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Dataset Title:  3A: Removal of organic carbon by natural bacterioplankton communities as a
function of pCO2 from laboratory experiments between 2012 and 2016
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_472032)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 experiment (unitless) ?          "BIOS"    "OA9"
 site (unitless) ?          "SBC"    "sargasso_sea"
 latitude (degrees_north) ?          -17.4502    34.4216
  < slider >
 longitude (degrees_east) ?          -149.8727    -64.6353
  < slider >
 bottle_number (unitless) ?          "11_12"    "7_8"
 doc_addition (unitless) ?          "A. glacialis exudate"    "T. weiss lysate"
 target_pCO2 (parts per million (ppm)) ?          250    1500
 time_point (unitless) ?          "T0"    "T9"
 time_days (unitless) ?          0.0    17.05
 date (unitless) ?          "2012-09-20"    "2016-01-22"
 bact_abun_x10e6_avg (cells per milliliter) ?          0.0    4.86
 bact_abun_x10e6_stderr (cells per milliliter) ?          0.0    1.16
 bact_abun_x10e6_stdev (cells per milliliter) ?          0.0    1.64
 toc_avg (micromoles per liter (uM)) ?          63.84    398.62
 toc_stderr (micromoles per liter (uM)) ?          0.0    14.2
 toc_stdev (micromoles per liter (uM)) ?          0.0    20.08
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  experiment {
    String bcodmo_name "exp_id";
    String description "Experiment identifier";
    String long_name "Experiment";
    String units "unitless";
  }
  site {
    String bcodmo_name "site";
    String description "Site the water for the experiment came from";
    String long_name "Site";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -17.4502, 34.4216;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude where water samples were collected; north is positive.";
    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 -149.8727, -64.6353;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude where water samples were collected; 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";
  }
  bottle_number {
    String bcodmo_name "bottle";
    String description "Bottle identifier";
    String long_name "Bottle Number";
    String units "unitless";
  }
  doc_addition {
    String bcodmo_name "treatment";
    String description "Dissolved organic carbon additions. See Aquisition Description section for an explaination�of values.";
    String long_name "Doc Addition";
    String units "unitless";
  }
  target_pCO2 {
    Int16 _FillValue 32767;
    Int16 actual_range 250, 1500;
    String bcodmo_name "pCO2";
    String description "Target pCO2 level";
    String long_name "Target P CO2";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PCO2C101/";
    String units "parts per million (ppm)";
  }
  time_point {
    String bcodmo_name "time_point";
    String description "Time point identifier in experiment";
    String long_name "Time Point";
    String units "unitless";
  }
  time_days {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 17.05;
    String bcodmo_name "time_elapsed";
    String description "Elapsed time since start of experiment in days";
    String long_name "Time Days";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
    String units "unitless";
  }
  date {
    String bcodmo_name "date";
    String description "Date of experiment in format YYYY-MM-DD";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  bact_abun_x10e6_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 4.86;
    String bcodmo_name "bact_abundance";
    String description "Bacterial abundance multiplied by 10^6";
    String long_name "Bact Abun X10e6 Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/BNTX";
    String units "cells per milliliter";
  }
  bact_abun_x10e6_stderr {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.16;
    String bcodmo_name "bact_abundance";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Standard error of bacterial abundance multiplied by 10^6";
    String long_name "Bact Abun X10e6 Stderr";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/BNTX";
    String units "cells per milliliter";
  }
  bact_abun_x10e6_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.64;
    String bcodmo_name "bact_abundance";
    String description "Standard deviation Bacterial abundance multiplied by 10^6";
    String long_name "Bact Abun X10e6 Stdev";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/BNTX";
    String units "cells per milliliter";
  }
  toc_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 63.84, 398.62;
    String bcodmo_name "TOC";
    String description "Total organic carbon";
    String long_name "Toc Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/";
    String units "micromoles per liter (uM)";
  }
  toc_stderr {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 14.2;
    String bcodmo_name "TOC";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Standard error of total organic carbon";
    String long_name "Toc Stderr";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/";
    String units "micromoles per liter (uM)";
  }
  toc_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 20.08;
    String bcodmo_name "TOC";
    String description "Standard deviation of total organic carbon";
    String long_name "Toc Stdev";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCOTX/";
    String units "micromoles per liter (uM)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"TOC measurements:
 
