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Dataset Title:  [Sciaenid egg identification] - Identity of sciaenid eggs collected from the
Gulf of Mexico Estuary near Port Aransas, Texas from 2020 to 2022 (Counter-
gradient Flow of Fatty Acids in Marine Food Webs Through Egg Boons)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_878631_v2)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | 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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Egg_size {
    String long_name "Egg_size";
    String units "millimeters";
  }
  Collection_date {
    String long_name "Collection_date";
    String units "unitless";
  }
  UIN {
    String long_name "Uin";
    String units "unitless";
  }
  Site {
    String long_name "Site";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  DNA_extraction_date {
    String long_name "Dna_extraction_date";
    String units "unitless";
  }
  Date_analyzed {
    String long_name "Date_analyzed";
    String units "unitless";
  }
  Red_Drum {
    String long_name "Red_drum";
    String units "unitless";
  }
  Gulf_Kingfish {
    String long_name "Gulf_kingfish";
    String units "unitless";
  }
  Southern_Kingfish {
    String long_name "Southern_kingfish";
    String units "unitless";
  }
  Spotted_Seatrout {
    String long_name "Spotted_seatrout";
    String units "unitless";
  }
  Atlantic_Croaker {
    String long_name "Atlantic_croaker";
    String units "unitless";
  }
  Black_Drum {
    String long_name "Black_drum";
    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.878631.2";
    String geospatial_lat_units "degrees_north";
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-14T04:52:17Z (local files)
2024-11-14T04:52:17Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_878631_v2.das";
    String infoUrl "https://www.bco-dmo.org/dataset/878631";
    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 represents the identity (based on PCR results) of sciaenid eggs from the Gulf of Mexico Estuary near Port Aransas, Texas. Egg samples were collected from 20 August, 2020 through 8 March, 2022 from the research pier at UTMSI, located in the Aransas Pass inlet. Egg samples were collected bi-weekly during the Red Drum spawning season (August – December) and monthly outside the Red drum spawning season from two locations. Eggs were sorted by morphology to isolate sciaenid eggs and molecular PCR techniques were applied to subsamples of eggs to confirm the species identification.";
    String title "[Sciaenid egg identification] - Identity of sciaenid eggs collected from the Gulf of Mexico Estuary near Port Aransas, Texas from 2020 to 2022 (Counter-gradient Flow of Fatty Acids in Marine Food Webs Through Egg Boons)";
  }
}

 

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.

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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