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Dataset Title:  Environmental data from Niskin bottle sampling during the Fall 2016 ESP
deployment in Monterey Bay, CA
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_756413)
Range: depth = 5.0 to 6.0m
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
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Things You Can Do With Your Graphs

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Date {
    String description "Date. Format: yyyy-mm-dd.";
    String ioos_category "Time";
    String long_name "Date";
    String units "unitless";
  Time_Pacific {
    String description "Time (Pacific time zone). Format: HH:MM.";
    String ioos_category "Time";
    String long_name "Time Pacific";
    String units "unitless";
  ISO_DateTime_Local {
    String description "Date and time (local) formatted to ISO8601 standard.";
    String ioos_category "Time";
    String long_name "ISO Date Time Local";
    String source_name "ISO_DateTime_Local";
    String units "unitless";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 5.0, 6.0;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Sampling depth";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  Chlorophyll_a {
    Float32 _FillValue NaN;
    Float32 actual_range 1.1, 56.5;
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "Chlorophyll a";
    String ioos_category "Ocean Color";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String units "micrograms per liter (ug/L)";
  DMSPd_in_situ {
    Float32 _FillValue NaN;
    Float32 actual_range 1.2, 7.9;
    String description "Dissolved DMSP sampled on boat immediately after seawater collection";
    String ioos_category "Currents";
    String long_name "DMSPd In Situ";
    String units "nanomolar (nM)";
  DMSPd_lab {
    Float32 _FillValue NaN;
    Float32 actual_range 1.5, 14.1;
    String description "Dissolved DMSP sampled after seawater transferred to lab";
    String ioos_category "Currents";
    String long_name "DMSPd Lab";
    String units "nanomolar (nM)";
  DMSPt {
    Float32 _FillValue NaN;
    Float32 actual_range 52.0, 4240.2;
    String description "Total DMSP";
    String ioos_category "Unknown";
    String long_name "DMSPT";
    String units "nanomolar (nM)";
  DMSPd_consumption_rate {
    Float32 _FillValue NaN;
    Float32 actual_range 11.45, 182.06;
    String description "Dissolved DMSP consumption rate";
    String ioos_category "Currents";
    String long_name "DMSPd Consumption Rate";
    String units "nM/d";
  Photosynthetic_eukaryotes {
    Float64 _FillValue NaN;
    Float64 actual_range 8958.333333, 30645.83333;
    String description "Determined by flow cytometry";
    String ioos_category "Unknown";
    String long_name "Photosynthetic Eukaryotes";
    String units "cells per milliliter (cells/mL)";
  Heterotrophic_bacteria {
    Float64 _FillValue NaN;
    Float64 actual_range 826402.7778, 4314583.333;
    String description "Determined by flow cytometry";
    String ioos_category "Unknown";
    String long_name "Heterotrophic Bacteria";
    String units "cells per milliliter (cells/mL)";
  Synechococcus {
    Float64 _FillValue NaN;
    Float64 actual_range 9625.0, 39493.05556;
    String description "Determined by flow cytometry";
    String ioos_category "Unknown";
    String long_name "Synechococcus";
    String units "cells per milliliter (cells/mL)";
  Akashiwo {
    Float64 _FillValue NaN;
    Float64 actual_range 6.859205776, 4914.666667;
    String description "Determined by microscopy";
    String ioos_category "Unknown";
    String long_name "Akashiwo";
    String units "cells per milliliter (cells/mL)";
  Chlorophyll_a_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.2;
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "Standard deviation of Chlorophyll_a (n = 3)";
    String ioos_category "Ocean Color";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String units "micrograms per liter (ug/L)";
  DMSPd_in_situ_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 4.0;
    String description "Standard deviation of DMSPd_in_situ (n = 3)";
    String ioos_category "Currents";
    String long_name "DMSPd In Situ Stdev";
    String units "nanomolar (nM)";
  DMSPd_lab_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 5.7;
    String description "Standard deviation of DMSPd_lab (n =3)";
    String ioos_category "Currents";
    String long_name "DMSPd Lab Stdev";
    String units "nanomolar (nM)";
  DMSPt_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 1.6, 352.0;
    String description "Standard deviation of DMSPt (n = 3)";
    String ioos_category "Unknown";
    String long_name "DMSPt Stdev";
    String units "nanomolar (nM)";
  Photosynthetic_eukaryotes_stdev {
    Float64 _FillValue NaN;
    Float64 actual_range 127.6720577, 4959.568396;
    String description "Standard deviation of Photosynthetic_eukaryotes (n = 2)";
    String ioos_category "Unknown";
    String long_name "Photosynthetic Eukaryotes Stdev";
    String units "cells per milliliter (cells/mL)";
  Heterotrophic_bacteria_stdev {
    Float64 _FillValue NaN;
    Float64 actual_range 3928.371007, 137492.9852;
    String description "Standard deviation of Heterotrophic_bacteria (n = 2)";
    String ioos_category "Unknown";
    String long_name "Heterotrophic Bacteria Stdev";
    String units "cells per milliliter (cells/mL)";
  Synechococcus_stdev {
    Float64 _FillValue NaN;
    Float64 actual_range 9.820927516, 3623.922254;
    String description "Standard deviation of Synechococcus (n = 2)";
    String ioos_category "Unknown";
    String long_name "Synechococcus Stdev";
    String units "cells per milliliter (cells/mL)";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Grab samples were taken using Niskin bottles that collected seawater at the
same depth and location of the Environmental Sample Processor deployed at
Station M0 (36.835 N, 121.901W). Water was transferred to a low-density
polyethylene cubitainer and maintained at ambient temperature until return to
lab within 30 min.
