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Dataset Title:  1A: Partitioning of carbon as a function of pCO2 and temperature during growth
of Thalassiosira weissflogii from UCSB Marine Science Institute Passow Lab from
2009 to 2010 (OA - Effects of High CO2 project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_4046)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
   or a List of Values ?
   Maximum ?
 
 Lab_Id (text) ?      
   - +  ?
 latitude (degrees_north) ?      
   - +  ?
  < slider >
 longitude (degrees_east) ?      
   - +  ?
  < slider >
 Temp (Temperature, Degrees C) ?          15    20
 pCO2 (micro atm) ?          400    1000
 replicate (dimensionless) ?          1    2
 sampling (dimensionless) ?          0    11
 pH_at_25C (total scale) ?          7.529    8.566
 DIC (micro mol C L-1) ?          1627    2264
 fluorescence ((tbd)) ?          42    396
 NO3 (micro mol N L-1) ?          0.0    14.5
 PO4 (micro mol P L-1) ?          1.6    6.4
 Si (micro mol Si L-1) ?          0.1    58.4
 POC (micro mol C L-1) ?          27.5    462.93
 PON (micro mol N L-1) ?          1.49    16.76
 DOC (micro mol C L-1) ?          32.67    57.34
 DON (micro mol N L-1) ?          2.41    13.78
 TEP (GXEQ L-1) ?          290    8210
 bacteria_production (pmol leucine L-1 hr-1) ?          377    2375
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Lab_Id {
    String bcodmo_name "laboratory";
    String description "Lab Id - Lab identifier where experiments were conducted";
    String long_name "Lab Id";
    String units "text";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 34.4126, 34.4126;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Approximate Latitude Position of Lab; South is negative";
    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 -119.842, -119.842;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Approximate Longitude Position of Lab; West is negative";
    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";
  }
  Temp {
    Byte _FillValue 127;
    Byte actual_range 15, 20;
    String bcodmo_name "temperature";
    String description "Temperature";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "Degrees C";
  }
  pCO2 {
    Int16 _FillValue 32767;
    Int16 actual_range 400, 1000;
    String bcodmo_name "unknown";
    String description "pCO2 conditions";
    String long_name "P CO2";
    String units "micro atm";
  }
  replicate {
    Byte _FillValue 127;
    Byte actual_range 1, 2;
    String bcodmo_name "unknown";
    String description "number of replicate samples";
    String long_name "Replicate";
    String units "dimensionless";
  }
  sampling {
    Byte _FillValue 127;
    Byte actual_range 0, 11;
    String bcodmo_name "unknown";
    String description "day of experiment";
    String long_name "Sampling";
    String units "dimensionless";
  }
  pH_at_25C {
    Float32 _FillValue NaN;
    Float32 actual_range 7.529, 8.566;
    String bcodmo_name "unknown";
    String description "pH at 25 C";
    String long_name "P H At 25 C";
    String units "total scale";
  }
  DIC {
    Int16 _FillValue 32767;
    Int16 actual_range 1627, 2264;
    String bcodmo_name "unknown";
    String description "DIC";
    String long_name "DIC";
    String units "micro mol C L-1";
  }
  fluorescence {
    Int16 _FillValue 32767;
    Int16 actual_range 42, 396;
    String bcodmo_name "unknown";
    String description "Fluorescence - Instantaneous Chlorophyll Fluorescence (FT from AquaPen)";
    String long_name "Fluorescence";
    String units "(tbd)";
  }
  NO3 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 14.5;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "NO3";
    String long_name "Mole Concentration Of Nitrate In Sea Water";
    String units "micro mol N L-1";
  }
  PO4 {
    Float32 _FillValue NaN;
    Float32 actual_range 1.6, 6.4;
    String bcodmo_name "unknown";
    String description "PO4";
    String long_name "Mass Concentration Of Phosphate In Sea Water";
    String units "micro mol P L-1";
