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Dataset Title:  [trial_b] - Trial B test of the dissolution method for estimates of the 15N2
atom% of incubations (EAGER: Collaborative Research: Detection limit in
marine nitrogen fixation measurements - Constraints of rates from the
mesopelagic ocean)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_778158)
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 {
  Sample_ID {
    String bcodmo_name "unknown";
    String description "sample";
    String long_name "Sample ID";
    String units "unitless";
  }
  time2 {
    Float64 _FillValue NaN;
    Float64 actual_range 0.4333564814814815, 0.6306365740740741;
    String bcodmo_name "unknown";
    String description "time";
    String long_name "Time";
    String units "unitless";
  }
  Mass_z_28 {
    Float64 _FillValue NaN;
    Float64 actual_range 1.659318e-6, 8.301695e-6;
    String bcodmo_name "unknown";
    String description "mass-to-charge";
    String long_name "Mass Z 28";
    String units "unitless";
  }
  Mass_z_29 {
    Float64 _FillValue NaN;
    Float64 actual_range 1.604068e-8, 5.335568e-8;
    String bcodmo_name "unknown";
    String description "mass-to-charge";
    String long_name "Mass Z 29";
    String units "unitless";
  }
  Mass_z_30 {
    Float64 _FillValue NaN;
    Float64 actual_range 3.998998e-9, 9.322125e-6;
    String bcodmo_name "unknown";
    String description "mass-to-charge";
    String long_name "Mass Z 30";
    String units "unitless";
  }
  Mass_z_32 {
    Float64 _FillValue NaN;
    Float64 actual_range 9.379484e-7, 4.042403e-6;
    String bcodmo_name "unknown";
    String description "mass-to-charge";
    String long_name "Mass Z 32";
    String units "unitless";
  }
  Mass_z_40 {
    Float32 _FillValue NaN;
    Float32 actual_range 3.616499e-8, 2.20631e-7;
    String bcodmo_name "unknown";
    String description "mass-to-charge";
    String long_name "Mass Z 40";
    String units "unitless";
  }
  O2_Ar {
    Float64 _FillValue NaN;
    Float64 actual_range 9.909134e-4, 9.938847;
    String bcodmo_name "unknown";
    String description "O2 to Ar ratio";
    String long_name "O2 Ar";
    String units "unitless";
  }
  ratio_30_28 {
    Float32 _FillValue NaN;
    Float32 actual_range 4.825058e-4, 5.618047;
    String bcodmo_name "unknown";
    String description "ratio 30/28";
    String long_name "Ratio 30 28";
    String units "unitless";
  }
  atom_pcnt_15N {
    Float64 _FillValue NaN;
    Float64 actual_range 0.37, 84.84;
    String bcodmo_name "unknown";
    String description "15N atom %";
    String long_name "Atom Pcnt 15 N";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Inocula of 15N2-enriched water were prepared according to either of two
protocols outlined by Klawonn et al. (2015).\\u00a0  
 In a first Trial A, respective 1.9 mL of 15N2 gas aliquots (Cambridge
Isotope Laboratories, Lot #I-21065) were injected into crimped-sealed 120 mL
glass serum vials filled with deionized water. To dissolve the 15N2 bubble,
each of the two serum vials was vortexed for 5 minutes. Two subsamples of each
inoculum were dispensed into Exetainers\\u2122 with a peristaltic pump for
analysis on the MIMS. An aliquot of each inoculum (5 % vol/vol) was then
dispensed in replicate 160 mL serum incubation bottles containing air-
equilibrated deionized water (Trials A1-A4), which were then crimped-sealed.
Following homogenization, triplicate subsamples of each incubation were
collected in Exetainers\\u2122 for MIMS analysis. The 15N atom % of the inocula
and of the corresponding incubations were measured by MIMS at the University
of Connecticut (Bay Instruments) and computed as follows:\\u00a0
 
