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Dataset Title:  32Si and 14C production data (experimental) from EXPORTS cruise RR1813 on R/V
Roger Revelle in the Subarctic North Pacific near Station PAPA from August to
September 2018
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_786013)
Range: longitude = -145.1413 to -144.691°E, latitude = 50.1496 to 50.5828°N, depth = 8.0 to 34.0m, time = 2018-08-16T14:00:13Z to 2018-09-07T12:56:55Z
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Cruise {
    String bcodmo_name "cruise_id";
    String description "cruise during which sample was collected";
    String long_name "Cruise";
    String units "unitless";
  }
  Date_Zulu {
    String bcodmo_name "date_utc";
    String description "UTC date; format: yyyy-mm-dd";
    String long_name "Date Zulu";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  Time_Zulu {
    String bcodmo_name "time_utc";
    String description "UTC time; format: HH:MM:SS";
    String long_name "Time Zulu";
    String units "unitless";
  }
  Event_num {
    String bcodmo_name "event";
    String description "event number from R2R event log";
    String long_name "Event Num";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/EVTAGFL/";
    String units "unitless";
  }
  Activity {
    String bcodmo_name "instrument";
    String description "which instrument was used for sample collection";
    String long_name "Activity";
    String units "unitless";
  }
  Station {
    String bcodmo_name "station";
    String description "station identifier";
    String long_name "Station";
    String units "unitless";
  }
  Cast {
    String bcodmo_name "cast";
    String description "cast type (CTD or experiment) and number";
    String long_name "Cast";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 50.1496, 50.5828;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude in decimal degrees";
    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 -145.1413, -144.691;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude in decimal degrees";
    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";
  }
  Rosette_Bottle {
    Byte _FillValue 127;
    Byte actual_range 4, 12;
    String bcodmo_name "bottle";
    String description "rosette bottle number";
    String long_name "Rosette Bottle";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 8.0, 34.0;
    String axis "Z";
    String bcodmo_name "depth";
    String description "target depth for sample collection";
    String ioos_category "Location";
    String long_name "Target Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  pcnt_lo {
    Byte _FillValue 127;
    Byte actual_range 10, 40;
    String bcodmo_name "PAR";
    String description "percent light level (PAR sensor)";
    String long_name "Pcnt Lo";
    String units "unitless (percent)";
  }
  TRMT {
    String bcodmo_name "treatment";
    String description "experimental sample treatment defined as follows: CTRL = no nutrient additions; +Si = addition of 320 uL of 20 mM Na2SiO3 to increase ambient dissolved silicon by 20uM (measured total Fe in 20nM Si stock indicates that increasing dissolved Si by 20uM increases total dissolved Fe by 0.05nM); +Fe = addition of 32uL of 10uM FeCl3 for a total concentration of 1nM; +Si+Fe = addition of both above.";
    String long_name "TRMT";
    String units "unitless";
  }
  PO4 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.62, 0.94;
    String bcodmo_name "PO4";
    String description "Macronutrients (PO4) - dissolved phosphate concentration in micromoles - analyzed in UCSB MSI Analytical lab";
    String long_name "Mass Concentration Of Phosphate In Sea Water";
    String units "mmol m-3";
  }
  PO4_flag {
    Byte _FillValue 127;
    Byte actual_range 1, 1;
    String bcodmo_name "q_flag";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission";
    String long_name "PO4 Flag";
    String units "unitless";
  }
  SiO4 {
    Float32 _FillValue NaN;
    Float32 actual_range 8.43, 18.38;
    String bcodmo_name "SiOH_4";
    String description "Macronutrients (SiO4) - silicic acid concentration in micromoles (also known as dissolved silicon concentration or dSi)";
