Accessing BCO-DMO data
log in    
Brought to you by BCO-DMO    

ERDDAP > tabledap > Make A Graph ?

Dataset Title:  Element quotas of individual Synechococcus cells collected during Bermuda
Atlantic Time-series Study (BATS) cruises aboard the R/V Atlantic Explorer
between dates 2012-07-11 and 2013-10-13 (Si_in_Syn project)
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_644840)
Range: longitude = -65.6664 to -64.1614°E, latitude = 21.6699 to 31.6691°N, depth = 1.0 to 88.0m
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
Graph Type:  ?
X Axis: 
Y Axis: 
Constraints ? Optional
Constraint #1 ?
Constraint #2 ?
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")
Graph Settings
Marker Type:   Size: 
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   
(Please be patient. It may take a while to get the data.)
Then set the File Type: (File Type information)
or view the URL:
(Documentation / Bypass this form ? )
    Click on the map to specify a new center point. ?
[The graph you specified. Please be patient.]


Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  cruise_id {
    String bcodmo_name "cruise_id";
    String description "cruise on which sample was collected";
    String long_name "Cruise Id";
    String units "text";
  BATS_bottle_ID {
    Int32 _FillValue 2147483647;
    Int32 actual_range 102830102, 500481408;
    String bcodmo_name "bottle";
    String description "unique identified given to each bottle sample collected on BATS cruises";
    String long_name "BATS Bottle ID";
    String units "text";
  cast {
    String bcodmo_name "cast";
    String description "CTD cast on which whole seawater was collected";
    String long_name "Cast";
    String units "text";
  depth_nom {
    String bcodmo_name "depth_n";
    String description "nominal depth; Surface or DCM (deep cholorophyll max)";
    String long_name "Depth";
    String standard_name "depth";
    String units "text";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 1.0, 88.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "bottle target trip depth in meters";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 21.6699, 31.6691;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -65.6664, -64.1614;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude; 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";
  SXRF_run {
    String bcodmo_name "sample";
    String description "SXRF run identifier";
    String long_name "SXRF Run";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String source_name "SXRF_run";
    String time_precision "1970-01";
    String units "text";
  mda_id {
    Int16 _FillValue 32767;
    Int16 actual_range 91, 444;
    String bcodmo_name "sample";
    String description "SXRF scan id within the run";
    String long_name "Mda Id";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "text";
  cell_Si {
    String bcodmo_name "trace_metal_conc";
    String description "total silicon content within each Synechococcus cell measured with SXRF";
    String long_name "Cell Si";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/C035/";
    String units "mol/cell";
  cell_P {
    String bcodmo_name "trace_element_conc";
    String description "total phosphorus content within each Synechococcus cell measured with SXRF";
    String long_name "Cell P";
    String units "mol/cell";
  cell_S {
    String bcodmo_name "trace_element_conc";
    String description "total sulfur content within each Synechococcus cell measured with SXRF";
    String long_name "Cell S";
    String units "mol/cell";
  cell_Si_to_P {
    Float32 _FillValue NaN;
    Float32 actual_range 0.05, 90.39;
    String bcodmo_name "mole_ratio";
    String description "derived mole ratio of silicon to phosphorous for each Synechococcus cell with determinable silicon and phosphorus content";
    String long_name "Mass Concentration Of Silicate In Sea Water";
    String units "dimensionless";
  cell_Si_to_S {
    Float32 _FillValue NaN;
    Float32 actual_range 0.05, 34.12;
    String bcodmo_name "mole_ratio";
    String description "derived mole ratio of silicon to sulfur for each Synechococcus cell with determinable silicon and sulfur content";
    String long_name "Mass Concentration Of Silicate In Sea Water";
    String units "dimensionless";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Samples were analyzed as described in Twining et al. (2015).