  }
  Si {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 58.4;
    String bcodmo_name "unknown";
    String description "Si";
    String long_name "Mass Concentration Of Silicate In Sea Water";
    String units "micro mol Si L-1";
  }
  POC {
    Float32 _FillValue NaN;
    Float32 actual_range 27.5, 462.93;
    String bcodmo_name "unknown";
    String description "POC";
    String long_name "Particulate Organic Carbon";
    String units "micro mol C L-1";
  }
  PON {
    Float32 _FillValue NaN;
    Float32 actual_range 1.49, 16.76;
    String bcodmo_name "unknown";
    String description "PON";
    String long_name "PON";
    String units "micro mol N L-1";
  }
  DOC {
    Float32 _FillValue NaN;
    Float32 actual_range 32.67, 57.34;
    String bcodmo_name "unknown";
    String description "DOC";
    String long_name "DOC";
    String units "micro mol C L-1";
  }
  DON {
    Float32 _FillValue NaN;
    Float32 actual_range 2.41, 13.78;
    String bcodmo_name "unknown";
    String description "DON";
    String long_name "DON";
    String units "micro mol N L-1";
  }
  TEP {
    Int16 _FillValue 32767;
    Int16 actual_range 290, 8210;
    String bcodmo_name "unknown";
    String description "TEP";
    String long_name "TEP";
    String units "GXEQ L-1";
  }
  bacteria_production {
    Int16 _FillValue 32767;
    Int16 actual_range 377, 2375;
    String bcodmo_name "unknown";
    String description "Bacteria production";
    String long_name "Bacteria Production";
    String units "pmol leucine L-1 hr-1";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Methods:  
 Two experiments, one with Thalassiosira weissflogii and one with
Dacyliosolen fragilissimus were conducted. Replicates of each treatment (2
temperatures by 2 pCO2 conditions) were grown in eight 20 L gas-tight
polyethylene bags. T. weissflogii and D. fragilissimus, respectively, were
grown in artificial and natural seawater based, modified f/2 media. Initial
nitrate addition was 15 \\u00b5mol L-1 NO3 for both species, and 6 and 8
\\u00b5mol L-1 PO4, and 16 and 50 \\u00b5mol L-1 SiO3 for T. weissflogii and D.
fragilissimus, respectively. Trace metals and vitamins were added according to
f/8.\\u00a0 Cultures were grown under a light / dark cycle of 14/10 hours at
~90 \\u2013 100 \\u00b5E m-2 s-1 at 15 \\u00b0C and 20 \\u00b0C. Partial pressure
levels of CO2 were set without bubbling to 400 and 1000 \\u00b5atm for both
temperatures; by appropriate addition of HCO3 and HCl.
 
Prior to the experiments the diatoms were acclimatized to the respective
target conditions growing semi-continuously in gas-tight polycarbonate bottles
for at least a week. At the onset of the experiment bags were inoculated with
~1000 cells ml-1 for T. weissflogii and ~500 cells ml-1 for the larger D.
fragilissimus. Daily sampling conducted immediately after the end of each
light cycle, was continued for at least 6 days after NO3 depletion.
 
For the determination of particulate organic carbon and nitrogen (POC and
PON), samples were filtered onto precombusted (5 hours at 450 \\u00b0C)
glassfibre filters (Whatman, GF/F, 0.7 \\u00b5m nominal poresize), dried at ~60
\\u00b0C for 24 hours and analyzed on a CHN organic elemental analyzer (Control
Equipment Corp., CEC 440HA). Samples for dissolved inorganic nitrate, nitrite,
phosphate and silicate were filtered through 0.2 \\u00b5m filters and measured
on a flow injection analyzer (Lachat Instruments Div., QuikChem 8000). Samples
for dissolved organic carbon (DOC) were gravity-filtered through precombusted
GF/F filters, with the filtrate being collecting collected in acid-washed
(HCl, 10%) and precombusted glass vials and frozen (at -20 \\u00b0C). The
analysis was carried out via high temperature combustion on a modified
Shimadzu TOC-V analyzers. Dissolved inorganic carbon (DIC) was measured on a
non-dispersive infrared (NDIR) analyzer. Samples were filtered through
glassfibre filters (GF/F) and stored in gas-tight ~400 ml borosilicate bottles
until analysis.
