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Dataset Title:  Bulk suspended PON d15N from several cruises conducted in the Southern Ocean
south of Africa from 2012-2019
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_805324)
Range: longitude = 3.0E-4 to 41.9621°E, latitude = -56.0768 to -34.4835°N, time = 2012-07-20T18:54:00Z to (now?)
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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 {
  cruise {
    String bcodmo_name "cruise_id";
    String description "Cruise identifier";
    String long_name "Cruise";
    String units "unitless";
  leg {
    Byte _FillValue 127;
    Byte actual_range 1, 3;
    String bcodmo_name "leg";
    String description "Cruise leg";
    String long_name "Leg";
    String units "unitless";
  ship {
    String bcodmo_name "ship";
    String description "Ship name";
    String long_name "Ship";
    String units "unitless";
  date {
    String bcodmo_name "date";
    String description "Date; format: yyyy-mm-dd";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date";
    String time_precision "1970-01-01";
    String units "unitless";
  time2 {
    String bcodmo_name "time";
    String description "Time; format: HH:MM";
    String long_name "Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -56.0768, -34.4835;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude; positive values = North";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range 3.0e-4, 41.9621;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude; positive values = East";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  PONconc_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 0.19, 1.81;
    String bcodmo_name "PON";
    String description "Mean PON concentration. PON is the bulk (> 0.3 µm) particulate organic nitrogen in surface waters filtered from the ship's underway intake) concentration.";
    String long_name "PONconc Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MDMAP013/";
    String units "micrometers (µm)";
  PONconc_sd {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.22;
    String bcodmo_name "PON";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Standard deviation of PONconc_avg";
    String long_name "PONconc Sd";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MDMAP013/";
    String units "micrometers (µm)";
  PONconc_n {
    Byte _FillValue 127;
    Byte actual_range 2, 4;
    String bcodmo_name "num_reps";
    String description "Number of replicate measurements of PON";
    String long_name "PONconc N";
    String units "unitless";
  PONd15N_avg {
    Float32 _FillValue NaN;
    Float32 actual_range -4.81, 7.7;
    String bcodmo_name "d15N";
    String description "Mean PON d15N. d15N is the nitrogen isotopic composition of a sample expressed in delta notation (d15N in units of per mil, ‰) relative to atmospheric N2, where d15N = {[(15N/14N)sample/(15N/14N)atmN2] – 1} × 1000.";
    String long_name "PONd15 N Avg";
    String units "per mil vs AIR";
  PONd15N_sd {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.84;
    String bcodmo_name "d15N";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Standard deviation of PONd15N_avg";
    String long_name "PONd15 N Sd";
    String units "per mil vs AIR";
  PONd15N_n {
    Byte _FillValue 127;
    Byte actual_range 2, 4;
    String bcodmo_name "num_reps";
    String description "Number of replicate measurements of PONd15N";
    String long_name "PONd15 N N";
    String units "unitless";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.34281044e+9, NaN;
    String axis "T";
    String bcodmo_name "date";
    String description "Date and time formatted to the ISO 8601 standard; format: yyyy-mm-ddTHH:MM";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Bulk (>0.3 um) suspended PON samples were collected from the underway intake
(at 7 m depth) and frozen at \\u221280\\u00b0C until isotope analysis. The N
isotope composition of bulk PON was measured by elemental analyser-isotope
ratio mass spectrometry at the University of Cape Town. See methods section of
Smart et al. (2020) for more detail.";
    String awards_0_award_nid "557249";
    String awards_0_award_number "PLR-1401489";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1401489";
    String awards_0_funder_name "NSF Division of Polar Programs";
    String awards_0_funding_acronym "NSF PLR";
    String awards_0_funding_source_nid "490497";
    String awards_0_program_manager "Dr Mark Kurz";
    String awards_0_program_manager_nid "557248";
    String awards_1_award_nid "558188";
    String awards_1_award_number "OCE-1060947";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1060947";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "Henrietta N Edmonds";
    String awards_1_program_manager_nid "51517";
    String awards_2_award_nid "788981";
    String awards_2_award_number "OCE-0922345";
    String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0922345";
    String awards_2_funder_name "NSF Division of Ocean Sciences";
    String awards_2_funding_acronym "NSF OCE";
    String awards_2_funding_source_nid "355";
    String awards_2_program_manager "Kandace  S Binkley";
    String awards_2_program_manager_nid "51512";
    String cdm_data_type "Other";
    String comment 
"Bulk suspended PON d15N from the Southern Ocean 
  PI: Daniel M. Sigman (Princeton) 
  Contact: Sandi Smart (Stellenbosch University & The Max Planck Institute for Chemistry) 
  Version date: 04 March 2020";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2020-03-04T19:46:44Z";