Bottle samples were collected during BATS cruises from surface level and the
deep chlorophyll max (DCM) using a CTD. The SXRF runs were done with a
Beamline 2-ID-E during three analytical runs in December 2012, April 2013, and
December 2013.";
    String awards_0_award_nid "544554";
    String awards_0_award_number "OCE-1131139";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1131139";
    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 awards_1_award_nid "544560";
    String awards_1_award_number "OCE-1335012";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1135012";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "David L. Garrison";
    String awards_1_program_manager_nid "50534";
    String awards_2_award_nid "544561";
    String awards_2_award_number "OCE-1131046";
    String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1131046";
    String awards_2_funder_name "NSF Division of Ocean Sciences";
    String awards_2_funding_acronym "NSF OCE";
    String awards_2_funding_source_nid "355";
    String awards_2_program_manager "David L. Garrison";
    String awards_2_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Cellular element quotas: Si in Synechococcus 
  P.I. Ben Twining 
  version 6 May 2016  
    N.B. bd = below detection";
    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 "2016-05-06T20:13:35Z";
    String date_modified "2018-11-16T20:49:08Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.651474";
    Float64 Easternmost_Easting -64.1614;
    Float64 geospatial_lat_max 31.6691;
    Float64 geospatial_lat_min 21.6699;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -64.1614;
    Float64 geospatial_lon_min -65.6664;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 88.0;
    Float64 geospatial_vertical_min 1.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-07-12T00:21:34Z (local files)
2020-07-12T00:21:34Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_644840.das";
    String infoUrl "https://www.bco-dmo.org/dataset/644840";
    String institution "BCO-DMO";
    String instruments_0_acronym "CTD";
    String instruments_0_dataset_instrument_nid "644996";
    String instruments_0_description "The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column.  The instrument is lowered via cable through the water column and permits scientists observe the physical properties in real time via a conducting cable connecting the CTD to a deck unit and computer on the ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or  radiometers.  It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast.  This instrument designation is used when specific make and model are not known.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
    String instruments_0_instrument_name "CTD profiler";
    String instruments_0_instrument_nid "417";
    String instruments_0_supplied_name "CTD";
    String instruments_1_acronym "XRF analyzer";
    String instruments_1_dataset_instrument_description 
"Abbreviation: SXRF
For this dataset the model used was: Beamline:2-ID-D
The instrument quantifies and maps elements (e.g. Si, Mn, Fe, Ni, S, P) in single cells.
Used in the following paper to look at trace elements in aquatic protists:
B. Twining, S. Baines, N. Fisher, J. Maser, S. Vogt, C. Jacobsen, A. Tovar-Sanchez, S. Sanudo-Wilhelmy; “Quantifying Trace Elements in Individual Aquatic Protist Cells with a Synchrotron X-ray Fluorescence Microprobe”, Analytical Chemistry 2003, 75, 3806-3816. DOI: 10.1021/ac034227z";
    String instruments_1_dataset_instrument_nid "647671";
    String instruments_1_description "Instruments that identify and quantify the elemental constituents of a sample from the spectrum of electromagnetic radiation emitted by the atoms in the sample when excited by X-ray radiation.";
    String instruments_1_instrument_name "X-ray fluorescence analyzer";
    String instruments_1_instrument_nid "648910";
    String instruments_1_supplied_name "Synchrotron X-ray Fluorescence Microprobe";
    String keywords "bats, BATS_bottle_ID, bco, bco-dmo, biological, bottle, cast, cell, cell_P, cell_S, cell_Si, cell_Si_to_P, cell_Si_to_S, chemical, chemistry, concentration, cruise, cruise_id, data, dataset, depth, depth_nom, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Silicate, erddap, latitude, longitude, management, mass, mass_concentration_of_silicate_in_sea_water, mda, mda_id, ocean, oceanography, oceans, office, preliminary, run, science, sea, seawater, silicate, sxrf, time, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/644840/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/644840";
    Float64 Northernmost_Northing 31.6691;
    String param_mapping "{'644840': {'lat': 'master - latitude', 'depth': 'flag - depth', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/644840/parameters";
    String people_0_affiliation "Bigelow Laboratory for Ocean Sciences";
    String people_0_person_name "Benjamin Twining";
    String people_0_person_nid "51087";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Bigelow Laboratory for Ocean Sciences";
    String people_1_person_name "Daniel Ohnemus";
    String people_1_person_nid "640096";
    String people_1_role "Contact";
    String people_1_role_type "related";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Ms Dicky Allison";
    String people_2_person_nid "50382";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Amber York";
    String people_3_person_nid "643627";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Si_in_Syn";
    String projects_0_acronym "Si_in_Syn";
    String projects_0_description 
"Extracted from the NSF award abstract:
INTELECTUAL MERIT: The investigators will follow-up on their discovery of significant accumulation of silicon by marine picocyanobacteria of the genus Synechococcus to assess the contribution of these organisms to the cycling of biogenic silica in the ocean. Oceanographers have long assumed that diatoms are the dominant marine organisms controlling the cycling of silica in the ocean. Recently, however, single-cell analyses of picocyanobacterial cells from field samples surprisingly revealed the presence of substantial amounts of silicon within Synechococcus. The contribution of Synechococcus to biogenic silica often rivaled that of living diatoms in the two systems examined. Moreover, size fractionation of biogenic silica indicates that up to 25% of biogenic silica can exist in the picoplanktonic size fraction. Given that picocyanobacteria dominate phytoplankton biomass and primary production over much of the world's ocean, these findings raise significant questions about the factors controlling the marine silica cycle globally, as well as the proper interpretation of biogenic silica measurements, Si:N ratios in particulate matter, and ratios of silicate and nitrate depletion. It also suggests that picocyanobacterial populations may be subject to previously unknown constraints on their productivity.
