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Dataset Title:  Stable isotope ratio and concentration of carbon in seawater during Plocamium
culture experiments, 2014-2015 (Seaweed OA Resilience project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_731237)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   Maximum ?
 Date (unitless) ?          "2014-09-09"    "2015-02-23"
 Sample (unitless) ?          "3E-1.1"    "8E-9.1"
 d13CVPDB (parts per thousand (ppt)) ?          -25.09    -10.09
 C_Conc_2ml (micrograms/milliliter (ug/mL)) ?          8.0    29.3
 C_Conc_3ml (micrograms/milliliter (ug/mL)) ?          5.3    19.5
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")

File type: (more info)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Date {
    String bcodmo_name "date_local";
    String description "Sample collection date formatted as yyyy-mm-dd";
    String long_name "Date";
    String source_name "Date";
    String time_precision "1970-01-01";
    String units "unitless";
  Sample {
    String bcodmo_name "sample";
    String description "Trial number: experiment end (E)-pot number.replicate";
    String long_name "Sample";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  d13CVPDB {
    Float32 _FillValue NaN;
    Float32 actual_range -25.09, -10.09;
    String bcodmo_name "delta13C";
    String description "Isotopic composition of delta-13C (seawater) relative to Pee Dee Belemnite (PDB)";
    String long_name "D13 CVPDB";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/D13CMITX/";
    String units "parts per thousand (ppt)";
  C_Conc_2ml {
    Float32 _FillValue NaN;
    Float32 actual_range 8.0, 29.3;
    String bcodmo_name "TOC";
    String description "Carbon concentration in a 2 ml sample";
    String long_name "C Conc 2ml";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/";
    String units "micrograms/milliliter (ug/mL)";
  C_Conc_3ml {
    Float32 _FillValue NaN;
    Float32 actual_range 5.3, 19.5;
    String bcodmo_name "TOC";
    String description "Carbon concentration in a 3 ml sample";
    String long_name "C Conc 3ml";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/";
    String units "micrograms/milliliter (ug/mL)";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Samples for delta-13C of dissolved inorganic carbon (DIC) in the seawater were
stored in 20 mL glass vials with cone lids to exclude air from samples.
Samples were stored at room temperature in low light until prepared for
analysis using the exetainer gas evolution technique for DIC (Li et al. 2007).
Then, the samples were sent to the University of California, Davis Stable
Isotope Facility (UCD-SIF) for analysis using the GasBench \\u2013isotope ratio
mass spectrometry technique.";
    String awards_0_award_nid "55177";
    String awards_0_award_number "OCE-1316198";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1316198";
    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 cdm_data_type "Other";
    String comment 
"Stable isotope ratio and concentration of carbon in seawater 
   PI's: J. Kubler, S. Dudgeon (CSU-Northridge) 
   version: 2018-03-19";
    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 "2018-03-20T19:32:08Z";
    String date_modified "2019-06-03T18:00:44Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.731237.1";
    String history 
"2020-12-04T17:18:28Z (local files)
2020-12-04T17:18:28Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_731237.html";
    String infoUrl "https://www.bco-dmo.org/dataset/731237";
    String institution "BCO-DMO";
    String instruments_0_acronym "IR Mass Spec";
    String instruments_0_dataset_instrument_description "Used to measure isotope concentrations of 13C in the seawater samples.";
    String instruments_0_dataset_instrument_nid "731254";
    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 "GasBench";
    String keywords "2ml, 3ml, bco, bco-dmo, biological, C_Conc_2ml, C_Conc_3ml, chemical, conc, cvpdb, d13, d13CVPDB, data, dataset, date, dmo, erddap, management, oceanography, office, preliminary, sample, time";
    String license "https://www.bco-dmo.org/dataset/731237/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/731237";
    String param_mapping "{'731237': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/731237/parameters";
    String people_0_affiliation "California State University Northridge";
    String people_0_affiliation_acronym "CSU-Northridge";
    String people_0_person_name "Dr Janet  E Kubler";
    String people_0_person_nid "51681";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "California State University Northridge";
    String people_1_affiliation_acronym "CSU-Northridge";
    String people_1_person_name "Dr Steve Dudgeon";
    String people_1_person_nid "51682";
    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 "Seaweed OA Resilience";
    String projects_0_acronym "Seaweed OA Resilience";
    String projects_0_description "Benthic macroalgae contribute to intensely productive near shore  ecosystems and little is known about the potential effects of ocean  acidification on non-calcifying macroalgae. Kübler and Dudgeon will test  hypotheses about two macroalgae, Ulva spp. and Plocamium cartilagineum,  which, for different reasons, are hypothesized to be more productive  and undergo ecological expansions under predicted changes in ocean  chemistry. They have designed laboratory culture-based experiments to  quantify the scope for response to ocean acidification in Plocamium,  which relies solely on diffusive uptake of CO2, and populations of Ulva  spp., which have an inducible concentrating mechanism (CCM). The  investigators will culture these algae in media equilibrated at 8  different pCO2 levels ranging from 380 to 940 ppm to address three key  hypotheses. The first is that macroalgae (such as Plocamium  cartilagineum) that are not able to acquire inorganic carbon in changed  form will benefit, in terms of photosynthetic and growth rates, from  ocean acidification. There is little existing data to support this  common assumption. The second hypothesis is that enhanced growth of Ulva  sp. under OA will result from the energetic savings from down  regulating the CCM, rather than from enhanced photosynthesis per se.  Their approach will detect existing genetic variation for adaptive  plasticity. The third key hypothesis to be addressed in short-term  culture experiments is that there will be a significant interaction  between ocean acidification and nitrogen limited growth of Ulva spp.,  which are indicator species of eutrophication. Kübler and Dudgeon will  be able to quantify the individual effects of ocean acidification and  nitrogenous nutrient addition on Ulva spp. and also, the synergistic  effects, which will inevitably apply in many highly productive, shallow  coastal areas. The three hypotheses being addressed have been broadly  identified as urgent needs in our growing understanding of the impacts  of ocean acidification.";
    String projects_0_end_date "2016-05";
    String projects_0_geolocation "Temperate coastal waters of the USA (30 - 45 N latitude, -66 to -88 W and -117 to -125 W longitude)";
    String projects_0_name "Ocean Acidification: Scope for Resilience to Ocean Acidification in Macroalgae";
    String projects_0_project_nid "2275";
    String projects_0_start_date "2013-06";
    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 "Stable isotope ratio and concentration of carbon in seawater during Plocamium culture experiments, 2014-2015.";
    String title "Stable isotope ratio and concentration of carbon in seawater during Plocamium culture experiments, 2014-2015 (Seaweed OA Resilience project)";
    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
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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