BCO-DMO ERDDAP
Accessing BCO-DMO data

Make A Graph

Dataset Title:	[Carbon CSI-AA SBB trap foraminifera] - Compound-specific carbon stable isotopes of amino acids in planktic foraminifera from Santa Barbara Basin sediment traps from 2018 to 2021 (Collaborative Research: Constraining Planktic Foraminiferal Ecology Using Compound Specific Isotope Analysis of Amino Acids)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_986825_v1)
Range:	longitude = -120.0593 to -120.0593°E, latitude = 34.24504 to 34.24504°N
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

To work correctly, this web page requires that JavaScript be enabled in your browser. Please:
1) Enable JavaScript in your browser:
      • Chrome: "Settings : Advanced : Privacy and security : Site Settings : JavaScript"
      • Firefox: (it should be always on!)"
      • Opera: "Settings : Websites : JavaScript"
      • Safari: "Safari : Preferences : Security : Enable JavaScript"
2) Reload this web page.

Graph Type:

X Axis:

Y Axis:

Color:

Constraints	Optional Constraint #1		Optional Constraint #2

Server-side Functions

distinct()

Hover here to see a list of options. Click on an option to select it.

Graph Settings

Marker Type:

Size:

Color:

Color Bar:

Continuity:

Scale:

Minimum:

Maximum:

N Sections:

Draw land mask:

Y Axis Minimum:

Maximum:

(Please be patient. It may take a while to get the data.)

Optional:
Then set the File Type: (File Type information)
and

or view the URL:
(Documentation / Bypass this form

)

Click on the map to specify a new center point.

Zoom:

[The graph you specified. Please be patient.]

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 {
  Sample {
    String long_name "Sample";
    String units "unitless";
  }
  Start_date {
    String long_name "Start_date";
    String units "unitless";
  }
  End_date {
    String long_name "End_date";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 34.24504, 34.24504;
    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 -120.0593, -120.0593;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Ala {
    Float32 actual_range -18.7, -17.5;
    String long_name "Ala";
    String units "permille";
  }
  Gly {
    Float32 actual_range -10.9, -9.0;
    String long_name "Gly";
    String units "permille";
  }
  Thr {
    Float32 actual_range -12.6, -11.7;
    String long_name "Thr";
    String units "permille";
  }
  Ser {
    Float32 actual_range -7.1, -0.5;
    String long_name "Ser";
    String units "permille";
  }
  Val {
    Float32 actual_range -25.1, -21.8;
    String long_name "Val";
    String units "permille";
  }
  Leu {
    Float32 actual_range -27.2, -23.5;
    String long_name "Leu";
    String units "permille";
  }
  Ile {
    Float32 actual_range -20.0, -16.7;
    String long_name "Ile";
    String units "permille";
  }
  Pro {
    Float32 actual_range -18.9, -13.6;
    String long_name "Pro";
    String units "permille";
  }
  Asp {
    Float32 actual_range -15.9, -10.9;
    String long_name "Asp";
    String units "permille";
  }
  Glu {
    Float32 actual_range -15.3, -14.4;
    String long_name "Glu";
    String units "permille";
  }
  Phe {
    Float32 actual_range -28.0, -24.8;
    String long_name "Phe";
    String units "permille";
  }
  Tyr {
    Float32 actual_range -24.9, -21.7;
    String long_name "Tyr";
    String units "permille";
  }
  Lys {
    Float32 actual_range -17.0, -13.3;
    String long_name "Lys";
    String units "permille";
  }
  Ala_sd {
    Float32 actual_range 0.1, 0.7;
    String long_name "Ala_sd";
    String units "permille";
  }
  Gly_sd {
    Float32 actual_range 0.1, 0.3;
    String long_name "Gly_sd";
    String units "permille";
  }
  Thr_sd {
    Float32 actual_range 0.0, 0.3;
    String long_name "Thr_sd";
    String units "permille";
  }
  Ser_sd {
    Float32 actual_range 0.1, 0.3;
    String long_name "Ser_sd";
    String units "permille";
  }
  Val_sd {
    Float32 actual_range 0.2, 0.5;
    String long_name "Val_sd";
    String units "permille";
  }
  Leu_sd {
    Float32 actual_range 0.1, 0.5;
    String long_name "Leu_sd";
    String units "permille";
  }
  Ile_sd {
    Float32 actual_range 0.2, 0.6;
    String long_name "Ile_sd";
    String units "permille";
  }
  Pro_sd {
    Float32 actual_range 0.3, 1.1;
    String long_name "Pro_sd";
    String units "permille";
  }
  Asp_sd {
    Float32 actual_range 0.0, 0.5;
    String long_name "Asp_sd";
    String units "permille";
  }
  Glu_sd {
    Float32 actual_range 0.1, 0.4;
    String long_name "Glu_sd";
    String units "permille";
  }
  Phe_sd {
    Float32 actual_range 0.1, 0.7;
    String long_name "Phe_sd";
    String units "permille";
  }
  Tyr_sd {
    Float32 actual_range 0.2, 1.1;
    String long_name "Tyr_sd";
    String units "permille";
  }
  Lys_sd {
    Float32 actual_range 0.2, 0.7;
    String long_name "Lys_sd";
    String units "permille";
  }
 }
  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.986825.1";
    Float64 Easternmost_Easting -120.0593;
    Float64 geospatial_lat_max 34.24504;
    Float64 geospatial_lat_min 34.24504;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -120.0593;
    Float64 geospatial_lon_min -120.0593;
    String geospatial_lon_units "degrees_east";
    String history 
"2025-12-12T17:21:15Z (local files)
2025-12-12T17:21:15Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_986825_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/986825";
    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 34.24504;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 34.24504;
    String summary "We measured carbon and nitrogen compound-specific stable isotopes of amino acids (CSI-AA) in the shells the three most abundant species of planktic foraminifera from Santa Barbara Basin sediment traps from 2018 to 2021: Globigerina bulloides (d'Orbigny, 1826), Neogloboquadrina incompta (Cifelli, 1961), and Turborotalita quinqueloba (Natland, 1938). Multiple sediment trap collections were combined to constitute representative samples. The N. incompta sample included individuals from sediment trap collections from May 2019 to October 2021 (n=4082). The T. quinqueloba sample included individuals from December 2018 to October 2021 (n=4964). G. bulloides was sufficiently abundant to split into seasonal samples: spring/summer from February 2019 to July 2019 (n=5081) and fall/winter from October to January in years 2018-2019, 2019-2020, 2020-2021 (n=3132). The collection of these data were supported by NSF OCE. This dataset includes only the carbon CSI-AA data. Nitrogen data are available in a related dataset.";
    String title "[Carbon CSI-AA SBB trap foraminifera] - Compound-specific carbon stable isotopes of amino acids in planktic foraminifera from Santa Barbara Basin sediment traps from 2018 to 2021 (Collaborative Research: Constraining Planktic Foraminiferal Ecology Using Compound Specific Isotope Analysis of Amino Acids)";
    Float64 Westernmost_Easting -120.0593;
  }
}

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.

ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact