.0,-4500.0,-4000.0,-3500.0,-3000.0,-2500.0,-2000.0,-1750.0,-1500.0,-1400.0,-1300.0,-1200.0,-1100.0,-1000.0,-900.0,-800.0,-700.0,-600.0,-500.0,-400.0,-300.0,-250.0,-200.0,-150.0,-125.0,-100.0,-75.0,-50.0,-30.0,-20.0,-10.0,-0.5 other text/xml other other other other other geonode:uop_xenos_density No abstract provided uop_xenos_density WCS GeoTIFF EPSG:32628 CRS:84 -13.577366382816892 -13.519057461192377 58.37582363551167 58.399503949403936 other other other other text/xml other other