Equation 4:\\u00a0
 
In Trial B, duplicate 6 mL, 12 mL, and 24 mL aliquots of enriched seawater,
prepared as per Wilson et al. (2012; Cambridge Isotope Laboratories 15N2 gas
aliquots, Lot #I-19168A), were added to 100 mL glass serum vials, filled with
air equilibrated seawater, and crimp-sealed with no headspace using Teflon-
lined septa. Triplicate subsamples of this dilution series and the enriched
seawater were analyzed at the University of Hawaii on a MIMS (Bay Instruments;
Eq. 4).  
 \\u00a0
 
In both trials, the concentration of N2 isotopologues (m/z 28, 29, and 30) in
each of the 15N2-enriched inocula was then extrapolated from the ionization
efficiency of N isotopologues in air-equilibrated seawater. We define the
ionization efficiency as the ratio of the isotopologue ion current measured by
MIMS relative to its concentration in air-equilibrated seawater (ASW):\\u00a0  
 \\u00a0
 
Equation S2:\\u00a0
 
 For instance, at a temperature of 25\\u00baC and salinity of 35 psu, the
solubility coefficients of Hamme and Emerson (2004) predict a N2 concentration
of 388.9 \\u03bcmol kg-1. The fraction of 15N in N2 (i.e., 15N/(14N+15N)) for
air-equilibrated seawater is 0.003663 (Mariotti, 1983), such that the expected
fractions of 28N2, 29N2, and 30N2 derived from their binomial probability
distributions are as follows:  
 \\u00a0
 
