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Dataset Title:	[STING N2 Fixation Rates AE2305 and EN704] - N2 Fixation Rates Collected on STINGI and STINGII Cruises aboard the R/V Atlantic Explorer, cruise AE2305, and the R/V Endeavor, cruise EN704, on the West Florida Shelf (Collaborative Research: Linking iron and nitrogen sources in an oligotrophic coastal margin: Nitrogen fixation and the role of boundary fluxes)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_997130_v1)
Range:	longitude = -86.567 to -82.515°E, latitude = 26.141 to 28.498°N, depth = 0.8 to 80.0m, time = 2023-02-21T15:46:00Z to 2023-07-12T11:21:00Z
Information:	Summary \| License \| FGDC \| ISO 19115 \| 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 {
  Cruise {
    String long_name "Cruise";
    String units "unitless";
  }
  DateTime_local_Eastern {
    String long_name "Datetime_local_eastern";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.67699436e+9, 1.68916086e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  STING_ID {
    Int32 actual_range 3, 344;
    String long_name "Sting_id";
    String units "unitless";
  }
  Station {
    String long_name "Station";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 0.8, 80.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 26.141, 28.498;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -86.567, -82.515;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Collection {
    String long_name "Collection";
    String units "unitless";
  }
  Type {
    String long_name "Type";
    String units "unitless";
  }
  NFixSampleNum {
    Int32 actual_range 1, 271;
    String long_name "Nfixsamplenum";
    String units "unitless";
  }
  APN_t0 {
    Float32 actual_range 0.3641, 0.3682;
    String long_name "Apn_t0";
    String units "atom %";
  }
  FLAG_APN_t0 {
    String long_name "Flag_apn_t0";
    String units "unitless";
  }
  vol {
    Float32 actual_range 0.5, 4.65;
    String long_name "Vol";
    String units "liters";
  }
  PN_tf_nM {
    Int32 actual_range 244, 6290;
    String long_name "Pn_tf_nm";
    String units "nanomolar";
  }
  APN_tf {
    Float32 actual_range 0.3684, 0.7397;
    String long_name "Apn_tf";
    String units "atom %";
  }
  Inc_length_d {
    Float32 actual_range 0.964, 1.086;
    String long_name "Inc_length_d";
    String units "days";
  }
  AN2 {
    Float32 actual_range 0.91, 3.9;
    String long_name "An2";
    String units "atom %";
  }
  AN2_flag {
    String long_name "An2_flag";
    String units "unitless";
  }
  SUR_d {
    Float32 actual_range 0.0011, 0.3109;
    String long_name "Sur_d";
    String units "per day";
  }
  SUR_LOD_d {
    Float32 actual_range 2.0e-4, 0.0011;
    String long_name "Sur_lod_d";
    String units "per day";
  }
  SUR_LOQ_d {
    Float32 actual_range 6.0e-4, 0.0037;
    String long_name "Sur_loq_d";
    String units "per day";
  }
  SUR_Flag {
    String long_name "Sur_flag";
    String units "unitless";
  }
  NFR_nmolNLd {
    Float32 actual_range 1.11, 866.11;
    String long_name "Nfr_nmolnld";
    String units "nanomoles nitrogen per liter per day";
  }
  NFR_LOD_nmolNLd {
    Float32 actual_range 0.07, 3.4;
    String long_name "Nfr_lod_nmolnld";
    String units "nanomoles nitrogen per liter per day";
  }
  NFR_LOQ_nmolNLd {
    Float32 actual_range 0.24, 11.34;
    String long_name "Nfr_loq_nmolnld";
    String units "nanomoles nitrogen per liter per day";
  }
  NFR_Flag {
    String long_name "Nfr_flag";
    String units "unitless";
  }
  NfixSTING_ID {
    Int32 actual_range 3, 344;
    String long_name "Nfixsting_id";
    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 defaultDataQuery "&amp;time&lt;now";
    String doi "10.26008/1912/bco-dmo.997130.1";
    Float64 Easternmost_Easting -82.515;
    Float64 geospatial_lat_max 28.498;
    Float64 geospatial_lat_min 26.141;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -82.515;
    Float64 geospatial_lon_min -86.567;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 80.0;
    Float64 geospatial_vertical_min 0.8;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2026-05-26T23:05:43Z (local files)
2026-05-26T23:05:43Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_997130_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/997130";
    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.";
    Float64 Northernmost_Northing 28.498;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 26.141;
    String summary 
"The West Florida Shelf (WFS) is a coastal oligotrophic region characterized by low inorganic nutrient concentrations; yet it often supports a diverse array of phytoplankton blooms, including those of the dinitrogen (N2)-fixing cyanobacterium Trichodesmium. 
This dataset includes incubation details and calculated average N2 fixation rates (NFR) and specific uptake rates (SUR) from incubations predominantly performed with WFS surface waters, as well as two near-surface rates from the chlorophyll maximum. This dataset is part of a collaborative effort (the STING project) to constrain the fluxes and fates of macronutrients and trace metals from boundary sources and to evaluate their impacts on N2 fixation on the WFS. This dataset includes SUR/NFR from two cruises on the shelf, with multiple inshore-offshore transects in contrasting wet/dry seasons, where coordinated sampling was conducted for inorganic and organic nutrients, trace metals, radium isotopes, Trichodesmium and other diazotroph gene abundance, and NFR/SUR.";
    String time_coverage_end "2023-07-12T11:21:00Z";
    String time_coverage_start "2023-02-21T15:46:00Z";
    String title "[STING N2 Fixation Rates AE2305 and EN704] - N2 Fixation Rates Collected on STINGI and STINGII Cruises aboard the R/V Atlantic Explorer, cruise AE2305, and the R/V Endeavor, cruise EN704, on the West Florida Shelf (Collaborative Research: Linking iron and nitrogen sources in an oligotrophic coastal margin: Nitrogen fixation and the role of boundary fluxes)";
    Float64 Westernmost_Easting -86.567;
  }
}

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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