    String long_name "Si O4";
    String units "mmol m-3";
  }
  SiO4_flag {
    Byte _FillValue 127;
    Byte actual_range 1, 1;
    String bcodmo_name "q_flag";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission";
    String long_name "Si O4 Flag";
    String units "unitless";
  }
  NO2 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.22;
    String bcodmo_name "NO2";
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String description "Macronutrients (NO2) - dissolved nitrite concentration in micromoles - analyzed in UCSB MSI Analytical lab";
    String long_name "Mole Concentration Of Nitrite In Sea Water";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/NTRIAAZX/";
    String units "mmol m-3";
  }
  NO2_flag {
    Byte _FillValue 127;
    Byte actual_range 1, 3;
    String bcodmo_name "q_flag";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission";
    String long_name "NO2 Flag";
    String units "unitless";
  }
  NO2_NO3 {
    Float32 _FillValue NaN;
    Float32 actual_range 5.85, 9.61;
    String bcodmo_name "NO3_NO2";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "dissolved nitrate+nitrite concentration in micromoles - analyzed in UCSB MSI Analytical lab";
    String long_name "Mole Concentration Of Nitrate In Sea Water";
    String units "mmol m-3";
  }
  NO2_NO3_flag {
    Byte _FillValue 127;
    Byte actual_range 1, 1;
    String bcodmo_name "q_flag";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission";
    String long_name "NO2 NO3 Flag";
    String units "unitless";
  }
  POC {
    Float32 _FillValue NaN;
    Float32 actual_range 40.84, 78.48;
    String bcodmo_name "POC";
    String description "Macronutrients (POC) - particulate organic carbon in micromoles - analyzed in UCSB MSI Analytical lab";
    String long_name "Particulate Organic Carbon";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "mg m-3";
  }
  POC_flag {
    Byte _FillValue 127;
    Byte actual_range 1, 1;
    String bcodmo_name "q_flag";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission";
    String long_name "POC Flag";
    String units "unitless";
  }
  PON {
    Float32 _FillValue NaN;
    Float32 actual_range 5.42, 16.53;
    String bcodmo_name "PON";
    String description "Macronutrients (PON) - particulate organic nitrogen in micromoles - analyzed in UCSB MSI Analytical lab";
    String long_name "PON";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MDMAP013/";
    String units "mg m-3";
  }
  PON_flag {
    Byte _FillValue 127;
    Byte actual_range 1, 1;
    String bcodmo_name "q_flag";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "data flag set as 1 (good) 2 (manual badflag) 3 (below detection limit) 9 (missing) as per Norm Nelson and his Seabass submission";
    String long_name "PON Flag";
    String units "unitless";
  }
  BSi_0_6umfilt_5umprefilt {
    Float32 _FillValue NaN;
    Float32 actual_range 9.13, 126.73;
    String bcodmo_name "Si_bio";
    String description "particulate biogenic silica in nanomoles Si per litre - 0.6-5um fraction";
    String long_name "BSi 0 6umfilt 5umprefilt";
    String units "umol m-3";
  }
  BSi_5umfilt {
    Float32 _FillValue NaN;
    Float32 actual_range 6.72, 157.13;
    String bcodmo_name "Si_bio";
    String description "particulate biogenic silica in nanomoles Si per litre - >5um fraction";
    String long_name "BSi 5umfilt";
    String units "umol m-3";
  }
  rate_32Si_uptake_24hr_0_6umfilt_5umprefilt {
    Float32 _FillValue NaN;
    Float32 actual_range 0.29, 26.74;
    String bcodmo_name "Si_acid";
    String description "size fractionated silicic acid 32Si uptake 0.6-5um fraction";
    String long_name "Rate 32 Si Uptake 24hr 0 6umfilt 5umprefilt";
    String units "nmol Si L-1 d-1";
  }
  rate_32Si_uptake_specific_24hr_0_6umfilt_5umprefilt {
    Float32 _FillValue NaN;
    Float32 actual_range 0.008, 0.756;
    String bcodmo_name "Si_acid";
    String description "size fractionated specific silicic acid 32Si uptake 0.6-5um fraction";
    String long_name "Rate 32 Si Uptake Specific 24hr 0 6umfilt 5umprefilt";
