Make A Graph

Dataset Title:	Potential biomass catches (tons/year) per surface unit (0.25º latitude x 0.25º longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic
Institution:	BRTA (Dataset ID: biology_8461_cafa_bd5b_f2a3)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

Start

Stop

aphiaid (level)

specify just 1 value →

latitude (degrees_north)

longitude (degrees_east)

Graph Settings
Color Bar:	Continuity:	Scale:
Minimum:	Maximum:	N Sections:
Draw land mask:
Y Axis Minimum:	Maximum:

(Please be patient. It may take a while to get the data.)

Optional:
Then set the File Type: (File Type information)
and

or view the URL:
(Documentation / Bypass this form

)

Click on the map to specify a new center point.

Zoom:

[The graph you specified. Please be patient.]

Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  aphiaid {
    Int32 actual_range 126285, 127427;
    String long_name "Life Science Identifier - World Register of Marine Species";
    String units "level";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range -82.875, 89.875;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -97.875, 68.375;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  potential_catches {
    Float64 _FillValue -99999.0;
    String long_name "Potential biomass catch";
    String units "tons year-1";
  }
  NC_GLOBAL {
    String acknowledgement "We acknowledge Ocean Biodiversity Information System (OBIS; https://obis.org/) and the Global Biodiversity Information Facility (GBIF; https://www.gbif.org/) for providing fish global occurrences studied here. We also thank to publicly available datasets Copernicus (http://marine.copernicus.eu/services-portfolio/access-to-products/) and the World Ocean Atlas (https://www.ncei.noaa.gov/products/world-ocean-atlas) for providing environmental data";
    String cdm_data_type "Grid";
    String citation "Valle, M., E. RamÃrez-Romero, L. Ibaibarriaga, L. Citores, J. A. Fernandes-Salvador, and G. Chust. 2024. Pan-Atlantic 3D distribution model incorporating water column for commercial fish. Ecological Modelling 490:110632. https://doi.org/10.1016/j.ecolmodel.2024.110632";
    String comment "Uses attributes recommended by https://cfconventions.org";
    String Conventions "CF-1.8, COARDS, ACDD-1.3";
    String creator_email "mvalle@azti.es";
    String creator_institution "AZTI, Marine research, Basque Research and Technology Alliance (BRTA)";
    String creator_name "Mireia Valle";
    String creator_type "person";
    String creator_url "www.azti.es";
    String date_created "2024-07-24";
    Float64 Easternmost_Easting 68.375;
    Float64 geospatial_lat_max 89.875;
    Float64 geospatial_lat_min -82.875;
    Float64 geospatial_lat_resolution 0.25;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 68.375;
    Float64 geospatial_lon_min -97.875;
    Float64 geospatial_lon_resolution 0.25;
    String geospatial_lon_units "degrees_east";
    String history 
"Thu Jul 25 15:47:06 2024: ncatted -O -a units,potential_catches,o,c,tons year-1 sum_catches.nc
Thu Jul 25 15:46:59 2024: ncatted -O -a units,aphiaid,c,c,level sum_catches.nc
Thu Jul 25 15:46:18 2024: ncatted -O -a units,potential_catches,o,c,tons year-1 sum_catches.nc
Thu Jul 25 15:46:18 2024: ncatted -O -a units,aphiaid,c,c,level sum_catches.nc
https://github.com/missionatlantic/3D_SDMs_AtlanticFish
2025-10-27T23:02:14Z (local files)
2025-10-27T23:02:14Z https://erddap.emodnet.eu/griddap/biology_8461_cafa_bd5b_f2a3.das";
    String infoUrl "www.azti.es";
    String institution "BRTA";
    String keywords "0.25\\u00c2\\u00ba, 3-d, aphiaid, atlantic, based, biomass, brta, catch, catches, commercial, data, fish, latitude, longitude, main, occurrence, per, potential, potential_catches, probability, species, surface, tons, unit, year";
    String license "CC-BY";
    String naming_authority "emodnet-biology.eu";
    String NCO "netCDF Operators version 5.0.6 (Homepage = http://nco.sf.net, Code = https://github.com/nco/nco)";
    Float64 Northernmost_Northing 89.875;
    String project "MISSION ATLANTIC project-European Unionâ€™s Horizon 2020 research and innovation programme under grant agreements No 862428";
    String publisher_email "bio@emodnet.eu";
    String publisher_institution "Flanders Marine Institute (VLIZ)";
    String publisher_name "EMODnet Biology Data Management Team";
    String publisher_type "group";
    String publisher_url "www.emodnet-biology.eu";
    String source "https://github.com/missionatlantic/3D_SDMs_AtlanticFish";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -82.875;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "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 490:110632 (https://doi.org/10.1016/j.ecolmodel.2024.110632), for more details";
    String title "Potential biomass catches (tons/year) per surface unit (0.25º latitude x 0.25º longitude) based on 3-D probability of occurrence for the main commercial fish species of the Atlantic";
    Float64 Westernmost_Easting -97.875;
  }
}

Using griddap to Request Data and Graphs from Gridded Datasets

griddap lets you request a data subset, graph, or map from a gridded dataset (for example, sea surface temperature data from a satellite), via a specially formed URL. griddap uses the OPeNDAP (external link)

Data Access Protocol (DAP) (external link)

and its projection constraints (external link)

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

(easy) You can get data by using the dataset's Data Access Form. It makes the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

griddap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.htmlTable?analysed_sst[(2002-06-01T09:00:00Z)][(-89.99):1000:(89.99)][(-179.99):1000:(180.0)]
Thus, the query is often a data variable name (e.g., analysed_sst), followed by [(start):stride:(stop)] (or a shorter variation of that) for each of the variable's dimensions (for example, [time][latitude][longitude]).

For details, see the griddap Documentation.