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| Dataset Title: | [DON concentration and DON d15N] - Measurements of dissolved organic nitrogen concentration and d15N from R/V Atlantis and R/V Melville cruises in the Eastern Tropical South Pacific from 2010 to 2011. (Collaborative Research: Documenting N2 fixation in N deficient waters of the Eastern Tropical South Pacific) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_729480) |
| Information: | Summary
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| ISO 19115
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Attributes {
s {
deployment {
String bcodmo_name "deployno";
String description "Deployment name";
String long_name "Deployment";
String units "unitless";
}
cruise_year {
Int16 _FillValue 32767;
Int16 actual_range 2010, 2011;
String bcodmo_name "year";
String description "Year of cruise; yyyy";
String long_name "Cruise Year";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
String units "unitless";
}
date {
String bcodmo_name "date";
String description "Date of sampling; 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";
}
station {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 13;
String bcodmo_name "station";
String description "Station where sampling occurred";
String long_name "Station";
String units "unitless";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range -20.0, -10.0;
String axis "Y";
String bcodmo_name "latitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "Latitude";
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 -100.0, -80.0;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "Longitude";
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";
}
depth {
String _CoordinateAxisType "Height";
String _CoordinateZisPositive "down";
Float64 _FillValue NaN;
Float64 actual_range 0.0, 200.0;
String axis "Z";
String bcodmo_name "depth";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "Depth of sampling";
String ioos_category "Location";
String long_name "Depth";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
String positive "down";
String standard_name "depth";
String units "m";
}
NO3_NO2 {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 3.85;
String bcodmo_name "NO3_NO2";
Float64 colorBarMaximum 50.0;
Float64 colorBarMinimum 0.0;
String description "NO3- + NO2- values";
String long_name "Mole Concentration Of Nitrate In Sea Water";
String units "uM";
}
NO3_NO2_d15N {
Float32 _FillValue NaN;
Float32 actual_range 8.9, 22.9;
String bcodmo_name "dN15_NO3";
Float64 colorBarMaximum 50.0;
Float64 colorBarMinimum 0.0;
String description "No3- + NO2- d15N values";
String long_name "Mole Concentration Of Nitrate In Sea Water";
String units "ppm vs air";
}
DON {
Float32 _FillValue NaN;
Float32 actual_range 3.7, 6.4;
String bcodmo_name "Dissolved Organic Nitrogen";
String description "Dissolved organic nitrogen";
String long_name "DON";
String units "uM";
}
DON_stdev {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 1.4;
String bcodmo_name "Dissolved Organic Nitrogen";
String description "Standard deviation of dissolved organic nitrogen";
String long_name "DON Stdev";
String units "uM";
}
DON_d15N {
Float32 _FillValue NaN;
Float32 actual_range 2.7, 6.5;
String bcodmo_name "d15N";
String description "Dissolved organic nitrogen d15N";
String long_name "DON D15 N";
String units "ppm vs air";
}
DON_d15N_stdev {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 2.0;
String bcodmo_name "d15N";
String description "Standard deviation of dissolved organic nitrogen d15N";
String long_name "DON D15 N Stdev";
String units "ppm vs air";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
String acquisition_description
"NO3- + NO2- concentration and isotopic composition analysis
The NO3- + NO2- concentration of samples was determined using chemiluminescent
analysis (Braman & Hendrix, 1989) in a configuration with a detection limit of
0.05 uM, and +/- 0.1 uM for 1 standard deviation (S.D.). The d15N of NO3- +
NO2- was determined using the \\u201cdenitrifier\\u201d method (K. L. Casciotti,
Sigman, Hastings, Bohlke, & Hilkert, 2002; Sigman et al., 2001) with
modifications (McIlvin & Casciotti, 2011) on samples with NO3- + NO2-
concentration >0.3 uM (typically <0.2\\u2030 1 S.D.) (Supp. Table 1) (Knapp,
Casciotti, Berelson, Prokopenko, & Capone, 2016).
DON concentration and isotopic analysis
The DON concentration of samples was determined using persulfate oxidation to
convert DON to NO3- (Solorzano & Sharp, 1980), adapted according to (Knapp et
al., 2005). The resulting NO3- concentration was then measured using
chemiluminescence as described above. In cases where NO3- + NO2- (and/or
ammonium, NH4+) was above the detection limit, DON was determined by
subtracting the concentration of NO3- + NO2-+NH4+ from the concentration of
total dissolved N (TDN). The average standard deviation for duplicate DON
concentration analyses of individual samples that have undetectable levels of
NO3- in the sample was +/- 0.30 uM, and the propagated error for DON
concentration in the presence of detectable NO3- was +/- 0.32 uM.
