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

ERDDAP > tabledap > Make A Graph ?

Dataset Title:  Photosynthetic data collected from the R/V Oceanus OC1504A in the Oregon/
California Coastal Upwelling Zone, between 34-44N and 120-124W in 2015.
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_652739)
Range: depth = 1.0 to 80.0m, time = 2015-04-20T03:43:15Z to 2015-05-01T11:08:20Z
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | 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: 
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 ? )
Time range:    |<   -       
[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 identification where samples where collected";
    String long_name "Cruise Id";
    String units "unitless";
  CTD {
    String bcodmo_name "cast";
    String description "CTD cast";
    String long_name "CTD";
    String units "unitless";
  date_local {
    String bcodmo_name "date_local";
    String description "local date of sample collection; mm/dd/yy";
    String long_name "Date Local";
    String units "unitless";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 1.0, 80.0;
    String axis "Z";
    String bcodmo_name "depth";
    String description "depth at which samples were collected";
    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";
  time_local {
    String bcodmo_name "time_local";
    String description "local time of sample collection; HH:MM:SSpp";
    String long_name "Time Local";
    String units "unitless";
  Fluor_min {
    Int16 _FillValue 32767;
    Int16 actual_range 20, 3165;
    String bcodmo_name "fluorescence";
    String description "minimal fluorescence yield corrected for background fluorescence. Fo";
    String long_name "Fluor Min";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
    String units "relative units";
  Fluor_max {
    Int16 _FillValue 32767;
    Int16 actual_range 36, 7528;
    String bcodmo_name "fluorescence";
    String description "maximal fluorescence yield corrected for background fluorescence. Fm";
    String long_name "Fluor Max";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
    String units "relative units";
  FvFm {
    Float32 _FillValue NaN;
    Float32 actual_range 0.3, 0.867;
    String bcodmo_name "Fv2Fm";
    String description "maximum quantum yield corrected for background fluorescence; Fv divided by Fm";
    String long_name "FV FM";
    String units "dimensionless";
  functional_absorption {
    Float32 _FillValue NaN;
    Float32 actual_range 0.443, 385.3;
    String bcodmo_name "unknown";
    String description "Functional absorption cross-section of photosystem II (measured using 450 nm excitation; units A2); sigma";
    String long_name "Functional Absorption";
    String units "unitless";
  connectivity_p {
    Float32 _FillValue NaN;
    Float32 actual_range 0.23, 0.46;
    String bcodmo_name "unknown";
    String description "connectivity factor defines the efficiency of exciton energy transfer between individual photosynthetic units; originally p";
    String long_name "Connectivity P";
    String units "unitless";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.429501395e+9, 1.4304785e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "DateTime (UTC) ISO formatted";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String source_name "ISO_DateTime_UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Photosynthetic parameters were measured using fast repetition rate fluorometry
on whole seawater collected by CTD. See reference below for details on data
    String awards_0_award_nid "558197";
    String awards_0_award_number "OCE-1333929";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1333929";
    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 "558203";
    String awards_1_award_number "OCE-1334387";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1334387";
    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 cdm_data_type "Other";
    String comment 
"Photosyntheticdata from OC1504a (MUSiCC) 
   K. Thamatrakoln and M. Brzezinski, PIs 
   Version 28 July 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 "2016-07-28T16:32:00Z";
    String date_modified "2019-06-05T20:06:35Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.652739.1";
    Float64 geospatial_vertical_max 80.0;
    Float64 geospatial_vertical_min 1.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2022-01-26T10:32:53Z (local files)
2022-01-26T10:32:53Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_652739.das";
    String infoUrl "https://www.bco-dmo.org/dataset/652739";
    String institution "BCO-DMO";
    String instruments_0_acronym "FRRf";
    String instruments_0_dataset_instrument_description "Photosynthetic parameters were measured.";
    String instruments_0_dataset_instrument_nid "652815";
    String instruments_0_description "An FRRf is used for measuring the fluorescence of a sample of phytoplankton photosynthetic competency (Fv/Fm).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/113/";
