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Dataset Title:  Reference carbon and nitrogen concentrations, and isotope ratios from alfalfa,
nylon-6, bovine liver, and enriched alanine
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_746325)
Information:  Summary ? | License ? | 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 {
  Reference {
    String bcodmo_name "sample_type";
    String description "type of material used as a reference";
    String long_name "Reference";
    String units "unitless";
  }
  Analysis {
    String bcodmo_name "sample";
    String description "analysis (sample) identifier";
    String long_name "Analysis";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  Weight_ug {
    Int16 _FillValue 32767;
    Int16 actual_range 388, 7019;
    String bcodmo_name "weight";
    String description "sample weight";
    String long_name "Weight Ug";
    String units "micrograms";
  }
  C_Amount_ug {
    Float32 _FillValue NaN;
    Float32 actual_range 148.87, 3027.56;
    String bcodmo_name "C";
    String description "mass of Carbon in the sample";
    String long_name "C Amount Ug";
    String units "micrograms";
  }
  d13C {
    Float32 _FillValue NaN;
    Float32 actual_range -29.92, 43.11;
    String bcodmo_name "d13C";
    String description "the ratio of stable isotopes 13C:12C";
    String long_name "D13 C";
    String units "unitless";
  }
  N_Amount_ug {
    Float32 _FillValue NaN;
    Float32 actual_range 18.47, 330.54;
    String bcodmo_name "N";
    String description "mass of Nitrogen in the sample";
    String long_name "N Amount Ug";
    String units "micrograms";
  }
  d15N {
    Float32 _FillValue NaN;
    Float32 actual_range -11.21, 41.23;
    String bcodmo_name "d15N";
    String description "the ratio of stable isotopes 15N:14N";
    String long_name "D15 N";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description "\"\"";
    String awards_0_award_nid "648650";
    String awards_0_award_number "OCE-1635403";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String awards_1_award_nid "710233";
    String awards_1_award_number "OCE-1633951";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1633951";
    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 "Michael E. Sieracki";
    String awards_1_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"Carbon and nitrogen reference samples 
   PI: R. Zimmerman (ODU) 
   version: 2018-09-11 
    Key: G-5=alfalfa; G-6=nylon-6; G-13=bovine liver; G-21=enriched alanine";
    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 "2018-09-17T19:16:13Z";
    String date_modified "2019-03-20T14:10:00Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.746325.1";
    String history 
"2024-03-28T09:50:50Z (local files)
2024-03-28T09:50:50Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_746325.das";
    String infoUrl "https://www.bco-dmo.org/dataset/746325";
    String institution "BCO-DMO";
    String instruments_0_acronym "IR Mass Spec";
    String instruments_0_dataset_instrument_description "Used for chemical and isotope analyses.";
    String instruments_0_dataset_instrument_nid "746333";
    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 "PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK)";
    String instruments_1_dataset_instrument_description "Used for chemical and isotope analyses.";
    String instruments_1_dataset_instrument_nid "746334";
    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 "PDZ Europa ANCA-GSL elemental analyzer";
    String keywords "amount, analysis, bco, bco-dmo, biological, C_Amount_ug, chemical, d13, d13C, d15, d15N, data, dataset, dmo, erddap, management, N_Amount_ug, oceanography, office, preliminary, reference, weight, Weight_ug";
    String license "https://www.bco-dmo.org/dataset/746325/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/746325";
    String param_mapping "{'746325': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/746325/parameters";
    String people_0_affiliation "Old Dominion University";
    String people_0_affiliation_acronym "ODU";
    String people_0_person_name "Richard C. Zimmerman";
    String people_0_person_nid "51308";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Old Dominion University";
    String people_1_affiliation_acronym "ODU";
    String people_1_person_name "David J Burdige";
    String people_1_person_nid "648653";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Nancy Copley";
    String people_2_person_nid "50396";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Seagrass Blue Carbon";
    String projects_0_acronym "Seagrass Blue Carbon";
    String projects_0_description 
"NSF abstract:
This research will develop a quantitative understanding of the factors controlling carbon cycling in seagrass meadows that will improve our ability to quantify their potential as blue carbon sinks and predict their future response to climate change, including sea level rise, ocean warming and ocean acidification. This project will advance a new generation of bio-optical-geochemical models and tools (ECHOES) that have the potential to be transform our ability to measure and predict carbon dynamics in shallow water systems.
This study will utilize cutting-edge methods for evaluating oxygen and carbon exchange (Eulerian and eddy covariance techniques) combined with biomass, sedimentary, and water column measurements to develop and test numerical models that can be scaled up to quantify the dynamics of carbon cycling and sequestration in seagrass meadows in temperate and tropical environments of the West Atlantic continental margin that encompass both siliciclastic and carbonate sediments. The comparative analysis across latitudinal and geochemical gradients will address the relative contributions of different species and geochemical processes to better constrain the role of seagrass carbon sequestration to global biogeochemical cycles. Specifically the research will quantify: (i) the relationship between C stocks and standing biomass for different species with different life histories and structural complexity, (ii) the influence of above- and below-ground metabolism on carbon exchange, and (iii) the influence of sediment type (siliciclastic vs. carbonate) on Blue Carbon storage. Seagrass biomass, growth rates, carbon content and isotope composition (above- and below-ground), organic carbon deposition and export will be measured. Sedimentation rates and isotopic composition of PIC, POC, and iron sulfide precipitates, as well as porewater concentrations of dissolved sulfide, CO2, alkalinity and salinity will be determined in order to develop a bio-optical-geochemical model that will predict the impact of seagrass metabolism on sediment geochemical processes that control carbon cycling in shallow waters. Model predictions will be validated against direct measurements of DIC and O2 exchange in seagrass meadows, enabling us to scale-up the density-dependent processes to predict the impacts of seagrass distribution and density on carbon cycling and sequestration across the submarine landscape.
Status, as of 09 June 2016: This project has been recommended for funding by NSF's Division of Ocean Sciences.";
    String projects_0_end_date "2019-07";
    String projects_0_geolocation "Chesapeake Bay, Northern Gulf of Mexico, and Bahamas Banks";
    String projects_0_name "Toward an Improved Understanding of Blue Carbon: The Role of Seagrasses in Sequestering CO2";
    String projects_0_project_nid "648649";
    String projects_0_start_date "2016-08";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "This dataset includes results of carbon and nitrogen analyses on reference materials including alfalfa, nylon-6, bovine liver, and enriched alanine. The reference materials were analyzed for Carbon, Nitrogen, delta-13C, and delta-15N by the Stable Isotope Facility, U.C. Davis using a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK).";
    String title "Reference carbon and nitrogen concentrations, and isotope ratios from alfalfa, nylon-6, bovine liver, and enriched alanine";
    String version "1";
    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
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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