The d15N of DON was determined according to (Knapp et al., 2005), where DON
samples were oxidized to NO3- by persulfate oxidation (as described above in
section 2.2), acidified to a pH range of 3 to 4, and measured as NO3- by the
denitrifier method. In samples with measurable NO3- + NO2-, the d15N of DON is
calculated by mass balance by subtracting the NO3- + NO2- concentration and
d15N of NO3- + NO2- from the TDN concentration and TDN d15N measurements. In
surface samples with undetectable NO3- + NO2- concentration, the standard
deviation of duplicate analyses of DON d15N in a sample is +/- 0.3\\u2030. For
subsurface samples with NO3- + NO2- concentration approximately equal to the
DON concentration, the propagated error for the calculation of DON d15N using
a Monte Carlo method (Press, Teukolsky, Vetterling, & Flannery, 1992), and
assuming duplicate analysis of a single sample and the standard deviations for
TN concentration, NO3- + NO2- concentration and d15N of NO3- + NO2- given
above, is +/- 0.6 0/00. The 15N of DON in samples with NO3- + NO2-
concentration exceeding DON concentration, and/or with NH4+ concentration >
0.2 uM, was not determined (i.e., Stations 9, 10, 11, and 12 from the 2010
cruise).
Sampling
Samples were collected on the R/V Atlantis in January through February 2010,
and the R/V Melville in March through April 2011 between 10 and 20 \\u00baS and
80\\u00ba W and 100\\u00ba W (Fig. 1), with station locations and sample depths,
salinities, sigma theta values, chlorophyll a concentrations, nitrate+nitrite
concentration, NO3-+ NO2- d15N, DON concentrations, and DON d15N reported in
Supplementary Information Table 1. Water column samples were collected by
Niskin bottles deployed on a rosette equipped with conductivity-temperature-
depth (CTD) sensors. All samples were collected into acid-washed, sample-
rinsed HDPE bottles, and samples from the upper 400 m passed a 0.2 um filter
before collection, and were stored at -20\\u00ba C until analysis on land.";
String awards_0_award_nid "55039";
String awards_0_award_number "OCE-0850801";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0850801";
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 "Donald L. Rice";
String awards_0_program_manager_nid "51467";
String awards_1_award_nid "55105";
String awards_1_award_number "OCE-0850905";
String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0850905";
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 "Donald L. Rice";
String awards_1_program_manager_nid "51467";
String awards_2_award_nid "555505";
String awards_2_award_number "OCE-0961207";
String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0961207";
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 "Donald L. Rice";
String awards_2_program_manager_nid "51467";
String awards_3_award_nid "555515";
String awards_3_award_number "OCE-0961098";
String awards_3_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0961098";
String awards_3_funder_name "NSF Division of Ocean Sciences";
String awards_3_funding_acronym "NSF OCE";
String awards_3_funding_source_nid "355";
String awards_3_program_manager "Donald L. Rice";
String awards_3_program_manager_nid "51467";
String cdm_data_type "Other";
String comment
"DON concentration and d15N
A. Knapp, M. Prokopenko and K. Casciotti, PIs
Version 15 March 2018";
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 "2018-03-06T21:52:05Z";
String date_modified "2019-03-19T18:29:08Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.729480.1";
Float64 Easternmost_Easting -80.0;
Float64 geospatial_lat_max -10.0;
Float64 geospatial_lat_min -20.0;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -80.0;
Float64 geospatial_lon_min -100.0;
String geospatial_lon_units "degrees_east";
Float64 geospatial_vertical_max 200.0;
Float64 geospatial_vertical_min 0.0;
String geospatial_vertical_positive "down";
String geospatial_vertical_units "m";
String history
"2024-11-21T08:46:31Z (local files)
2024-11-21T08:46:31Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_729480.html";
String infoUrl "https://www.bco-dmo.org/dataset/729480";
String institution "BCO-DMO";
String instruments_0_acronym "Niskin bottle";
String instruments_0_dataset_instrument_description "Used to collect water samples";
String instruments_0_dataset_instrument_nid "729500";
String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24 or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
String instruments_0_instrument_name "Niskin bottle";
String instruments_0_instrument_nid "413";
String instruments_0_supplied_name "Niskin";
String instruments_1_acronym "CTD";
String instruments_1_dataset_instrument_nid "729495";
String instruments_1_description "The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column. The instrument is lowered via cable through the water column and permits scientists observe the physical properties in real time via a conducting cable connecting the CTD to a deck unit and computer on the ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or radiometers. It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast. This instrument designation is used when specific make and model are not known.";