Chlorophyll a: 150 ml of seawater was filtered through a 25 mm GF/F filter in
triplicate using a vacuum pump and <5 in Hg pressure. The filter was placed in
a glass scintillation vial and 10 ml of 90% acetone was added and placed in
-20 freezer for at least 24 hours to extract the pigment. Extracted
chlorophyll a was quantified using fluorometry (Pennington and Chavez, 2000).
Flow Cytometry: Cubitainer seawater was transferred to a 50 ml Falcon tube
using laminar flow. 1.8 ml was then aliquoted to triplicate cryovials and
preserved with 200 ul of 5% glutaraldehyde and stored at -80 degrees C.
Analysis was run on a Beckman Coulter Altra flow cytometer for detection of
DNA, pigments, and forward and side light scatter (Monger and Landry, 1993).
Akashiwo Microscopy Counts: 7 - 14 ml of seawater was preserved to 1% final
concentration electron microscopy grade glutaraldehyde and stored at 4 degrees
C. Slides were made by filtering the full volume onto a 0.22 um black
polycarbonate filter (GE Water & Process Technologies) using a vacuum pump (<5
in Hg), and cells were counted under epifluorescence microscopy.
DMSP concentrations: Immediately upon return to the deck, duplicate samples
were collected from the Niskin bottle for in situ dissolved DMSP (DMSPd) (see
details below) before seawater transfer to the cubitainer. Upon return to the
laboratory, the cubitainer of water was gently mixed by inversion and three
replicate 10 ml sub-samples were removed by pipette into individual 15 ml
centrifuge tubes (Corning, polypropylene). The samples were immediately
acidified with 0.3 ml of 50% concentrated HCl (1.5% final concentration of
concentrated HCl) to preserve total DMSP (dissolved plus particulate). These
DMSPt samples were closed tightly and stored until analysis (described below)
which took place within three months of collection.\\u00a0
DMSPd consumption: To measure the consumption rate of dissolved DMSP, we used
the glycine betaine (GBT) inhibition technique (Kiene & Gerard, 1995; Li et
al., 2016). Immediately upon return to the laboratory, six 500 ml glass
bottles were filled with seawater from the gently-mixed cubitainer. Three of
the bottles were treated with 25 ul of a 100 mM GBT anhydrous reagent (Sigma)
solution (10 uM final GBT concentration), and three were left untreated as
controls. Bottles were incubated in seawater maintained within 1 degree C of
the in situ temperature. Immediately after GBT addition, the first time point
was collected by simultaneously filtering ~50 ml sub-samples from each bottle
through 47 mm Whatman GF/F filters using the small volume gravity drip
filtration protocol of Kiene and Slezak (2006). The first\\u00a03.5 ml of
filtrate from each sample was collected into 15 ml centrifuge tubes (Corning,
polypropylene) that contained 100 ul of 50% HCl to immediately preserve any
DMSP passing through the GF/F filter, which is defined as dissolved DMSP
(DMSPd). Additional time points from each bottle were collected at 3 and 6 h.