 
pH (total scale) was measured spetrophotometrically at 25\\u00baC (Thermo
Scientific Genesys 105 VIS Spetrophotometer with a SPG 1A air-cooled single
cell Peltier element), using m-cresol as an indicator dye. The dye was
calibrated against certified reference material (A. Dickson, La Jolla,
California). Samples for transparent exopolymer particles (TEP) were filtered
onto 0.4 \\u00b5m polycarbonate filters (Poretics) and subsequently stained
with Alcian Blue following the procedure of Passow and Alldredge (1995).";
    String awards_0_award_nid "55209";
    String awards_0_award_number "OCE-1041038";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1041038&HistoricalAwards=false";
    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 cdm_data_type "Other";
    String comment 
"OA_Effects_of_HighCO2 
  Version: 19 September 2013 
  PIs: Passow, Carlson, Brzezinski 
  Data Set #1A: Partitioning of carbon as a function of pCO2 and temperature during growth of Thalassiosira weissflogii 
  
  
  Data Set #1A: Partitioning of carbon as a function of pCO2 and temperature during growth of Thalassiosira weissflogii";
    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 "2013-09-20T18:59:23Z";
    String date_modified "2019-09-04T00:55:26Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.4046.1";
    Float64 Easternmost_Easting -119.842;
    Float64 geospatial_lat_max 34.4126;
    Float64 geospatial_lat_min 34.4126;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -119.842;
    Float64 geospatial_lon_min -119.842;
    String geospatial_lon_units "degrees_east";
    String history 
"2020-07-06T05:37:58Z (local files)
2020-07-06T05:37:58Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_4046.html";
    String infoUrl "https://www.bco-dmo.org/dataset/4046";
    String institution "BCO-DMO";
    String instruments_0_acronym "LI-COR LI-840";
    String instruments_0_dataset_instrument_description "Dissolved inorganic carbon (DIC) was measured on a non-dispersive infrared (NDIR) analyzer.";
    String instruments_0_dataset_instrument_nid "6316";
    String instruments_0_description "The LI-COR LI-840 is specifically designed for continuous monitoring of CO2 and H2O over a wide range of environmental conditions. The LI-840 is an absolute, non-dispersive, infrared (NDIR) gas analyzer based on a single, interchangeable optical path, and a dual wavelength infrared detection system.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/382/";
    String instruments_0_instrument_name "LI-COR LI-840 NDIR Gas Analyzer";
    String instruments_0_instrument_nid "566";
    String instruments_0_supplied_name "NDIR Gas Analyzer";
    String instruments_1_acronym "Shimadzu TOC-V";
    String instruments_1_dataset_instrument_description "Samples for dissolved organic carbon (DOC) were gravity-filtered through  precombusted GF/F filters, with the filtrate being collecting collected  in acid-washed (HCl, 10%) and precombusted glass vials and frozen (at  -20 �C). The analysis was carried out via high temperature combustion on  a modified Shimadzu TOC-V analyzers.";
    String instruments_1_dataset_instrument_nid "6315";
    String instruments_1_description "A Shimadzu TOC-V Analyzer measures DOC by high temperature combustion method.";
    String instruments_1_instrument_external_identifier "http://onto.nerc.ac.uk/CAST/124";
    String instruments_1_instrument_name "Shimadzu TOC-V Analyzer";
    String instruments_1_instrument_nid "603";
    String instruments_1_supplied_name "Shimadzu TOC-V Analyzer";
    String instruments_2_acronym "CHN_EA";
    String instruments_2_dataset_instrument_description "For the determination of particulate organic carbon and nitrogen (POC  and PON), samples were filtered onto precombusted (5 hours at 450 �C)  glassfibre filters (Whatman, GF/F, 0.7 �m nominal poresize), dried at  ~60 �C for 24 hours and analyzed on a CHN organic elemental analyzer (Control Equipment Corp., CEC 440HA)";
    String instruments_2_dataset_instrument_nid "6313";
    String instruments_2_description "A CHN Elemental Analyzer is used for the determination of carbon, hydrogen, and  nitrogen content in organic and other types of materials, including  solids, liquids, volatile, and viscous samples.";
    String instruments_2_instrument_name "CHN Elemental Analyzer";
    String instruments_2_instrument_nid "625";
    String instruments_2_supplied_name "Control Equipment Corp., CEC 440HA";
    String instruments_3_acronym "FIA";
    String instruments_3_dataset_instrument_description "Samples for dissolved inorganic nitrate, nitrite, phosphate and silicate  were filtered through 0.2 �m filters and measured on a flow injection  analyzer (Lachat Instruments Div., QuikChem 8000).";
    String instruments_3_dataset_instrument_nid "6314";
    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 Div., QuikChem 8000";
    String instruments_4_acronym "pH Sensor";
    String instruments_4_dataset_instrument_description "pH (total scale) was measured spetrophotometrically at 25�C (Thermo  Scientific Genesys 105 VIS Spetrophotometer with a SPG 1A air-cooled  single cell Peltier element), using m-cresol as an indicator dye.";
    String instruments_4_dataset_instrument_nid "6317";
