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Dataset Title:	[2022 CBL Seine Dissection Results] - Stomach dissection results from fish caught in Chesapeake Biological Laboratory's seine survey in Summer 2022 (Planktonic Omnivores and Stable Isotopes: Developing, Validating and Field-testing a Multi-species Functional Response Model)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_986256_v1)
Information:	Summary \| License \| Metadata \| Background \| Data Access Form \| Files

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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 {
  Fish_ID {
    Int32 actual_range 1, 159;
    String long_name "Fish_id";
    String units "unitless";
  }
  Date_Caught {
    String long_name "Date_caught";
    String units "unitless";
  }
  Location_Survey {
    String long_name "Location_survey";
    String units "unitless";
  }
  Species {
    String long_name "Species";
    String units "unitless";
  }
  TotalLength_mm {
    Int32 actual_range 35, 417;
    String long_name "Totallength_mm";
    String units "millimeters (mm)";
  }
  Weight_g {
    Float32 actual_range 0.24, 718.0;
    String long_name "Weight_g";
    String units "grams (g)";
  }
  Full_stomach_wt_g {
    Float32 actual_range 0.0023, 14.74;
    String long_name "Full_stomach_wt_g";
    String units "grams (g)";
  }
  Empty_stomach_wt_g {
    Float32 actual_range 3.0e-4, 12.02;
    String long_name "Empty_stomach_wt_g";
    String units "grams (g)";
  }
  Mysids_count {
    Int32 actual_range 0, 30;
    String long_name "Mysids_count";
    String units "unitless";
  }
  Mysids_present {
    Int32 actual_range 0, 1;
    String long_name "Mysids_present";
    String units "unitless";
  }
  Amphipods {
    Int32 actual_range 0, 1;
    String long_name "Amphipods";
    String units "unitless";
  }
  Polychetes {
    Int32 actual_range 0, 1;
    String long_name "Polychetes";
    String units "unitless";
  }
  Unid_crustacean {
    Int32 actual_range 0, 1;
    String long_name "Unid_crustacean";
    String units "unitless";
  }
  Copeods {
    Int32 actual_range 0, 1;
    String long_name "Copeods";
    String units "unitless";
  }
  Isopods {
    Int32 actual_range 0, 1;
    String long_name "Isopods";
    String units "unitless";
  }
  Barnacles {
    Int32 actual_range 0, 1;
    String long_name "Barnacles";
    String units "unitless";
  }
  Miscellaneous_larvae {
    Int32 actual_range 0, 1;
    String long_name "Miscellaneous_larvae";
    String units "unitless";
  }
  Insects {
    Int32 actual_range 0, 1;
    String long_name "Insects";
    String units "unitless";
  }
  Fish {
    Int32 actual_range 0, 1;
    String long_name "Fish";
    String units "unitless";
  }
  Foliage {
    Int32 actual_range 0, 1;
    String long_name "Foliage";
    String units "unitless";
  }
  Diatoms {
    Int32 actual_range 0, 1;
    String long_name "Diatoms";
    String units "unitless";
  }
  Potential_parasites {
    Int32 actual_range 0, 1;
    String long_name "Potential_parasites";
    String units "unitless";
  }
  Items {
    String long_name "Items";
    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.986256.1";
    String history 
"2025-11-19T03:18:01Z (local files)
2025-11-19T03:18:01Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_986256_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/986256";
    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 results from the dissection of stomach contents of fish caught from a yearly seine survey (May-October) conducted by Chesapeake Biological Laboratory (CBL). The fish were kept based on morphology, where those that could physically consume a mysid shrimp were kept and frozen to be dissected at a later date. The dissection data include the individual fish identification number, date the fish was caught, location fish was caught, species of fish, total length of fish, full and empty weights of the fish, and the presence of various prey items (unidentifiable material, amphipods, polychaetes, mysids, unidentifiable crustaceans, isopods, barnacles, bivalves, miscellaneous larvae, insects, fish, foliage, diatoms, algae, potential parasites), the items found in the stomachs, and comments about each dissection. Dissections took place from September 2022 to January 2023. Laboratory scalpels and forceps were used to remove the organs from the fish, and a dissecting microscope was used to identify the stomach contents visually. Sampling was done by various students and technicians at Chesapeake Biological Laboratory, and dissections were done by Lael Collins.";
    String title "[2022 CBL Seine Dissection Results] - Stomach dissection results from fish caught in Chesapeake Biological Laboratory's seine survey in Summer 2022 (Planktonic Omnivores and Stable Isotopes: Developing, Validating and Field-testing a Multi-species Functional Response Model)";
  }
}

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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