    String instruments_0_instrument_name "Fast Repetition Rate Fluorometer";
    String instruments_0_instrument_nid "426";
    String instruments_0_supplied_name "Fast Repetition Rate Fluorometer";
    String keywords "absorption, bco, bco-dmo, biological, chemical, conductivity, connectivity, connectivity_p, cruise, cruise_id, ctd, data, dataset, date, date_local, depth, depth2, dmo, erddap, fluor, Fluor_max, Fluor_min, functional, functional_absorption, FvFm, iso, local, management, max, min, oceanography, office, preliminary, sonde, temperature, time, time_local";
    String license "https://www.bco-dmo.org/dataset/652739/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/652739";
    String param_mapping "{'652739': {'depth': 'master - depth', 'ISO_DateTime_UTC': 'master - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/652739/parameters";
    String people_0_affiliation "Rutgers University";
    String people_0_affiliation_acronym "Rutgers IMCS";
    String people_0_person_name "Kimberlee Thamatrakoln";
    String people_0_person_nid "558200";
    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-LifeSci";
    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 "Rutgers University";
    String people_2_affiliation_acronym "Rutgers IMCS";
    String people_2_person_name "Kimberlee Thamatrakoln";
    String people_2_person_nid "558200";
    String people_2_role "Contact";
    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 "Hannah Ake";
    String people_3_person_nid "650173";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Diatom Silicification";
    String projects_0_acronym "Diatom Silicification";
    String projects_0_description 
"Description from NSF award abstract:
Diatoms, unicellular, eukaryotic photoautotrophs, are among the most ecologically successful and functionally diverse organisms in the ocean. In addition to contributing one-fifth of total global primary productivity, diatoms are also the largest group of silicifying organisms in the ocean. Thus, diatoms form a critical link between the carbon and silicon (Si) cycles. The goal of this project is to understand the molecular regulation of silicification processes in natural diatom populations to better understand the processes controlling diatom productivity in the sea. Through culture studies and two research cruises, this research will couple classical measurements of silicon uptake and silica production with molecular and biochemical analyses of Silicification-Related Gene (SiRG) and protein expression. The proposed cruise track off the West Coast of the US will target gradients in Si and iron (Fe) concentrations with the following goals: 1) Characterize the expression pattern of SiRGs, 2) Correlate SiRG expression patterns to Si concentrations, silicon uptake kinetics, and silica production rates, 3) Develop a method to normalize uptake kinetics and silica production to SiRG expression levels as a more accurate measure of diatom activity and growth, 4) Characterize the diel periodicity of silica production and SiRG expression.
It is estimated that diatoms process 240 Teramoles of biogenic silica each year and that each molecule of silicon is cycled through a diatom 39 times before being exported to the deep ocean. Decades of oceanographic and field research have provided detailed insight into the dynamics of silicon uptake and silica production in natural populations, but a molecular understanding of the factors that influence silicification processes is required for further understanding the regulation of silicon and carbon fluxes in the ocean. Characterizing the genetic potential for silicification will provide new information on the factors that regulate the distribution of diatoms and influence in situ rates of silicon uptake and silica production. This research is expected to provide significant information about the molecular regulation of silicification in natural populations and the physiological basis of Si limitation in the sea.";
    String projects_0_end_date "2016-08";
    String projects_0_geolocation "Oregon/California Coastal Upwelling Zone, between 34-44N and 120-124W";
    String projects_0_name "Linking physiological and molecular aspects of diatom silicification in field populations";
    String projects_0_project_nid "558198";
    String projects_0_start_date "2013-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "cruise_id";
    String summary "Photosynthetic data collected from the R/V Oceanus OC1504A in the Oregon/California Coastal Upwelling Zone, between 34-44N and 120-124W in 2015.";
    String time_coverage_end "2015-05-01T11:08:20Z";
    String time_coverage_start "2015-04-20T03:43:15Z";
    String title "Photosynthetic data collected from the R/V Oceanus OC1504A in the Oregon/California Coastal Upwelling Zone, between 34-44N and 120-124W in 2015.";
    String version "1";
    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