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Dataset Title:  [B. elegans cold water coral lab culture: particulate data] - Particulate data
collected near Friday Harbor, WA between 2020 and 2021 as part of a study of
cold-water coral Balanophyllia elegans diet and trophic position (Collaborative
Research: Refining the use of scleractinian cold-water coral skeleton-bound
d15N as a proxy for marine N cycling)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_919985_v1)
Range: longitude = -123.014 to -122.937°E, latitude = 48.545 to 48.596°N, depth = 5.0 to 30.0m
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 {
  Sample_ID {
    String long_name "Sample_id";
    String units "unitless";
  }
  Date_Collected {
    String long_name "Date_collected";
    String units "unitless";
  }
  Location_collected {
    String long_name "Location_collected";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 48.545, 48.596;
    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 -123.014, -122.937;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Sample_type {
    String long_name "Sample_type";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 5.0, 30.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Mesh_size {
    String long_name "Mesh_size";
    String units "microns";
  }
  NO3 {
    Float32 actual_range 10.32, 33.5;
    String long_name "No3";
    String units "micromolar (uM)";
  }
  d15N {
    Float32 actual_range 1.6, 11.74;
    String long_name "D15n";
    String units "permil (0/00)";
  }
  d15N_stdev {
    String long_name "D15n_stdev";
    String units "permil (0/00)";
  }
  d13C {
    Float32 actual_range -29.52, -18.45;
    String long_name "D13c";
    String units "permil (0/00)";
  }
  d13C_stdev {
    String long_name "D13c_stdev";
    String units "permil (0/00)";
  }
  d18O {
    Float32 actual_range 1.8, 3.85;
    String long_name "D18o";
    String units "permil (0/00)";
  }
  d18O_stdev {
    String long_name "D18o_stdev";
    String units "permil (0/00)";
  }
  Molar_C_to_N_ratio {
    Float32 actual_range 3.8, 11.9;
    String long_name "Molar_c_to_n_ratio";
    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.919985.1";
    Float64 Easternmost_Easting -122.937;
    Float64 geospatial_lat_max 48.596;
    Float64 geospatial_lat_min 48.545;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -122.937;
    Float64 geospatial_lon_min -123.014;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 30.0;
    Float64 geospatial_vertical_min 5.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-10-14T08:01:25Z (local files)
2024-10-14T08:01:25Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_919985_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/919985";
    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 48.596;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 48.545;
    String summary 
"Particulate data collected near Friday Harbor, WA between 2020 and 2021.These data were collected as part of the following study:

Data collected as part of this study include nitrogen isotope ratio data for coral tissue and skeleton of the scleractinian cold-water coral Balanophyllia elegans collected at Friday Harbor, WA. Data was collected between March 2019 and August 2021. These data include paired measurements of the N isotope ratio (d15N) of coral tissue and skeleton. Tissue was measured using and Elemental Analyzer (EA)-coupled Isotope Ratio Mass Spectrometer (IRMS) and skeleton samples were first dissolved and organic nitrogen was oxidized to nitrate with persulfate before being run on a GC-IRMS with the denitrifier method. These data also include the results of two culture experiments with the same species of corals. The corals in the first culture experiment were fed Artemia diets with different known d15N in order to quantify change in the tissue d15N in response to a change in the food source and to determine the offset in d15N between the coral tissue and its diet. The starvation trial culture experiment was conducted to evaluate the effects of starvation on the d15N of coral tissue. For both experiments coral tissue was analyzed using an EA-IRMS. This data also includes the d15N of the respective Artemia diets. Finally, included in this data is hydrological and particulate matter data collect at the site the corals were collected (near Friday Harbor, WA). This data includes nitrate d15N and d18O, suspended particulate organic matter d15N, net tow material d15N, and data collected from a CTD profiler. This data enhances the understanding of cold-water coral diet and trophic position. This data improves the understanding of the relationship between surface nitrate d15N and the d15N recorded in the coral skeleton which is useful for enhancing the resolution of coral d15N paleoproxies.";
    String title "[B. elegans cold water coral lab culture: particulate data] - Particulate data collected near Friday Harbor, WA between 2020 and 2021 as part of a study of cold-water coral Balanophyllia elegans diet and trophic position (Collaborative Research: Refining the use of scleractinian cold-water coral skeleton-bound d15N as a proxy for marine N cycling)";
    Float64 Westernmost_Easting -123.014;
  }
}

 

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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