The procedures used to set up each experiment (inoculum filtration and
dilution with 0.2 um filtrate) removed the majority of particulate organic
carbon such that changes in bacterioplankton carbon production and DOC removal
were mainly a function of the growth of the inoculum. Ideally, samples
collected for organic carbon would be filtered in order to directly assess DOC
removal separate from bacterioplankton carbon production over the course of
the incubations. However, sample handling during filtration can result in
contamination that obscures changes in DOC on the scale of a few micro-molar
C. To avoid contamination, seawater samples from the incubation experiments
were not filtered. Therefore, measured values of organic carbon include both
DOC and bacterioplankton carbon and are considered total organic carbon (TOC).
 
TOC samples were collected into 60 mL high-density polyethylene bottles
(Sargasso Sea and South Pacific Subtropical Gyre) or in combusted 40 mL glass
EPA vials with Teflon coated silicone septa (Santa Barbara Channel). All TOC
samples were frozen at -20 C until analysis. Samples were analyzed via high
temperature combustion method on a modified Shimadzu TOC-V or Shimadzu TOC-L
using the standardization and referencing approaches described in Carlson et
al. 2010.
 
Bacterioplankton abundance measurement \\u2013 Samples for bacterioplankton
abundance were analyzed by epifluorescence microscopy with 0, 6-diamidino
-2-phenyl dihydrochloride (5ug/mL, DAPI, SIGMA-Aldrich, St. Louis, MO, USA)
according to Porter and Feig 1980, or by Flow Cytometry (FCM) on an LSR II
with SYBR Green I according to Nelson et al. 2011. See Parsons et al. 2014 and
Nelson et al. 2011 regarding sample preparation and instrument settings for
epifluorescence microscopy and FCM analyses, respectively. DAPI direct counts
and FCM analysis enumerate total prokaryotic abundance. We were not able to
differentiate between bacterial and archaeal domains and refer to the combined
cell densities as bacterioplankton abundance (Glockner et al. 1999).
 
Water sources:
 
Experiment OA11 was conducted on board a research cruise R/V Kilo Moana
KM1416. The Sargasso Sea experiments were conducted at the Bermuda Institute
for Ocean Sciences (BIOS) with water was collected via the R/V Atlantic
Explorer. The Santa Barbara Channel experiments were conducted with water
collected near-shore via a pier near the UCSB campus.
 
Experimental design:
 
At all three study sites, experiments consisted of 0.2 um-filtered (0.2 um
GSWP, Millipore, Billerica, MA) seawater or 0.2 um-filtered phytoplankton
exudate that was inoculated with natural bacterial communities. The inoculum
of natural bacterial communities consisted of either unfiltered whole seawater
(Sargasso Sea and South Pacific Subtropical Gyre experiments) or 1.2 um
filtrate (Santa Barbara Channel experiments; 1.2 um RAWP, Millipore,
Billerica, MA). Particulate organic carbon concentration in oligotrophic gyres
is low (1-3 umol L-1) so to avoid filtration artifacts such as reduced
bacterial production (unpublished data) and contamination of DOC due to
handling, the inoculum was not pre-filtered for the experiments conducted in
oligotrophic waters. Because particulate organic carbon concentration can be
much greater in coastal upwelling systems it was necessary to remove large
particles and organisms from the inoculum. Inoculum was added at 25 \\u2013 30%
of final volume, effectively diluting grazer concentrations and grazing
pressure. All filters were pre-rinsed with ~2 L of deionized distilled water
and sample water prior to use in order to remove organic contaminants from the
filters.
 