    String units "d-1";
  }
  rate_32Si_uptake_24hr_5umfilt {
    Float32 _FillValue NaN;
    Float32 actual_range 0.49, 23.83;
    String bcodmo_name "Si_acid";
    String description "size fractionated silicic acid 32Si uptake >5um fraction";
    String long_name "Rate 32 Si Uptake 24hr 5umfilt";
    String units "nmol Si L-1 d-1";
  }
  rate_32Si_uptake_specific_24hr_5umfilt {
    Float32 _FillValue NaN;
    Float32 actual_range 0.004, 1.355;
    String bcodmo_name "Si_acid";
    String description "size fractionated specific silicic acid 32Si uptake >5um fraction";
    String long_name "Rate 32 Si Uptake Specific 24hr 5umfilt";
    String units "d-1";
  }
  rate_14C_uptake_24hr_0_6umfilt_5umprefilt {
    Float32 _FillValue NaN;
    Float32 actual_range 0.009, 0.42;
    String bcodmo_name "Primary Production";
    String description "size fractionated primary production 14C uptake 0.6-5um fraction";
    String long_name "Rate 14 C Uptake 24hr 0 6umfilt 5umprefilt";
    String units "umol C L-1 d-1";
  }
  rate_14C_uptake_24hr_5umfilt {
    Float32 _FillValue NaN;
    Float32 actual_range 0.012, 0.323;
    String bcodmo_name "Primary Production";
    String description "size fractionated primary production 14C uptake >5um fraction";
    String long_name "Rate 14 C Uptake 24hr 5umfilt";
    String units "umol C L-1 d-1";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.534428013e+9, 1.536325015e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date and time foramtted to ISO8601 standard; format: yyyy-mm-ddTHH:MM:SS";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String source_name "ISO_DateTime_UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Seawater samples were collected using an epoxy coated CTD-rosette mounted with
Go-Flo samplers and a Sea-Bird Electronics CTD (SBE9plus). Go-Flo bottles were
transferred to a trace metal clean van for subsampling into polypropylene
tubes (nutrients), polypropylene bottle (biogenic silica and particulate
carbon and nitrogen) or TM acid-cleaned polycarbonate incubation bottles
(Si-32 & C-14 incubation experiments).
 
Nutrient samples were filtered through 0.2 \\u03bcm polycarbonate filters and
frozen at -20\\u00b0C. Samples for biogenic silica concentrations were size
fractionated by serial filtration through 5 \\u03bcm and 0.6 \\u03bcm
polycarbonate filters. Filters were stored frozen at -20\\u00b0C. Particulate
organic carbon and nitrogen were measured on samples from experiments
examining the effect of added Fe and Si on carbon fixation. These samples were
filtered through precombusted GFF filters placed in glass scintillation vials
and frozen at -20\\u00b0C.
 
Samples for silicic acid uptake profiles were spiked with the radioisotope
Si-32. Nutrient limitation assays were performed on pairs of samples where
rate of silicic acid uptake (Si-32) or carbon fixation (C-14 in paired
light/dark bottles) were determined in unaltered controlled samples and in
samples augmented with either silicic acid (20 \\u03bcM) or iron chloride (1
nM). All samples were incubated on deck in simulated in situ incubators cooled
with flowing surface seawater from 24 h. Profiles samples six depths from near
surface to the 1% light level. Nutrient limitation assays were performed at
the 40% and 10% light levels.
 
Particles from incubated samples were size fractionated by serial filtration
through 5 \\u03bcm and 0.6 \\u03bcm 25 mm polycarbonate filters. For C-14
incubations, total radioactivity in each sample was determined by sampling 100
\\u03bcl of sample seawater prior to filtration. Filters from Si-32 incubations
were placed on plastic planchettes and dried before covering with mylar film
and stored or analysis ashore using low level beta counters (Riso Inc).
Filters from C-14 incubations were acidified in glass scintillation vials,
scintillation cocktail (Ultima Gold XR) added followed by liquid scintillation
counting. Total radioactivity samples received 100 \\u03bcL of b-phenethylamine
and 5 mL of scintillation cocktail prior to analysis at sea using a Beckman
8500 scintillation counter.