The rate of change of DMSPd in no-treatment bottles was subtracted from the
rate of change in the +GBT bottles to obtain an estimate of DMSPd consumption
rate (Kiene and Gerard, 1995).
DMSP Analysis: DMSP was quantified by proxy as the amount of DMS released from
samples after alkaline cleavage (White, 1982). For DMSPt, 0.05 to 0.5 ml of
each preserved sample was pipetted into a 14 ml glass serum vial, with the
volume being adjusted based on the concentration of DMSPt in the sample. For
DMSPd, the volume pipetted was 1.0 to 3.0 ml. Each serum vial was treated with
1 ml of 5 M NaOH and capped with a Teflon-faced serum stopper (Wheaton). After
1 h, the amount of DMS in each vial was quantified by purge and trap gas
chromatography with flame photometric detection. Briefly, each vial was
attached to the purge system and a flow of helium (90-100 ml per minute)
allowed bubbling of the solution. An excurrent needle led to a Nafion dryer
and six-port valve (Valco). The DMS in the samples was cryotrapped in a Teflon
tubing loop immersed in liquid nitrogen. After a 4 min sparge, during which
>99% of the DMS in the samples was removed, hot water replaced the liquid
nitrogen to introduce the DMS into the Shimadzu GC-2014 gas chromatograph.
Separation of the sulfur gases was achieved with a Chromosil 330 column
(Supelco; Sigma) maintained at 60 degrees C with a helium carrier flow of 25
ml per minute. The flame photometric detector was operated in sulfur mode and
maintained at 175 degrees C. Minimum detection limits during this study were
0.5 to 1 pmol DMS per sample with minimum detectable concentrations ranging
from 0.17 to 10 nM, depending on the volume analyzed. The GC-FPD system was
calibrated with a gas stream containing known amounts of DMS from a permeation
Problem report:\\u00a0For November chlorophyll a samples, fluorescence after
acid addition not measured but estimated from samples with similar total
fluorescence (Pennington and Chavez, 2000).";
    String awards_0_award_nid "541254";
    String awards_0_award_number "OCE-1342694";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1342694";
    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 "Dr David  L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Niskin Bottle Data from 2016 ESP Deployment 
   in Monterey Bay, CA 
  PI: Mary Ann Moran (University of Georgia) 
  Co-PI: Ronald Kiene (Dauphin Island Sea Lab) 
  Version date: 20-Feb-2019";
    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 2.2d  13 Jun 2019";
    String date_created "2019-02-20T21:04:36Z";
    String date_modified "2019-04-17T17:38:02Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.756413.1";
    Float64 geospatial_vertical_max 6.0;
    Float64 geospatial_vertical_min 5.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2019-08-20T20:40:33Z (local files)
2019-08-20T20:40:33Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_756413.das";
    String infoUrl "https://www.bco-dmo.org/dataset/756413";
    String institution "BCO-DMO";
    String instruments_0_acronym "Turner Fluorometer -10AU";
    String instruments_0_dataset_instrument_nid "756455";
    String instruments_0_description "The Turner Designs 10-AU Field Fluorometer is used to measure Chlorophyll fluorescence.  The 10AU Fluorometer can be set up for continuous-flow monitoring or discrete sample analyses. A variety of compounds can be measured using application-specific optical filters available from the manufacturer. (read more from Turner Designs, turnerdesigns.com, Sunnyvale, CA, USA)";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0393/";
    String instruments_0_instrument_name "Turner Designs Fluorometer -10-AU";
    String instruments_0_instrument_nid "464";
    String instruments_0_supplied_name "Turner Designs 10-AU Fluorometer";
    String instruments_1_acronym "Flow Cytometer";
    String instruments_1_dataset_instrument_nid "756456";
    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 "Beckman Coulter Altra";
    String instruments_2_acronym "Gas Chromatograph";
    String instruments_2_dataset_instrument_nid "756457";
    String instruments_2_description "Instrument separating gases, volatile substances, or substances dissolved in a volatile solvent by transporting an inert gas through a column packed with a sorbent to a detector for assay. (from SeaDataNet, BODC)";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB02/";
    String instruments_2_instrument_name "Gas Chromatograph";
    String instruments_2_instrument_nid "661";
    String instruments_2_supplied_name "Shimadzu GC-2014 gas chromatograph";