Four types of DOC treatments were used and are described in the data as
\\\"doc_additions\\\":
 
1\\. None: unamended seawater, which provided naturally occurring DOC.  
 2. CNP: Naturally occurring DOC amended with glucose (~10 uM C) plus NH4 Cl
(1uM) and K2HPO4 (0.1uM) (CNP)  
 3. Species name + \\\" exudate\\\": phytoplankton exudate  
 4. Species name + \\\" lysate\\\": naturally occurring DOC amended with
phytoplankton lysate (~10 uM C L-1; labeled by phytoplankton species used).
 
The various treatments were generated by inoculating the 0.2 um pre-filtered
seawater or exudate with the microbial community; this solution was then
divided into two polycarbonate (PC) containers to adjust\\u00a0pCO2.\\u00a0pCO2
levels were adjusted via chemical additions (Sargasso Sea experiment) or by
bubbling with CO2-mixed air (Santa Barbara Channel and South Pacific
Subtropical Gyre experiments). Adjusted seawater incubations were then
transferred into new PC carboys and CNP or lysate was added, if appropriate. A
very small volume of lysate (1.2 mL to 11.5 L of experimental volume) or CNP
(12 mL to 10 L of experimental water for the Sargasso Sea experiment; 0.28 mL
to 10 L of experimental volume for the Santa Barbara Channel experiment) was
added to minimize perturbing the carbonate chemistry. All experiments were
conducted in duplicate, at in situ temperatures, and in the dark to eliminate
photoautotrophic production. All PC bottles had been acid-washed (5 % or 10 %
HCL) and rinsed with deionized distilled water and sample water before use.  
 \\u00a0";
    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 
"Bacterial use of DOC as a function of pCO2 
  Uta Passow, PI 
    version 28 Nov 2016";
    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 "2013-11-25T16:22:02Z";
    String date_modified "2019-09-04T18:22:42Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.665253";
    Float64 Easternmost_Easting -64.6353;
    Float64 geospatial_lat_max 34.4216;
    Float64 geospatial_lat_min -17.4502;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -64.6353;
    Float64 geospatial_lon_min -149.8727;
    String geospatial_lon_units "degrees_east";
    String history 
"2020-07-08T04:14:12Z (local files)
2020-07-08T04:14:12Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_472032.html";
    String infoUrl "https://www.bco-dmo.org/dataset/472032";
    String institution "BCO-DMO";
    String instruments_0_acronym "Shimadzu TOC-V";
    String instruments_0_dataset_instrument_description "Samples were analyzed via high-temperature combustion method on a modified Shimadzu TOC-V or Shimadzu TOC-L using the standardization and referencing approaches described in Carlson et al. 2010.";
    String instruments_0_dataset_instrument_nid "665756";
    String instruments_0_description "A Shimadzu TOC-V Analyzer measures DOC by high temperature combustion method.";
    String instruments_0_instrument_external_identifier "http://onto.nerc.ac.uk/CAST/124";
    String instruments_0_instrument_name "Shimadzu TOC-V Analyzer";
    String instruments_0_instrument_nid "603";
    String instruments_0_supplied_name "modified Shimadzu TOC-L";
    String instruments_1_acronym "Flow Cytometer";
    String instruments_1_dataset_instrument_description "Flow Cytometry (FCM) on an LSR II with SYBR Green I according to Nelson et al. 2011.";
    String instruments_1_dataset_instrument_nid "665758";
    String instruments_1_description 
"Flow cytometers (FC or FCM) are automated instruments that quantitate properties of single cells, one cell at a time. They can measure cell size, cell granularity, the amounts of cell components such as total DNA, newly synthesized DNA, gene expression as the amount messenger RNA for a particular gene, amounts of specific surface receptors, amounts of intracellular proteins, or transient signalling events in living cells.
(from: http://www.bio.umass.edu/micro/immunology/facs542/facswhat.htm)";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB37/";
    String instruments_1_instrument_name "Flow Cytometer";
    String instruments_1_instrument_nid "660";
    String instruments_1_supplied_name "Flow Cytometry (FCM)";
    String instruments_2_dataset_instrument_description "Samples for bacterioplankton abundance were analyzed by epifluorescence microscopy with 0, 6-diamidino -2-phenyl dihydrochloride (5�g mL-1, DAPI, SIGMA-Aldrich, St. Louis, MO, USA) according to Porter and Feig 1980.";
    String instruments_2_dataset_instrument_nid "665757";
    String instruments_2_description "Instruments that generate enlarged images of samples using the phenomena of fluorescence and phosphorescence instead of, or in addition to, reflection and absorption of visible light. Includes conventional and inverted instruments.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB06/";
    String instruments_2_instrument_name "Microscope-Fluorescence";
    String instruments_2_instrument_nid "695";
    String instruments_2_supplied_name "Epifluorescence microscopy";
    String instruments_3_acronym "Shimadzu TOC-L";
    String instruments_3_dataset_instrument_description "Samples were analyzed via high-temperature combustion method on a modified Shimadzu TOC-V or Shimadzu TOC-L using the standardization and referencing approaches described in Carlson et al. 2010.";
    String instruments_3_dataset_instrument_nid "665755";
    String instruments_3_description 
"A Shimadzu TOC-L Analyzer measures DOC by high temperature combustion method.