 
For more information, see the Protocol documents (under Supplemental Files).";
    String awards_0_award_nid "757394";
    String awards_0_award_number "OCE-1756442";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1756442";
    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 
"14C 32Si Experiments 
   EXPORTS 
  PI: Mark Brzezinksi (UCSB) 
  Co-PIs: Kristen Buck (USF) & Bethany Jenkins (URI) 
  Contact: Janice Jones (UCSB) 
  Version date: 2020-Jan-06";
    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 "2020-01-06T18:15:25Z";
    String date_modified "2020-02-06T20:16:22Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.786013.1";
    Float64 Easternmost_Easting -144.691;
    Float64 geospatial_lat_max 50.5828;
    Float64 geospatial_lat_min 50.1496;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -144.691;
    Float64 geospatial_lon_min -145.1413;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 34.0;
    Float64 geospatial_vertical_min 8.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-07-06T04:50:00Z (local files)
2020-07-06T04:50:00Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_786013.das";
    String infoUrl "https://www.bco-dmo.org/dataset/786013";
    String institution "BCO-DMO";
    String instruments_0_acronym "GO-FLO";
    String instruments_0_dataset_instrument_nid "789448";
    String instruments_0_description "GO-FLO bottle cast used to collect water samples for pigment, nutrient, plankton, etc. The GO-FLO sampling bottle is specially designed to avoid sample contamination at the surface, internal spring contamination, loss of sample on deck (internal seals), and exchange of water from different depths.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/30/";
    String instruments_0_instrument_name "GO-FLO Bottle";
    String instruments_0_instrument_nid "411";
    String instruments_0_supplied_name "Go-Flo samplers";
    String instruments_1_acronym "CTD SBE 9";
    String instruments_1_dataset_instrument_nid "789446";
    String instruments_1_description "The Sea-Bird SBE 9 is a type of CTD instrument package.  The SBE 9 is the Underwater Unit and is most often combined with the SBE 11 Deck Unit (for real-time readout using conductive wire) when deployed from a research vessel. The combination of the SBE 9 and SBE 11 is called a SBE 911.  The SBE 9 uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 and SBE 4). The SBE 9 CTD can be configured with auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorometer, altimeter, etc.). Note that in most cases, it is more accurate to specify SBE 911 than SBE 9 since it is likely a SBE 11 deck unit was used.  more information from Sea-Bird Electronics";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
    String instruments_1_instrument_name "CTD Sea-Bird 9";
    String instruments_1_instrument_nid "488";
    String instruments_1_supplied_name "Sea-Bird Electronics CTD (SBE9plus)";
    String instruments_2_acronym "Light-Dark Bottle";
    String instruments_2_dataset_instrument_nid "789450";
    String instruments_2_description "The light/dark bottle is a way of measuring primary production by comparing before and after concentrations of dissolved oxygen.  Bottles containing seawater samples with phytoplankton are incubated for a predetermined period of time under light and dark conditions. Incubation is preferably carried out in situ, at the depth from which the samples were collected. Alternatively, the light and dark bottles are incubated in a water trough on deck, and neutral density filters are used to approximate the light conditions at the collection depth.Rates of net and gross photosynthesis and respiration can be determined from measurements of dissolved oxygen concentration in the sample bottles.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/82/";
    String instruments_2_instrument_name "Light-Dark Bottle";
    String instruments_2_instrument_nid "498";
    String instruments_3_acronym "FIA";
    String instruments_3_dataset_instrument_nid "789452";
    String instruments_3_description "An instrument that performs flow injection analysis. Flow injection analysis (FIA) is an approach to chemical analysis that is accomplished by injecting a plug of sample into a flowing carrier stream. FIA is an automated method in which a sample is injected into a continuous flow of a carrier solution that mixes with other continuously flowing solutions before reaching a detector. Precision is dramatically increased when FIA is used instead of manual injections and as a result very specific FIA systems have been developed for a wide array of analytical techniques.";
    String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB36/";
    String instruments_3_instrument_name "Flow Injection Analyzer";
    String instruments_3_instrument_nid "657";
    String instruments_3_supplied_name "Lachat Instruments QuikChem 8500 Series 2 anayzer";
