BCO-DMO ERDDAP
Accessing BCO-DMO data

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Dataset Title:	[Abyssal megafauna capture records] - Capture records of abyssal megafauna captured using submersibles and ROVs at Station ALOHA off Hawaii and Station M off California from 2019 to 2020 (Collaborative Research: Assessing the relative importance of small vs large particles as sources of nutrition to abyssal communities)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_922718_v1)
Range:	longitude = -158.0 to -123.06°E
Information:	Summary \| License \| Metadata \| Background \| Data Access Form \| Files

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Constraints	Optional Constraint #1		Optional Constraint #2

Server-side Functions

distinct()

Hover here to see a list of options. Click on an option to select it.

Graph Settings

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[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 {
 s {
  Cruise_number {
    String long_name "Cruise_number";
    String units "unitless";
  }
  sample_code {
    String long_name "Sample_code";
    String units "unitless";
  }
  Sample {
    Int32 actual_range 1, 181;
    String long_name "Sample";
    String units "unitless";
  }
  Station {
    String long_name "Station";
    String units "unitless";
  }
  Station_Latitude {
    Float32 actual_range 22.75, 34.5;
    String long_name "Station_latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -158.0, -123.06;
    String axis "X";
    String ioos_category "Location";
    String long_name "Station_longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  local_date {
    String long_name "Local_date";
    String units "unitless";
  }
  Type_of_organism {
    String long_name "Type_of_organism";
    String units "unitless";
  }
  species {
    String long_name "Species";
    String units "unitless";
  }
  number {
    String long_name "Number";
    String units "unitless";
  }
  Total_Length_cm {
    String long_name "Total_length_cm";
    String units "centimeters (cm)";
  }
  Standard_Length_cm {
    String long_name "Standard_length_cm";
    String units "centimeters (cm)";
  }
  PreAnal_Fin_Length_cm {
    String long_name "Preanal_fin_length_cm";
    String units "centimeters (cm)";
  }
  Carapace_Length_mm {
    Float32 actual_range 1.6, 4.1;
    String long_name "Carapace_length_mm";
    String units "millimeters (mm)";
  }
  Mass_g {
    String long_name "Mass_g";
    String units "grams (g)";
  }
  sex {
    String long_name "Sex";
    String units "unitless";
  }
  Tissue_fin_clip {
    String long_name "Tissue_fin_clip";
    String units "unitless";
  }
  Tissue_whole_body {
    String long_name "Tissue_whole_body";
    String units "unitless";
  }
  Tissue_white_muscle {
    String long_name "Tissue_white_muscle";
    String units "unitless";
  }
  Tissue_gut_removed {
    String long_name "Tissue_gut_removed";
    String units "unitless";
  }
  Tissue_body_wall {
    String long_name "Tissue_body_wall";
    String units "unitless";
  }
  Tissue_liver {
    String long_name "Tissue_liver";
    String units "unitless";
  }
  Tissue_pereiopod {
    String long_name "Tissue_pereiopod";
    String units "unitless";
  }
  Tissue_pleopod {
    String long_name "Tissue_pleopod";
    String units "unitless";
  }
  number_cryovials {
    Int32 actual_range 1, 4;
    String long_name "Number_cryovials";
    String units "unitless";
  }
  pics {
    String long_name "Pics";
    String units "unitless";
  }
  whole_body_fate {
    String long_name "Whole_body_fate";
    String units "unitless";
  }
  container_size {
    String long_name "Container_size";
    String units "unitless";
  }
  comments {
    String long_name "Comments";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String doi "10.26008/1912/bco-dmo.922718.1";
    Float64 Easternmost_Easting -123.06;
    Float64 geospatial_lon_max -123.06;
    Float64 geospatial_lon_min -158.0;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-08T06:19:40Z (local files)
2024-11-08T06:19:40Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_922718_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/922718";
    String institution "BCO-DMO";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String sourceUrl "(local files)";
    String summary "This dataset includes the capture records for the abyssal megafauna captured as part of this food web project. Megafauna were captured using submersibles and ROVs at Station ALOHA off Hawaii and Station M off California from 2019 to 2020. These animals were captured as representatives of their abyssal food webs for an isotopic investigation of their original particulate nutritional sources (different sized particles). Each organism was identified, measured, most weighed using a motion compensated scale, and frozen for later drying and isotope analysis. For larger organisms such as holothurians or fishes, samples of tissues were taken and often the whole animal was preserved for later confirmation of taxonomic identification.";
    String title "[Abyssal megafauna capture records] - Capture records of abyssal megafauna captured using submersibles and ROVs at Station ALOHA off Hawaii and Station M off California from 2019 to 2020 (Collaborative Research: Assessing the relative importance of small vs large particles as sources of nutrition to abyssal communities)";
    Float64 Westernmost_Easting -158.0;
  }
}

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link)

Data Access Protocol (DAP) (external link)

and its selection 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 or Subset form. They make 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.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

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