String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
String instruments_1_instrument_name "CTD profiler";
String instruments_1_instrument_nid "417";
String instruments_1_supplied_name "CTD";
String instruments_2_acronym "IR Mass Spec";
String instruments_2_dataset_instrument_description "Used to collect NO3- + NO2- d15N and DON d15N data";
String instruments_2_dataset_instrument_nid "729503";
String instruments_2_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_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
String instruments_2_instrument_name "Isotope-ratio Mass Spectrometer";
String instruments_2_instrument_nid "469";
String instruments_2_supplied_name "Thermo Delta V Plus isotope ratio mass spectrometer";
String instruments_3_acronym "Gas Analyzer";
String instruments_3_dataset_instrument_description "Used to collect the NO3- + NO2- concentration and DON concentration data";
String instruments_3_dataset_instrument_nid "729501";
String instruments_3_description "Gas Analyzers - Instruments for determining the qualitative and quantitative composition of gas mixtures.";
String instruments_3_instrument_name "Gas Analyzer";
String instruments_3_instrument_nid "720";
String instruments_3_supplied_name "Sievers 280i Nitric Oxide Analyzer";
String instruments_4_acronym "Gas Analyzer";
String instruments_4_dataset_instrument_description "Used to collect the NO3- + NO2- concentration and DON concentration data";
String instruments_4_dataset_instrument_nid "729502";
String instruments_4_description "Gas Analyzers - Instruments for determining the qualitative and quantitative composition of gas mixtures.";
String instruments_4_instrument_name "Gas Analyzer";
String instruments_4_instrument_nid "720";
String instruments_4_supplied_name "Teledyne API Model 200EU Chemiluminescence NO/NOx/NOX analyzer";
String keywords "bco, bco-dmo, biological, chemical, chemistry, concentration, cruise, cruise_year, d15, data, dataset, date, deployment, depth, deviation, dmo, don, DON_d15N, DON_d15N_stdev, DON_stdev, earth, Earth Science > Oceans > Ocean Chemistry > Nitrate, erddap, latitude, longitude, management, mole, mole_concentration_of_nitrate_in_sea_water, n02, nitrate, no3, NO3_NO2, NO3_NO2_d15N, ocean, oceanography, oceans, office, preliminary, science, sea, seawater, standard, standard deviation, station, stdev, time, water, year";
String keywords_vocabulary "GCMD Science Keywords";
String license "https://www.bco-dmo.org/dataset/729480/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/729480";
Float64 Northernmost_Northing -10.0;
String param_mapping "{'729480': {'lat': 'master - latitude', 'depth': 'master - depth', 'lon': 'master - longitude'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/729480/parameters";
String people_0_affiliation "Florida State University";
String people_0_affiliation_acronym "FSU - EOAS";
String people_0_person_name "Angela N. Knapp";
String people_0_person_nid "555499";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Stanford University";
String people_1_person_name "Karen L. Casciotti";
String people_1_person_nid "50980";
String people_1_role "Co-Principal Investigator";
String people_1_role_type "originator";
String people_2_affiliation "Pomona College";
String people_2_affiliation_acronym "Pomona";
String people_2_person_name "Maria Prokopenko";
String people_2_person_nid "675316";
String people_2_role "Co-Principal Investigator";
String people_2_role_type "originator";
String people_3_affiliation "Florida State University";
String people_3_affiliation_acronym "FSU - EOAS";
String people_3_person_name "Angela N. Knapp";
String people_3_person_nid "555499";
String people_3_role "Contact";
String people_3_role_type "related";
String people_4_affiliation "Woods Hole Oceanographic Institution";
String people_4_affiliation_acronym "WHOI BCO-DMO";
String people_4_person_name "Hannah Ake";
String people_4_person_nid "650173";
String people_4_role "BCO-DMO Data Manager";
String people_4_role_type "related";
String project "N2 fixation ETSP,Microbial Nitrification";
String projects_0_acronym "N2 fixation ETSP";
String projects_0_description
"Description from NSF award abstract:
Several independent lines of geochemical and remote sensing evidence suggest that dinitrogen (N2) fixation may be associated with surface waters downstream of major oxygen minimum zones (OMZs) and in particular in the Eastern Tropical South Pacific (ETSP). However, little direct evidence supports these inferences. Besides substantiating these indirect assessments, documenting significant N2 fixation in the ETSP would provide insight into two longstanding controversies: Is the marine N budget balanced, as implied by modeling and paleoceanographic data, and if so, how are the processes that add and remove N spatially, and thus temporally coupled?