    String keywords "24hr, 5umfilt, 5umprefilt, 6umfilt, activity, bco, bco-dmo, biological, bottle, bsi, BSi_0_6umfilt_5umprefilt, BSi_5umfilt, carbon, cast, chemical, chemistry, concentration, cruise, data, dataset, date, Date_Zulu, depth, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Nitrate, Earth Science > Oceans > Ocean Chemistry > Phosphate, erddap, event, Event_num, flag, iso, latitude, longitude, management, mass, mass_concentration_of_phosphate_in_sea_water, mole, mole_concentration_of_nitrate_in_sea_water, mole_concentration_of_nitrite_in_sea_water, n02, nitrate, nitrite, no2, NO2_flag, NO2_NO3, NO2_NO3_flag, no3, num, ocean, oceanography, oceans, office, organic, particulate, pcnt, pcnt_lo, phosphate, po4, PO4_flag, poc, POC_flag, pon, PON_flag, preliminary, rate, rate_14C_uptake_24hr_0_6umfilt_5umprefilt, rate_14C_uptake_24hr_5umfilt, rate_32Si_uptake_24hr_0_6umfilt_5umprefilt, rate_32Si_uptake_24hr_5umfilt, rate_32Si_uptake_specific_24hr_0_6umfilt_5umprefilt, rate_32Si_uptake_specific_24hr_5umfilt, rosette, Rosette_Bottle, science, sea, seawater, SiO4, SiO4_flag, specific, station, target, Target_Depth, time, Time_Zulu, trmt, uptake, water, zulu";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/786013/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/786013";
    Float64 Northernmost_Northing 50.5828;
    String param_mapping "{'786013': {'Latitude': 'flag - latitude', 'Longitude': 'flag - longitude', 'ISO_DateTime_UTC': 'master - time', 'Target_Depth': 'flag - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/786013/parameters";
    String people_0_affiliation "University of California-Santa Barbara";
    String people_0_affiliation_acronym "UCSB-MSI";
    String people_0_person_name "Mark A. Brzezinski";
    String people_0_person_nid "50663";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of South Florida";
    String people_1_affiliation_acronym "USF";
    String people_1_person_name "Kristen N. Buck";
    String people_1_person_nid "51624";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Rhode Island";
    String people_2_affiliation_acronym "URI";
    String people_2_person_name "Bethany D. Jenkins";
    String people_2_person_nid "558172";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "University of California-Santa Barbara";
    String people_3_affiliation_acronym "UCSB";
    String people_3_person_name "Janice L. Jones";
    String people_3_person_nid "51661";
    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 "Shannon Rauch";
    String people_4_person_nid "51498";
    String people_4_role "BCO-DMO Data Manager";
    String people_4_role_type "related";
    String project "Diatoms and carbon export";
    String projects_0_acronym "Diatoms and carbon export";
    String projects_0_description 
"NSF Award Abstract:
This project focuses on a group of microscopic single-celled photosynthetic organisms in the ocean called diatoms. Diatoms float in the surface ocean as part of a group of organisms collectively called phytoplankton. There are thousands of different species of diatoms distributed across the global ocean. A famous oceanographer Henry Bigelow once said \"All fish is diatoms\" reflecting the importance of diatoms as the base of the food chain that supports the world's largest fisheries. Despite their small size, diatom photosynthesis produces 20% of the oxygen on earth each year. That's more than all of the tropical rain forests on land. The major objective of the research is to understand how the metabolic differences among diatom species affects the amount of diatom organic carbon that is carried, or exported, from the surface ocean to the deep ocean. As diatoms are photo-synthesizers like green plants, their biological carbon comes from converting carbon dioxide dissolved in seawater from the atmosphere into organic forms. Diatoms also require a series of other nurtrients supplied by the ocean such as nitrogen and phosphorous and, uniquely for diatoms, the silicon used to construct their glass shells. This research will investigate how genetic and physiological differences among diatoms influence how each species react to changes in nutrient levels in the ocean and how those shifts affect the export of diatom carbon to the deep sea. The link between diatoms' physiological response and their carbon export comes about because shifts in physiology affect diatom attributes like how fast they sink and how tasty they are to predators. So if we can relate the physiological condition of different diatoms to the food-web pathways followed by different species, we can ultimately use knowledge of diatom physiological status and food web structure to predict how much diatom carbon gets to the deep sea. The research involves investigators with expertise in the physiology and genomics of diatoms and in the ocean's chemistry. The work will initially take place in the subarctic North Pacific in conjunction with the NASA Export Processes in the Ocean from RemoTe Sensing (EXPORTS) field program. The EXPORTS program is using a wide variety of methods to quantify the export and fate of photo-synthetically fixed carbon in the upper ocean. The research supports the training of undergraduate students, graduate students and a postdoctoral scholar. The research will also serve as the basis for activities aimed at K-12 and junior high school students.