    String keywords "akashiwo, bacteria, bco, bco-dmo, biological, chemical, chemistry, chlorophyll, Chlorophyll_a, Chlorophyll_a_stdev, color, concentration, concentration_of_chlorophyll_in_sea_water, consumption, currents, data, dataset, date, depth, deviation, dmo, dmspd, DMSPd_consumption_rate, DMSPd_in_situ, DMSPd_in_situ_stdev, DMSPd_lab, DMSPd_lab_stdev, dmspt, DMSPt_stdev, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, erddap, eukaryotes, heterotrophic, Heterotrophic_bacteria, Heterotrophic_bacteria_stdev, iso, lab, local, management, ocean, ocean color, oceanography, oceans, office, pacific, photosynthetic, Photosynthetic_eukaryotes, Photosynthetic_eukaryotes_stdev, preliminary, rate, science, sea, seawater, situ, standard, standard deviation, stdev, synechococcus, Synechococcus_stdev, time, Time_Pacific, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String metadata_source "https://www.bco-dmo.org/api/dataset/756413";
    String param_mapping "{'756413': {'Depth': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/756413/parameters";
    String people_0_affiliation "University of Georgia";
    String people_0_affiliation_acronym "UGA";
    String people_0_person_name "Mary Ann Moran";
    String people_0_person_nid "51592";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Dauphin Island Sea Lab";
    String people_1_affiliation_acronym "DISL";
    String people_1_person_name "Dr Ronald Kiene";
    String people_1_person_nid "51594";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Bacterial Taxa that Control Sulfur Flux from the Ocean to the Atmosphere";
    String projects_0_acronym "OceanSulfurFluxBact";
    String projects_0_description 
"Surface ocean bacterioplankton preside over a divergence point in the marine sulfur cycle where the fate of dimethylsulfoniopropionate (DMSP) is determined. While it is well recognized that this juncture influences the fate of sulfur in the ocean and atmosphere, its regulation by bacterioplankton is not yet understood. Based on recent findings in biogeochemistry, bacterial physiology, bacterial genetics, and ocean instrumentation, the microbial oceanography community is poised to make major advances in knowledge of this control point. This research project is ascertaining how the major taxa of bacterial DMSP degraders in seawater regulate DMSP transformations, and addresses the implications of bacterial functional, genetic, and taxonomic diversity for global sulfur cycling.
The project is founded on the globally important function of bacterial transformation of the ubiquitous organic sulfur compound DMSP in ocean surface waters. Recent genetic discoveries have identified key genes in the two major DMSP degradation pathways, and the stage is now set to identify the factors that regulate gene expression to favor one or the other pathway during DMSP processing. The taxonomy of the bacteria mediating DMSP cycling has been deduced from genomic and metagenomic sequencing surveys to include four major groups of surface ocean bacterioplankton. How regulation of DMSP degradation differs among these groups and maps to phylogeny in co-occurring members is key information for understanding the marine sulfur cycle and predicting its function in a changing ocean. Using model organism studies, microcosm experiments (at Dauphin Island Sea Lab, AL), and time-series field studies with an autonomous sample collection instrument (at Monterey Bay, CA), this project is taking a taxon-specific approach to decipher the regulation of bacterial DMSP degradation.
This research addresses fundamental questions of how the diversity of microbial life influences the geochemical environment of the oceans and atmosphere, linking the genetic basis of metabolic potential to taxonomic diversity. The project is training graduate students and post-doctoral scholars in microbial biodiversity and providing research opportunities and mentoring for undergraduate students. An outreach program is enhance understanding of the role and diversity of marine microorganisms in global elemental cycles among high school students. Advanced Placement Biology students are participating in marine microbial research that covers key learning goals in the AP Biology curriculum. Two high school students are selected each year for summer research internships in PI laboratories.";
    String projects_0_end_date "2018-12";
    String projects_0_name "Bacterial Taxa that Control Sulfur Flux from the Ocean to the Atmosphere";
    String projects_0_project_nid "541255";
    String projects_0_start_date "2014-01";
    String publisher_name "Shannon Rauch";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Environmental data from Niskin bottle sampling during the Fall 2016 ESP deployment in Monterey Bay, CA. Samples were taken using Niskin bottles that collected seawater at the same depth and location of the Environmental Sample Processor deployed at Station M0 (36.835 N, 121.901W).";
    String title "Environmental data from Niskin bottle sampling during the Fall 2016 ESP deployment in Monterey Bay, CA";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5-beta";


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
For example,
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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