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Dataset Title:	[BLOOFINZ-IO Flow Cytometry Abundance] - Abundances of phytoplankton and non- pigmented bacteria determined by flow cytometry from water samples collected on R/V Roger Revelle cruise RR2201 in the Eastern Indian Ocean during February and March 2022 (Collaborative Research: Mesoscale variability in nitrogen sources and food-web dynamics supporting larval southern bluefin tuna in the eastern Indian Ocean)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_916288_v1)
Range:	longitude = 114.1351 to 121.4977°E, depth = 5.0 to 120.0m, time = 2002-02-09T18:57:00Z to 2022-03-02T03:54:00Z
Information:	Summary \| License \| Metadata \| Background \| Data Access Form \| Files

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Constraints	Optional Constraint #1		Optional Constraint #2

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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";
  }
  Station {
    String long_name "Station";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.01328102e+9, 1.64619324e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Iso_datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  Date {
    String long_name "Date";
    String units "unitless";
  }
  Latitude {
    Float32 actual_range -17.12632, -13.174;
    String long_name "Latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 114.1351, 121.4977;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  CTD_Number {
    String long_name "Ctd_number";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 5, 120;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  PRO {
    Int32 actual_range 12112, 343386;
    String long_name "Pro";
    String units "cells per milliliter";
  }
  SYN {
    Int32 actual_range 4, 6628;
    String long_name "Syn";
    String units "cells per milliliter";
  }
  PEUK {
    Int32 actual_range 112, 10712;
    String long_name "Peuk";
    String units "cells per milliliter";
  }
  HBACT {
    Int32 actual_range 192242, 1061258;
    String long_name "Hbact";
    String units "cells per milliliter";
  }
  HEUK {
    Int32 actual_range 162, 4875;
    String long_name "Heuk";
    String units "cells per milliliter";
  }
  MEUK {
    Int32 actual_range 133, 3402;
    String long_name "Meuk";
    String units "cells per milliliter";
  }
 }
  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.916288.1";
    Float64 Easternmost_Easting 121.4977;
    Float64 geospatial_lon_max 121.4977;
    Float64 geospatial_lon_min 114.1351;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 120.0;
    Float64 geospatial_vertical_min 5.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-19T00:04:55Z (local files)
2024-11-19T00:04:55Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_916288_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/916288";
    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 is from CTD-based water collections of samples for phytoplankton and non-pigmented bacteria in the Indian Ocean on an R/V Roger Revelle cruise in Feb-March 2022 led by Dr. Michael Landry to investigate the plankton dynamics and impacts on growth and survival of larval Southern Bluefin Tuna (SBT). These flow cytometry results include abundances of phytoplankton taxa (Prochlorococcus, Synechococcus, photosynthetic eukaryotes), non-pigmented bacteria (HBACT), heterotrophic eukaryotes (HEUK), and potential mixotrophic eukaryotes (MEUK). Photosynthetic eukaryote (PEUK) abundance includes the MEUK cells reported (e.g., MEUK are a subset of the PEUK cells with chlorophyll and acidic-vacuoles). Note that MEUK cells likely also include some HEUK with intact chlorophyll-bearing prey, but there is no way to definitively separate these cells from each other.";
    String time_coverage_end "2022-03-02T03:54:00Z";
    String time_coverage_start "2002-02-09T18:57:00Z";
    String title "[BLOOFINZ-IO Flow Cytometry Abundance] - Abundances of phytoplankton and non-pigmented bacteria determined by flow cytometry from water samples collected on R/V Roger Revelle cruise RR2201 in the Eastern Indian Ocean during February and March 2022 (Collaborative Research: Mesoscale variability in nitrogen sources and food-web dynamics supporting larval southern bluefin tuna in the eastern Indian Ocean)";
    Float64 Westernmost_Easting 114.1351;
  }
}

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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