    String date_modified "2020-03-12T18:41:16Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.805324.1";
    Float64 Easternmost_Easting 41.9621;
    Float64 geospatial_lat_max -34.4835;
    Float64 geospatial_lat_min -56.0768;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 41.9621;
    Float64 geospatial_lon_min 3.0e-4;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-07-19T18:34:28Z (local files)
2024-07-19T18:34:28Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_805324.das";
    String infoUrl "https://www.bco-dmo.org/dataset/805324";
    String institution "BCO-DMO";
    String instruments_0_acronym "IR Mass Spec";
    String instruments_0_dataset_instrument_nid "805400";
    String instruments_0_description "The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_0_instrument_name "Isotope-ratio Mass Spectrometer";
    String instruments_0_instrument_nid "469";
    String instruments_0_supplied_name "Thermo Scientific Delta V Plus mass spectrometer";
    String instruments_1_dataset_instrument_nid "805399";
    String instruments_1_description "Instruments that quantify carbon, nitrogen and sometimes other elements by combusting the sample at very high temperature and assaying the resulting gaseous oxides. Usually used for samples including organic material.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB01/";
    String instruments_1_instrument_name "Elemental Analyzer";
    String instruments_1_instrument_nid "546339";
    String instruments_1_supplied_name "Thermo Scientific FLASH 2000 elemental analyzer";
    String keywords "average, bco, bco-dmo, biological, chemical, cruise, data, dataset, date, dmo, erddap, iso, ISO_DateTime_UTC, latitude, leg, longitude, management, oceanography, office, ponconc, PONconc_avg, PONconc_n, PONconc_sd, pond15, PONd15N_avg, PONd15N_n, PONd15N_sd, preliminary, ship, time, time2";
    String license "https://www.bco-dmo.org/dataset/805324/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/805324";
    Float64 Northernmost_Northing -34.4835;
    String param_mapping "{'805324': {'latitude': 'flag - latitude', 'longitude': 'flag - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/805324/parameters";
    String people_0_affiliation "Princeton University";
    String people_0_person_name "Daniel M. Sigman";
    String people_0_person_nid "51417";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Stellenbosch University";
    String people_1_person_name "Sandi M. Smart";
    String people_1_person_nid "557790";
    String people_1_role "Contact";
    String people_1_role_type "related";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Diatom-bound_N_Isotopes,N Isotopes Foraminifera,stable isotope instrumentation";
    String projects_0_acronym "Diatom-bound_N_Isotopes";
    String projects_0_description 
"Description from NSF award abstract:
The high concentration of the major nutrients nitrate and phosphate is a fundamental characteristic of the Antarctic Zone in the Southern Ocean and is central to its role in global ocean fertility and the global carbon cycle. The isotopic composition of diatom-bound organic nitrogen is one of the best hopes for reconstructing the nutrient status of polar surface waters over glacial cycles, which in turn may hold the explanation for the decline in atmospheric carbon dioxide during ice ages. The PIs propose to generate detailed diatom-bound nitrogen isotope (δ15Ndb) records from high sedimentation rate cores from the Kerguelen Plateau. Because the cores were collected at relatively shallow seafloor depths, they have adequate planktonic and benthic foraminifera to develop accurate age models. The resulting data could be compared with climate records from Antarctic ice cores and other archives to investigate climate-related changes, including the major steps into and out of ice ages and the millennial-scale events that occur during ice ages and at their ends. The records generated in this project will provide a critical test of hypotheses for the cause of lower ice age CO2.
This study will contribute to the goal of understanding ice ages and past CO2 changes, which both have broad implications for future climate. Undergraduates will undertake summer internships, with the possibility of extending their work into junior year projects and senior theses. In addition, the PI will lead modules for two Princeton programs for middle school teachers and will host a teacher for a six-week summer research project.";
    String projects_0_end_date "2017-04";
    String projects_0_geolocation "Kerguelen Plateau";
    String projects_0_name "High-resolution, Assemblage-specific Records of Diatom-bound N Isotopes from the Indian Sector of the Antarctic Ocean";
    String projects_0_project_nid "557250";
    String projects_0_start_date "2014-05";
    String projects_1_acronym "N Isotopes Foraminifera";
    String projects_1_description 
"NSF Award Abstract:
Nitrogen (N) and phosphorus are the two nutrients required in large quantity by phytoplankton in the ocean, and together they limit productivity throughout most of the tropical, subtropical, and temperate ocean. Both the cycling of N and its input/output budget have been argued to control the fertility of the ocean and the ocean's role in setting atmospheric CO2. The CaCO3 tests of foraminifera can represent a substantial fraction of marine sediments and have been used extensively in paleoceanography; they are an obvious target for isotopic analysis of microfossil-bound organic matter.