    String instruments_4_description "General term for an instrument that measures the pH or how acidic or basic a solution is.";
    String instruments_4_instrument_name "pH Sensor";
    String instruments_4_instrument_nid "674";
    String instruments_4_supplied_name "Thermo Scientific Genesys 105 VIS Spetrophotometer with a SPG 1A air-cooled single cell Peltier element";
    String keywords "bacteria, bacteria_production, bco, bco-dmo, biological, carbon, carbon dioxide, chemical, chemistry, co2, commerce, concentration, data, dataset, department, dic, dioxide, dmo, doc, don, earth, Earth Science > Oceans > Ocean Chemistry > Nitrate, Earth Science > Oceans > Ocean Chemistry > Phosphate, Earth Science > Oceans > Ocean Chemistry > Silicate, erddap, fluorescence, lab, Lab_Id, latitude, longitude, management, mass, mass_concentration_of_phosphate_in_sea_water, mass_concentration_of_silicate_in_sea_water, mole, mole_concentration_of_nitrate_in_sea_water, n02, nitrate, no3, ocean, oceanography, oceans, office, organic, particulate, pCO2, pH_at_25C, phosphate, po4, POC, pon, preliminary, production, replicate, sampling, science, sea, seawater, silicate, Temp, temperature, tep, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/4046/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/4046";
    Float64 Northernmost_Northing 34.4126;
    String param_mapping "{'4046': {'Lat': 'flag - latitude', 'Lon': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/4046/parameters";
    String people_0_affiliation "University of California-Santa Barbara";
    String people_0_affiliation_acronym "UCSB-MSI";
    String people_0_person_name "Dr Uta Passow";
    String people_0_person_nid "51317";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-Santa Barbara";
    String people_1_affiliation_acronym "UCSB-MSI";
    String people_1_person_name "Mark A. Brzezinski";
    String people_1_person_nid "50663";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of California-Santa Barbara";
    String people_2_affiliation_acronym "UCSB-MSI";
    String people_2_person_name "Craig Carlson";
    String people_2_person_nid "50575";
    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-MSI";
    String people_3_person_name "Mr Jan Taucher";
    String people_3_person_nid "51732";
    String people_3_role "Student";
    String people_3_role_type "related";
    String people_4_affiliation "University of California-Santa Barbara";
    String people_4_affiliation_acronym "UCSB-MSI";
    String people_4_person_name "Dr Uta Passow";
    String people_4_person_nid "51317";
    String people_4_role "Contact";
    String people_4_role_type "related";
    String people_5_affiliation "Woods Hole Oceanographic Institution";
    String people_5_affiliation_acronym "WHOI BCO-DMO";
    String people_5_person_name "Stephen R. Gegg";
    String people_5_person_nid "50910";
    String people_5_role "BCO-DMO Data Manager";
    String people_5_role_type "related";
    String project "OA - Effects of High CO2";
    String projects_0_acronym "OA - Effects of High CO2";
    String projects_0_description 
"From the NSF Award Abstract
Coastal waters are already experiencing episodic exposure to carbonate conditions that were not expected until the end of the century making understanding the response to these episodic events as important as understanding the long-term mean response. Among the most striking examples are those associated with coastal upwelling along the west coast of the US, where the pH of surface waters may drop to 7.6 and pCO2 can reach 1100 uatm. Upwelling systems are responsible for a significant fraction of global carbon export making them prime targets for investigations on how ocean acidification is already affecting the biological pump today.
In this study, researchers at the University of California at Santa Barbara will investigate the potential effects of ocean acidification on the strength of the biological pump under the transient increases in CO2 experienced due to upwelling. Increases in CO2 are expected to alter the path and processing of carbon through marine food webs thereby strengthening the biological pump. Increases in inorganic carbon without proportional increases in nutrients result in carbon over-consumption by phytoplankton. How carbon over-consumption affects the strength of the biological pump will depend on the fate of the extra carbon that is either incorporated into phytoplankton cells forming particulate organic matter (POM), or is excreted as dissolved organic matter (DOM). Results from mesocosm experiments demonstrate that the mechanisms controlling the partitioning of fixed carbon between the particulate and dissolved phases, and the processing of those materials, are obscured when both processes operate simultaneously under natural or semi-natural conditions. Here, POM and DOM production and the heterotrophic processing of these materials will be separated experimentally across a range of CO2 concentrations by conducting basic laboratory culture experiments. In this way the mechanisms whereby elevated CO2 alters the flow of carbon along these paths can be elucidated and better understood for use in mechanistic forecasting models.