The project will have both laboratory and field components. Because cellular Si varies substantially among the field-collected samples and laboratory strains so far analyzed, the laboratory component will document variability in Si uptake and cellular Si concentrations, while determining what role physiological and phylogenetic factors play in this variability. The investigators will use strains of Synechococcus for which there are already genome sequences. Laboratory experiments will 1) use 32Si radiotracer uptake experiments to assess the degree of variability in Si content and Si uptake kinetics among strains of Synechococcus acclimated to different levels of silicate, 2) characterize the intracellular distribution and chemistry of silicon within cells using fractionation techniques, density centrifugation, electron microscopy and x-ray absorption spectroscopy, and 3) use bioinformatic analyses of published genomes to determine whether uptake of Si can be predicted based on phylogenetic relationships, to identify candidate genes involved in cyanobacterial Si metabolism, and to develop probes for community structure that can be related to cellular Si content. Field work at the Bermuda Atlantic Time Series (BATS) site will assess the contribution of Synechococcus and diatoms to total biogenic silica in surface waters at times of the year when the former are typically dominant. Field measurements will include size fractionation of biogenic silica biomass and Si uptake, and synchrotron-based x-ray fluorescence microscopy, and the phylogenetic composition of the Synechococcus assemblage.
BROADER IMPACTS: This project has the potential to drive a major paradigm shift in our understanding of the marine silicon cycle. In addition, one PhD student will be trained at Stony Brook. Each PI will provide research experience to a number of undergraduates working on original research projects for credit, as a part of an REU program or as the basis for undergraduate theses. Stony Brook research programs for undergraduates are supported with summer research money from the Undergraduate Research and Creative Activities (URECA) program, and draw on its very diverse student body. The investigators will also engage promising high school level students through several residential programs that the PIs have been a part of in the past. These include the BLOOM program at Bigelow and the Simons Summer Research Fellowship Program at Stony Brook. The PI has continuing relationship with a regional high school (Brentwood) with a high proportion of underrepresented minorities. PI Twining is involved in the Caf� Scientifique program at Bigelow. Baines will engage in similar outreach through the Center for Science and Mathematics Education (CESAME) sponsored Open Science Nights. Finally, PI Baines will cooperate with CESAMEs teacher education programs, with the aim of incorporating biological oceanography into K-12 curricula. PIs Krause and Brzezinski will incorporate aspects of phytoplankton ecology into UCSB's Oceans to Classroom Program that brings marine research at UCSB to life for over 18,000 K-12 students each year.";
    String projects_0_end_date "2015-12";
    String projects_0_geolocation "Samples collected in western North Atlantic Ocean between Puerto Rico, Bermuda, and Gulf of Maine.";
    String projects_0_name "Understanding the Role of Picocyanobacteria in the Marine Silicate Cycle";
    String projects_0_project_nid "544555";
    String projects_0_start_date "2012-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 21.6699;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary 
"Field work at the Bermuda Atlantic Time Series (BATS) site was done to assess
the contribution of Synechococcus and diatoms to total biogenic silica in
surface waters. The data include information about the elemental content
(Silicon, Phosphorus, and Sulfur) of Synechococcus cells as measured by
synchrotron-based x-ray fluorescence (SBXF) microscopy.\\u00a0 Derived mole
ratios (Si:P, and Si:S) are also provided.
Twining, B. S., Rauschenberg, S., Morton, P. L., & Vogt, S. (2015). Metal
contents of phytoplankton and labile particulate material in the North
Atlantic Ocean. Progress in Oceanography, 137, 261\\u2013283.
DMO notes:
  * Changed formatting of lat/lon to 4 decimal places from 5.
  * Elemental content values rounded to two decimal places from 15.";
    String title "Element quotas of individual Synechococcus cells collected during Bermuda Atlantic Time-series Study (BATS) cruises aboard the R/V Atlantic Explorer between dates 2012-07-11 and 2013-10-13 (Si_in_Syn project)";
    String version "1";
    Float64 Westernmost_Easting -65.6664;
    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
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.

ERDDAP, Version 2.02
Disclaimers | Privacy Policy | Contact