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Dataset Title:  [Depth profiles of quantitative PCR of ammonia-oxidizing archaea and bacteria
KM1314] - Depth profiles of quantitative PCR of ammonia-oxidizing archaea and
bacteria from R/V Kilo Moana KM1314 in the North Pacific Ocean (Significance of
nitrification in shaping planktonic biodiversity in the ocean) Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_997806_v1)
Range: longitude = -150.0 to -134.6803°E, latitude = 30.0 to 50.0°N, depth = 0.0 to 300.0m, time = 2013-08-14T13:05:19Z to 2013-08-29T14:50:20Z
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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.376485519e+9, 1.37778782e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Datetime_of_sampling";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 30.0, 50.0;
    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 -150.0, -134.6803;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Station_ID {
    Int32 actual_range 5, 13;
    String long_name "Station_id";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 0, 300;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth_m";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  AOA_amoA_Calculated_Abundance {
    Float32 actual_range 135.06, 237067.6;
    String long_name "Aoa_amoa_calculated_abundance";
    String units "copies per milliliter (copies/mL)";
  }
  stdev_AOA {
    Float32 actual_range 0.57, 109459.7;
    String long_name "Stdev_aoa";
    String units "copies per milliliter (copies/mL)";
  }
  AOB_amoA_Calculated_Abundance {
    Float32 actual_range 268.24, 14856.44;
    String long_name "Aob_amoa_calculated_abundance";
    String units "copies per milliliter (copies/mL)";
  }
  stdev_AOB {
    Float32 actual_range 8.62, 2789.12;
    String long_name "Stdev_aob";
    String units "copies per milliliter (copies/mL)";
  }
 }
  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.997806.1";
    Float64 Easternmost_Easting -134.6803;
    Float64 geospatial_lat_max 50.0;
    Float64 geospatial_lat_min 30.0;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -134.6803;
    Float64 geospatial_lon_min -150.0;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 300.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2026-07-24T07:37:29Z (local files)
2026-07-24T07:37:29Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_997806_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/997806";
    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 50.0;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 30.0;
    String summary "This dataset reports depth-resolved abundances of archaeal and β-proteobacterial ammonia monooxygenase (amoA) genes collected at Stations 5, 8, and 13 in the northeastern Pacific Ocean during the R/V Kilo Moana cruise KM1314 in August 2013. One liter of seawater from each depth was filtered onto 0.22 μm Sterivex filters and stored at −80 °C prior to DNA extraction using a modified manual extraction protocol. Archaeal and bacterial amoA gene abundances were quantified by quantitative PCR using primer sets CrenAmoAQ-F/CrenAmoAModR and AmoA1-F/AmoA2-R on a LightCycler platform. Standard curves, amplification procedures, melting curve analyses, and gel electrophoresis verification followed established protocols. These measurements characterize vertical distributions of ammonia-oxidizing microorganisms in the upper 300 m of the water column and support analyses of nitrification activity and microbial community structure in the oligotrophic North Pacific.";
    String time_coverage_end "2013-08-29T14:50:20Z";
    String time_coverage_start "2013-08-14T13:05:19Z";
    String title "[Depth profiles of quantitative PCR of ammonia-oxidizing archaea and bacteria KM1314] - Depth profiles of quantitative PCR of ammonia-oxidizing archaea and bacteria from R/V Kilo Moana KM1314 in the North Pacific Ocean (Significance of nitrification in shaping planktonic biodiversity in the ocean)";
    Float64 Westernmost_Easting -150.0;
  }
}

 

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.

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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