Broader Impacts- The need to understand the effects of ocean acidification for the future of society is clear. In addition to research education, both formal and informal, will be important for informing the public. Within this project 1-2 graduate students and 2-3 minority students will be recruited as interns from the CAMP program (California Alliance for Minority Participation). Within the 'Ocean to Classrooms' program run by outreach personnel from UCSB's Marine Science Institute an educational unit for K-12 students will be developed. Advice and support is also given to the Education Coordinator of NOAA, Channel Islands National Marine Sanctuary for the development of an education unit on ocean acidification.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Arnosti C, Grossart H-P, Muehling M, Joint I, Passow U. \"Dynamics of extracellular enzyme activities in seawater under changed atmsopheric pCO2: A mesocosm investigation.,\" Aquatic Microbial Ecology, v.64, 2011, p. 285.
Passow U. \"The Abiotic Formation of TEP under Ocean Acidification Scenarios.,\" Marine Chemistry, v.128-129, 2011, p. 72.
Passow, Uta; Carlson, Craig A.. \"The biological pump in a high CO2 world,\" MARINE ECOLOGY PROGRESS SERIES, v.470, 2012, p. 249-271.
Gaerdes, Astrid; Ramaye, Yannic; Grossart, Hans-Peter; Passow, Uta; Ullrich, Matthias S.. \"Effects of Marinobacter adhaerens HP15 on polymer exudation by Thalassiosira weissflogii at different N:P ratios,\" MARINE ECOLOGY PROGRESS SERIES, v.461, 2012, p. 1-14.
Philip Boyd, Tatiana Rynearson, Evelyn Armstrong, Feixue Fu, Kendra Hayashi, Zhangi Hu, David Hutchins, Raphe Kudela, Elena Litchman, Margaret Mulholland, Uta Passow, Robert Strzepek, Kerry Whittaker, Elizabeth Yu, Mridul Thomas. \"Marine Phytoplankton Temperature versus Growth Responses from Polar to Tropical Waters - Outcome of a Scientific Community-Wide Study,\" PLOS One 8, v.8, 2013, p. e63091.
Arnosti, C., B. M. Fuchs, R. Amann, and U. Passow. \"Contrasting extracellular enzyme activities of particle-associated bacteria from distinct provinces of the North Atlantic Ocean,\" Frontiers in Microbiology, v.3, 2012, p. 1.
Koch, B.P., Kattner, G., Witt, M., Passow, U., 2014. Molecular insights into the microbial formation of marine dissolved organic matter: recalcitrant or labile? Biogeosciences Discuss. 11 (2), 3065-3111.
Taucher, J., Brzezinski, M., Carlson, C., James, A., Jones, J., Passow, U., Riebesell, U., submitted. Effects of warming and elevated pCO2 on carbon uptake and partitioning of the marine diatoms Thalassiosira weissflogii and Dactyliosolen fragilissimus. Limnology and Oceanography";
    String projects_0_end_date "2014-09";
    String projects_0_geolocation "Passow Lab, Marine Science Institute, University of California Santa Barbara";
    String projects_0_name "Will high CO2 conditions affect production, partitioning and fate of organic matter?";
    String projects_0_project_nid "2284";
    String projects_0_project_website "http://www.msi.ucsb.edu/people/research-scientists/uta-passow";
    String projects_0_start_date "2010-10";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 34.4126;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "Lab_Id,latitude,longitude";
    String summary "Experiments with the diatom Thalassiosira weissflogii (CCMP 1336) on the impact of temperature and carbonate chemistry on carbon uptake and partitioning into particulate and dissolved organic matter.\\r\\n\\r\\nExperiments were conducted in March and May 2013 in Santa Barbara California, in the Passow lab.\\r\\nTreatments: multifactorial analysis with 2 temperature treatments (15C, 20C) and two ocean acidification treatments (400 and 1000 micro-atm).\\r\\n\\r\\nDaily sampling after the light cycle (14/10) was completed.";
    String title "1A: Partitioning of carbon as a function of pCO2 and temperature during growth of Thalassiosira weissflogii from UCSB Marine Science Institute Passow Lab from 2009 to 2010 (OA - Effects of High CO2 project)";
    String version "1";
    Float64 Westernmost_Easting -119.842;
    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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