In this project researchers at the University of Southern California and the University of Miami will test the hypothesis that fixation occurs in the ETSP at areal rates that equal or exceed those previously documented in more well-studied regions such as the oligotrophic waters of the sub/tropical North Atlantic. If scaled to the surface area of ETSP waters, this could add an additional 10-50 Tg N per year of inputs to the global marine N budget. They will undertake two cruises in the ETSP during early and late summer in two consecutive years to assess the quantitative significance of N2 fixation as a source of new N to surface waters using complementary biological and geochemical tools. N2 fixation rates will be evaluated on two temporal/spatial scales: daily/local (bottle 15N2 incubations and floating sediment traps); and seasonal/regional (d15N budget using moored sediment traps and water column TDN d15N). These estimates provide detailed observations of potential N2 fixation during station occupation in two summer seasons, when rates are expected to be greatest, as well as prolonged observation over lower expected N2 fixation periods. A combination of these different estimates will aim to determine if N2 fixation in this region can help balance the marine N budget. If all goes as planned, this study will determine the quantitative importance of N2 fixation in the ETSP, and whether these previously undocumented rates can help resolve the marine N budget. Implications include the ability of the marine N cycle to maintain homeostasis, and thus the global C cycle on glacial/interglacial time scales.";
String projects_0_end_date "2012-07";
String projects_0_geolocation "Eastern Tropical South Pacific";
String projects_0_name "Collaborative Research: Documenting N2 fixation in N deficient waters of the Eastern Tropical South Pacific";
String projects_0_project_nid "555496";
String projects_0_start_date "2009-08";
String projects_1_acronym "Microbial Nitrification";
String projects_1_description
"Description from NSF award abstract:
Closing the marine budgets of nitrate and nitrous oxide are central goals for researchers interested in nutrient-driven changes in primary productivity and climate change. With the implementation of new methods for oxygen isotopic analysis of seawater nitrate, it will be possible to construct a budget for nitrate based on its oxygen isotopic distribution that is complementary to nitrogen isotope budgets. Before we can effectively use oxygen isotopes in nitrate to inform the current understanding of the marine nitrogen cycle, we must first understand how different processes that produce (nitrification) and consume (assimilation, denitrification) nitrate affect its oxygen isotopic signature.
In this study, researchers at the Woods Hole Oceanographic Institution will provide a quantitative assessment of the oxygen isotopic systematics of nitrification in the field and thus fill a key gap in our understanding of 18O variations in nitrate, nitrite, and nitrous oxide. The primary goal is to develop a quantitative prediction of the oxygen isotopic signatures of nitrite and nitrate produced during nitrification in the sea. The researchers hypothesize that oxygen isotopic fractionation during nitrification is the primary factor setting the 18O values of newly produced nitrate and nitrite. Secondly, they hypothesize that oxygen atom exchange is low where ammonia oxidation and nitrite oxidation are tightly coupled, but may increase in regions with nitrite accumulation, such as in the primary and secondary nitrite maxima. They will test these hypotheses with a series of targeted laboratory and field experiments, as well as with measurements of nitrite and nitrate isotopic distributions extending through the euphotic zone, primary nitrite maximum, and secondary nitrite maximum of the Eastern Tropical South Pacific. The results of these experiments are expected to provide fundamental information required for the interpretation of 18O isotopic signatures in nitrite, nitrate, and N2O in the context of underlying microbial processes. A better understanding of these features and the processes involved is important for quantifying new production, controls on the N budget, and N2O production in the ocean -- which should lead to a better understanding of the direct and indirect interactions among the nitrogen cycle, marine chemistry, and climate.";
String projects_1_end_date "2011-07";
String projects_1_geolocation "Eastern Tropical South Pacific";
String projects_1_name "Expression of Microbial Nitrification in the Stable Isotopic Systematics of Oceanic Nitrite and Nitrate";
String projects_1_project_nid "555516";
String projects_1_start_date "2010-04";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing -20.0;
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Measurements of dissolved organic nitrogen concentration and d15N from R/V Atlantis and R/V Melville cruises in the Eastern Tropical South Pacific from 2010 to 2011.";
String title "[DON concentration and DON d15N] - Measurements of dissolved organic nitrogen concentration and d15N from R/V Atlantis and R/V Melville cruises in the Eastern Tropical South Pacific from 2010 to 2011. (Collaborative Research: Documenting N2 fixation in N deficient waters of the Eastern Tropical South Pacific)";
String version "1";
Float64 Westernmost_Easting -100.0;
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
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.