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Shapefile of Atlantic Seabed Areas - Results of a basin-wide cluster analysis of the Atlantic near seafloor environment

This data set presents the results of an automated cluster analysis using Gaussian mixture models of the entire Atlantic seafloor environment. The analysis was based on eight global datasets and their derivatives: Bathymetry, slope, terrain ruggedness index, topographic position index, sediment thickness, POC flux, salinity, dissolved oxygen, temperature, current velocity, and phytoplankton abundance in surface waters along with seasonal variabilities (see Source data set). We obtained nine seabed areas (SBAs) that portray the Atlantic seafloor that are shown as polygons in the data set. The attribute table holds short descriptions of each SBA as well as about the colours used in the accompanying paper publication. Data sets like this can be used for further analysis like e.g. for landscape ecology metrics to identify regions of interest. The compressed file further contains a style file that can be used to directly load the correct style in the QGIS software package.

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Cite this as

Schumacher, Mia, Huvenne, Veerle A I, Devey, Colin W, Martínez-Arbizu, Pedro, Biastoch, Arne, Meinecke, Stefan (2022). Dataset: Shapefile of Atlantic Seabed Areas - Results of a basin-wide cluster analysis of the Atlantic near seafloor environment. https://doi.org/10.1594/PANGAEA.946690

DOI retrieved: 2022

Additional Info

Field Value
Imported on November 30, 2024
Last update November 30, 2024
License CC-BY-4.0
Source https://doi.org/10.1594/PANGAEA.946690
Author Schumacher, Mia
Given Name Mia
Family Name Schumacher
More Authors
Huvenne, Veerle A I
Devey, Colin W
Martínez-Arbizu, Pedro
Biastoch, Arne
Meinecke, Stefan
Source Creation 2022
Publication Year 2022
Resource Type text/tab-separated-values - filename: Schumacher-etal_2022_Shapefile_Atlantic_Seabed_Areas
Subject Areas
Name: Ecology

Related Identifiers
Title: The Atlantic Ocean landscape: A basin-wide cluster analysis of the Atlantic near seafloor environment
Identifier: https://doi.org/10.3389/fmars.2022.936095
Type: DOI
Relation: References
Year: 2022
Source: Frontiers in Marine Science
Authors: Schumacher Mia , Huvenne Veerle A I , Devey Colin W , Martínez Arbizu Pedro , Biastoch Arne , Meinecke Stefan , Copernicus Services , Copernicus Services , Straume EO , Gaina Carmen , Medvedev S , Hochmuth Katharina , Gohl Karsten , Whittaker Joanne , Abdul Fattah R , Doornenbal J C , Hopper J R .

Title: Copernicus Marine Data Store
Identifier: https://data.marine.copernicus.eu/products
Type: DOI
Relation: References
Source: https://data.marine.copernicus.eu/products
Authors: Schumacher Mia , Huvenne Veerle A I , Devey Colin W , Martínez Arbizu Pedro , Biastoch Arne , Meinecke Stefan , Copernicus Services , Copernicus Services , Straume EO , Gaina Carmen , Medvedev S , Hochmuth Katharina , Gohl Karsten , Whittaker Joanne , Abdul Fattah R , Doornenbal J C , Hopper J R .

Title: Copernicus Marine Data Store / Shuttle Radar Topography Mission / Open topography
Identifier: https://data.marine.copernicus.eu/products
Type: DOI
Relation: References
Source: https://data.marine.copernicus.eu/
Authors: Schumacher Mia , Huvenne Veerle A I , Devey Colin W , Martínez Arbizu Pedro , Biastoch Arne , Meinecke Stefan , Copernicus Services , Copernicus Services , Straume EO , Gaina Carmen , Medvedev S , Hochmuth Katharina , Gohl Karsten , Whittaker Joanne , Abdul Fattah R , Doornenbal J C , Hopper J R .

Title: GlobSed: Updated Total Sediment Thickness in the World's Oceans
Identifier: https://doi.org/10.1029/2018GC008115
Type: DOI
Relation: References
Year: 2019
Source: World Data Service for Geophysics: https://www.ngdc.noaa.gov/mgg/sedthick/
Authors: Schumacher Mia , Huvenne Veerle A I , Devey Colin W , Martínez Arbizu Pedro , Biastoch Arne , Meinecke Stefan , Copernicus Services , Copernicus Services , Straume EO , Gaina Carmen , Medvedev S , Hochmuth Katharina , Gohl Karsten , Whittaker Joanne , Abdul Fattah R , Doornenbal J C , Hopper J R .