Developed by Shimadzu, the 680 degree�C combustion catalytic oxidation method is now used worldwide. One of its most important features is the capacity to efficiently oxidize hard-to-decompose organic compounds, including insoluble and macromolecular organic compounds. The 680 degree�C combustion catalytic oxidation method has been adopted for the TOC-L series.

http://www.shimadzu.com/an/toc/lab/toc-l2.html";
    String instruments_3_instrument_external_identifier "http://onto.nerc.ac.uk/CAST/124.html";
    String instruments_3_instrument_name "Shimadzu TOC-L Analyzer";
    String instruments_3_instrument_nid "527277";
    String instruments_3_supplied_name "modified Shimazdu TOC-L";
    String keywords "abun, addition, average, bact, bact_abun_x10e6_avg, bact_abun_x10e6_stderr, bact_abun_x10e6_stdev, bco, bco-dmo, biological, bottle, bottle_number, carbon, carbon dioxide, chemical, co2, commerce, data, dataset, date, days, department, deviation, dioxide, dmo, doc, doc_addition, erddap, experiment, latitude, longitude, management, number, oceanography, office, point, preliminary, site, standard, standard deviation, stderr, stdev, target, target_pCO2, time, time_days, time_point, toc, toc_avg, toc_stderr, toc_stdev, x10e6";
    String license "https://www.bco-dmo.org/dataset/472032/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/472032";
    Float64 Northernmost_Northing 34.4216;
    String param_mapping "{'472032': {'latitude': 'flag - latitude', 'longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/472032/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 "Ms Anna James";
    String people_3_person_nid "471722";
    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 people_6_affiliation "Woods Hole Oceanographic Institution";
    String people_6_affiliation_acronym "WHOI BCO-DMO";
    String people_6_person_name "Amber York";
    String people_6_person_nid "643627";
    String people_6_role "BCO-DMO Data Manager";
    String people_6_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 -17.4502;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Factors that affect the removal of organic carbon by heterotrophic bacterioplankton can impact the rate and magnitude of organic carbon loss in the ocean through the conversion of a portion of consumed organic carbon to CO2. Through enhanced rates of consumption, surface bacterioplankton communities can also reduce the amount of dissolved organic carbon (DOC) available for export from the surface ocean. The present study investigated the direct effects of elevated pCO2 on bacterioplankton removal of several forms of DOC ranging from glucose to complex phytoplankton exudate and lysate, and naturally occurring DOC. Elevated pCO2 (1000 \\u2013 1500 ppm) enhanced both the rate and magnitude of organic carbon removal by bacterioplankton communities compared to low (pre-industrial and ambient) pCO2 (250 \\u2013 ~400 ppm). The increased removal was largely due to enhanced respiration, rather than enhanced production of bacterioplankton biomass.";
    String title "3A: Removal of organic carbon by natural bacterioplankton communities as a function of pCO2 from laboratory experiments between 2012 and 2016";
    String version "1";
    Float64 Westernmost_Easting -149.8727;
    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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