 
\\u00a0 = 99.2687 % Equation S3a
 
= 0.7299 % Equation S3b
 
= 0.0013 % Equation S3c  
 \\u00a0
 
Accordingly, air-equilibrated concentrations of 28N2, 29N2, and 30N2 at this
temperature and salinity are 386.0, 2.8, and 0.005 \\u03bcmol kg-1,
respectively. The ionization efficiency of the isotopologues is then equal to
the ion current of m/z 28 recorded for ASW divided by the corresponding 28N2
concentration (Eq. S2). We used the ionization efficiency of m/z 28 in ASW to
derive the N2 isotopologue concentrations in the inocula from their respective
MIMS ion currents. We did not derive distinct ionization efficiencies from the
ion current-to-concentration of m/z 29 and 30 in ASW, as these isotopologues
are poorly resolved by the MIMS at natural abundance. Thus, we are assuming
that the ionization efficiency of m/z 29 and 30 isotopologues is roughly
similar to that of m/z 28 (i.e., that ionization isotope effects are
negligible for our purposes). The initial expected AN2 of the
\\u201cincubations\\u201d was then calculated using a linear mixing model with
N2 isotopologue concentrations in ambient and enriched seawater";
    String awards_0_award_nid "772538";
    String awards_0_award_number "OCE-1732246";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1732246";
    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 "Henrietta N Edmonds";
    String awards_0_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
"Trial b test of the dissolution method 
  PI: Julie Granger 
  Version: 2019-09-30";
    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 "2019-09-30T19:25:34Z";
    String date_modified "2019-10-02T18:52:25Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.778158.1";
    String history 
"2024-11-06T01:44:56Z (local files)
2024-11-06T01:44:56Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_778158.das";
    String infoUrl "https://www.bco-dmo.org/dataset/778158";
    String institution "BCO-DMO";
    String instruments_0_acronym "IR Mass Spec";
    String instruments_0_dataset_instrument_description "continuous flow Delta V Isotope Ratio Mass Spectrometer (Smith et al. 2015), and continuous flow-GV Isoprime IRMS (Charoenpong et al., 2014)";
    String instruments_0_dataset_instrument_nid "778166";
    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 "Isotope Ratio Mass Spectrometer";
    String instruments_1_acronym "MIMS";
    String instruments_1_dataset_instrument_description "Membrane Inlet Mass Spectrometer (Bay Instruments)";
    String instruments_1_dataset_instrument_nid "778165";
    String instruments_1_description "Membrane-introduction mass spectrometry (MIMS) is a method of introducing analytes into the mass spectrometer's vacuum chamber via a semipermeable membrane.";
    String instruments_1_instrument_name "Membrane Inlet Mass Spectrometer";
    String instruments_1_instrument_nid "661606";
    String instruments_1_supplied_name "Membrane Inlet Mass Spectrometer";
    String keywords "atom, atom_pcnt_15N, bco, bco-dmo, biological, chemical, data, dataset, dmo, erddap, management, mass, Mass_z_28, Mass_z_29, Mass_z_30, Mass_z_32, Mass_z_40, O2, O2_Ar, oceanography, office, oxygen, pcnt, preliminary, ratio, ratio_30_28, sample, Sample_ID, time, time2";
    String license "https://www.bco-dmo.org/dataset/778158/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/778158";
    String param_mapping "{'778158': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/778158/parameters";
    String people_0_affiliation "University of Connecticut";
    String people_0_affiliation_acronym "UConn";
    String people_0_person_name "Julie Granger";
    String people_0_person_nid "528937";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Massachusetts Dartmouth";
    String people_1_affiliation_acronym "UMass Dartmouth";
    String people_1_person_name "Annie Bourbonnais";
    String people_1_person_nid "778011";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Hawaii";
    String people_2_person_name "Samuel Wilson";
    String people_2_person_nid "51733";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Mathew Biddle";
    String people_3_person_nid "708682";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "EAGER NitFix";
    String projects_0_acronym "EAGER NitFix";
    String projects_0_description 
"NSF Award Abstract:
The availability of nitrogen is required to support the growth and production of organisms living in the surface of our global ocean. This element can be scarce. To alleviate this scarcity, a special class of bacteria and archaea, called nitrogen fixers, can derive the nitrogen needed for growth from nitrogen gas. This project would carefully examine one specific method for measuring nitrogen fixation that has been used recently to suggest the occurrence of small amounts of nitrogen fixation in subsurface ocean waters. If these reports are verified, then a revision of our understanding of the marine nitrogen cycle may be needed. The Ocean Carbon and Biogeochemistry program will be used as a platform to develop community consensus for best practices in nitrogen fixation measurements and detection of diversity, activity, and abundances of the organisms responsible. In addition, a session will be organized in a future national/international conference to communicate with the broader scientific community while developing these best practices.
The goal of this study is to conduct a thorough examination of potential experimental and analytical errors inherent to the 15N2-tracer nitrogen fixation method, in tandem with comprehensive molecular measurements, in mesopelagic ocean waters. Samples will be collected and experimental work conducted on a cruise transect in the North Atlantic Ocean, followed by analytical work in the laboratory. The specific aims of this study are to (1) determine the minimum quantifiable rates of 15N2 fixation based on incubations of mesopelagic waters via characterization of sources of experimental and analytical error, and (2) seek evidence of presence and expression of nitrogen fixation genes via comprehensive molecular approaches on corresponding samples. The range of detectable rates and diazotroph activity from the measurements made in this study will be informative for the understanding of the importance of nitrogen fixation in the oceanic nitrogen budget.";
    String projects_0_end_date "2018-10";
    String projects_0_geolocation "North Atlantic Ocean, Pacific Ocean";
    String projects_0_name "EAGER:  Collaborative Research:  Detection limit in marine nitrogen fixation measurements - Constraints of rates from the mesopelagic ocean";
    String projects_0_project_nid "772534";
    String projects_0_start_date "2017-05";
    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 "The \\u201cdissolution\\u201d method to measure N2 fixation rates with 15N2 gas tracer involves the preparation of 15N2-enriched water that is then added to each incubation bottle. Investigators typically measure the 15N2 atom% of the 15N2-enriched inoculum by MIMS, and extrapolate the 15N2 atom% in the incubations based on the inoculum value. Here, we demonstrate that such extrapolation yields inaccurate estimates of the 15N2 atom% of incubations. The latter should be measured directly.";
    String title "[trial_b] - Trial B test of the dissolution method for estimates of the 15N2 atom% of incubations (EAGER:  Collaborative Research:  Detection limit in marine nitrogen fixation measurements - Constraints of rates from the mesopelagic ocean)";
    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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