In recent years, researchers at Princeton have developed a protocol for the isotopic analysis of foraminiferal shell-bound N. The current protocol is at least 100 times more sensitive than typical on-line combustion, allowing for rapid progress with a N isotope archive that was previously not feasible to measure. Measurements on surface sediments and a downcore record from the Caribbean show the promise of foraminifera-bound del15N (fb-del15N) to provide both a robust N isotope archive for paleoceanography, and one with a unique potential of richness, given the existence of multiple foraminiferal species with different depth habitats and behaviors. Moreover, the finding from the Caribbean Sea record -- reduced N fixation in ice age Atlantic -- has changed the scientific conversation about the nature of the input/output budget of oceanic fixed N and its potential to change ocean fertility and atmospheric CO2. However, the controls on fb-del15N have not yet been adequately studied.
In this project, as a first major step in developing a foundation for the paleoceanographic application of fb-del15N, the same Princeton University team will study its genesis in the water column, transport to the seafloor, and early diagenesis. They will undertake this study in the Sargasso Sea south of Bermuda. This is one of the best studied regions of the ocean, in general and with respect to foraminifera, and a region that has been has been a focus of the N isotope research of the PI for the last decade and others previously. Moreover, its significant seasonality -- in physical oceanography, biogeochemistry, and foraminiferal species abundance -- will facilitate the effort to understand the controls on fb-del15N at a mechanistic level. The research team will participate in six Bermuda Atlantic Time-series Study (BATS) cruises over two years, collecting foraminifera and other N forms likely to provide insight into the controls on fb-del15N. From the nearby Oceanic Flux Program (OFP) moored sediment traps and from shallow sediments collected in the region, they will pick foraminifera shells and again make relevant ancillary measurements. This work will establish the relationship of foraminiferal biomass to shell-bound del15N for different species, and comparison of the foraminiferal isotope data with the upper ocean N pools will yield empirical isotopic relationships and work toward a mechanistic insight of fb-del15N (e.g., the importance of different N pools to the diets of different foraminifera; the role of algal symbionts). The sediment trap and surface sediment data will support the plankton tow data by integrating over longer time scales and will also address questions regarding late stage (e.g., gametogenic) calcification and the early diagenesis of fb-del15N and fb-N content.
Broader Impacts: This study will yield an improved understanding of the nutrient dynamics of foraminifera, a class of organisms whose shells are a central tool in micropaleontology and paleoclimatology. The project will also build on the principal investigator's involvement in the Bermuda Institute of Ocean Sciences as an asset for integrating ocean-related education and research at both the undergraduate and graduate levels.";
    String projects_1_end_date "2016-03";
    String projects_1_geolocation "Sargasso Sea";
    String projects_1_name "Understanding the nitrogen isotopes of planktonic foraminifera: A modern Sargasso Sea study";
    String projects_1_project_nid "743583";
    String projects_1_start_date "2011-04";
    String projects_2_acronym "stable isotope instrumentation";
    String projects_2_description 
"NSF Award Abstract:
Intellectual Merit:
The PIs are requesting funds to acquire a suite of instruments for stable isotope (N) research, including a denitrifier-based, natural abundance isotope system, a tracer isotope system, and general purpose natural abundance peripherals for an existing mass spectrometer. Specific instruments requested include a Thermo Electron MAT 253 stable isotope mass spectrometer, a Thermo DeltaVAdvantage stable isotope mass spectrometer with peripherals, an EA peripheral for combustion-based isotope analysis, and a GasBench II carbon dioxide preparation and purification system. The proposed instrumentation would enable research efforts examining natural stable isotope abundances that include ocean biogeochemistry and paleoceanography, terrestrial biogeochemistry, carbon isotopes in Precambrian Earth history. Stable isotope tracer research would include nitrification, nitrogen fixation, and carbon partitioning during biostimulation.
Broader Impacts:
The PIs state that the proposed instrumentation would expand the research capabilities of the institution and specifically the Departments of Geosciences and Ecology and Evolutionary Biology. The improvements to the denitrifier method will also serve to expand the capabilities of the ocean research community at large. Additionally, the proposed instrumentation will enable method development and provide training for undergraduate students at the institution and those participating in a collaborative effort with the University of Cape Town.";
    String projects_2_end_date "2012-08";
    String projects_2_name "MRI: Acquisition of Stable Isotope Instrumentation for the Biogeosciences at Princeton University";
    String projects_2_project_nid "788982";
    String projects_2_start_date "2009-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -56.0768;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Compilation of surface measurements of bulk suspended particulate organic nitrogen (PON) collected from the Southern Ocean south of Africa (spanning 0-42\\u00b0E). Date, time, latitude, and longitude are the averages of the start and end values of each underway collection.";
    String time_coverage_start "2012-07-20T18:54:00Z";
    String title "Bulk suspended PON d15N from several cruises conducted in the Southern Ocean south of Africa from 2012-2019";
    String version "1";
    Float64 Westernmost_Easting 3.0e-4;
    String xml_source "osprey2erddap.update_xml() v1.3";


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
For example,
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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