The research will broadly impact our understanding of the biology of the biological pump (the transport of photo-synthetically fixed organic carbon to the deep sea) by forming a mechanistic basis for predicting the export of diatom carbon. It is hypothesized that the type and degree of diatom physiological stress are vital aspects of ecosystem state that drive export. To test this hypothesis, the genetic composition, rates of nutrient use and growth response of diatom communities will be evaluated and supported with measurements of silicon and iron stress to evaluate stress as a predictor of the path of diatom carbon export. The subarctic N. Pacific ecosystem is characterized as high nutrient low chlorophyll (HNLC) due to low iron (Fe) levels that are primary controllers constraining phytoplankton utilization of other nutrients. It has been a paradigm in low Fe, HNLC systems that diatoms grow at elevated Si:C and Si:N ratios and should be efficiently exported as particles significantly enriched in Si relative to C. However, Fe limitation also alters diatoms species composition and the high Si demand imposed by low Fe can drive HNLC regions to Si limitation or Si/Fe co-limitation. Thus, the degree of Si and/or Fe stress in HNLC waters can all alter diatom taxonomic composition, the elemental composition of diatom cells, and the path cells follow through the food web ultimately altering diatom carbon export.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.";
    String projects_0_end_date "2022-02";
    String projects_0_geolocation "Sub-Arctic Pacific, Ocean Station Papa";
    String projects_0_name "Collaborative Research: Diatoms, Food Webs and Carbon Export - Leveraging NASA EXPORTS to Test the Role of Diatom Physiology in the Biological Carbon Pump";
    String projects_0_project_nid "757387";
    String projects_0_start_date "2018-03";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 50.1496;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "Cruise,Activity,PO4_flag,SiO4_flag,NO2_NO3_flag,POC_flag,PON_flag";
    String summary "This dataset includes 32Si and 14C production data (experimental) from EXPORTS cruise RR1813. The EXPORTS field campaign in the subarctic North Pacific sampled an ecosystem characterized as high nutrient low chlorophyll (HNLC) due to low iron (Fe) levels that are primary controllers constraining phytoplankton utilization of other nutrients. It has been a paradigm in low Fe, HNLC systems that diatoms grow at elevated Si:C and Si:N ratios and should be efficiently exported as particles significantly enriched in Si relative to C. However, Fe limitation also alters diatoms species composition and the high Si demand imposed by low Fe can drive HNLC regions to Si limitation or Si/Fe co-limitation. Thus, the degree of Si and/or Fe stress in HNLC waters can all alter diatom taxonomic composition, the elemental composition of diatom cells, and the path cells follow through the food web ultimately altering diatom carbon export.\\r\\n\\r\\nWithin each ecosystem state examined in the EXPORTS program, nutrient biogeochemistry, diatom and phytoplankton community structure, and global diatom gene expression patterns (metatranscriptomics) are characterized in the lit ocean. Nutrient amendment experiments with tracer addition (14C, 32Si) are used to quantify the level of Si and Fe stress being experienced by the phytoplankton and to contextualize taxa-specific metatranscriptome responses for resolving gene expression profiles in the in situ communities.";
    String time_coverage_end "2018-09-07T12:56:55Z";
    String time_coverage_start "2018-08-16T14:00:13Z";
    String title "32Si and 14C production data (experimental) from EXPORTS cruise RR1813 on R/V Roger Revelle in the Subarctic North Pacific near Station PAPA from August to September 2018";
    String version "1";
    Float64 Westernmost_Easting -145.1413;
    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.


 
ERDDAP, Version 2.02
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