Accessing BCO-DMO data
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BCO-DMO ERDDAP
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| Dataset Title: | [MUSiCC OC1504A - Bacteria Virus and Chlorophyll Containing Cell Abundance] - Abundance of bacteria viruses and chlorophyll containing cells collected from the R/V Oceanus OC1504A in the Oregon/California Coastal Upwelling Zone, between 34-44N and 120-124W during 2015 (Linking physiological and molecular aspects of diatom silicification in field populations) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_652223) |
| Information: | Summary
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| FGDC
| ISO 19115
| Metadata
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Attributes {
s {
cruise_id {
String bcodmo_name "cruise_id";
String description "The name of the cruise that collected these data.";
String long_name "Cruise Id";
String units "unitless";
}
station {
String bcodmo_name "station";
String description "consecutive station number";
String long_name "Station";
String units "unitless";
}
cast {
String bcodmo_name "cast";
String description "cast number";
String long_name "Cast";
String units "unitless";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 34.55467, 43.65434;
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 -124.48169, -120.81017;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "longitude";
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";
}
date_local {
String bcodmo_name "date_local";
String description "local date of cast; mm-bbb-yy";
String long_name "Date Local";
String units "unitless";
}
time_local {
String bcodmo_name "time_local";
String description "local time of cast; HH:MM";
String long_name "Time Local";
String units "unitless";
}
date_utc {
String bcodmo_name "date_utc";
String description "UTC date of cast; mm-bbb-yy";
String long_name "Date Utc";
String units "unitless";
}
time_utc {
String bcodmo_name "time_utc";
String description "UTC time of cast; HH:MM";
String long_name "Time Utc";
String units "unitless";
}
depth {
String _CoordinateAxisType "Height";
String _CoordinateZisPositive "down";
Float64 _FillValue NaN;
Float64 actual_range 1.0, 1200.0;
String axis "Z";
String bcodmo_name "depth";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "depth of sample collection";
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";
}
bacteria {
Float32 _FillValue NaN;
Float32 actual_range 930000.0, 6290000.0;
String bcodmo_name "abundance";
String description "bacteria-like particle abundance";
String long_name "Bacteria";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "bacteria per milliliter";
}
virus {
Float32 _FillValue NaN;
Float32 actual_range 2.45e+7, 3.11e+8;
String bcodmo_name "abundance";
String description "virus-like particle abundance (VLP)";
String long_name "Virus";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "VLP per milliliter";
}
chl_total {
Float32 _FillValue NaN;
Float32 actual_range 117.0, 12500.0;
String bcodmo_name "abundance";
String description "chlorophyll containing cells";
String long_name "Chl Total";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "cells per milliliter";
}
time {
String _CoordinateAxisType "Time";
Float64 actual_range 1.42949628e+9, 1.43049876e+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";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
String acquisition_description
"Environmental Sample Collection
1. Transfer 1 ml of whole seawater to a 2 ml cryovial.
2. Add 20 ul of 25% glutaraldehyde for a final concentration of 0.5%.
3. Incubate at 4 degrees celsius\\u00a0for 30 min.
4. Flash freeze in liquid N2\\u00a0and store at -80 degrees celsius.
Fluorescent DNA staining (for bacterial and viral abundances)
1. Thaw samples.
2. To 20 ul of sample, add 980 ul 1X TE buffer with SYBR Gold (see recipe below)\\u00a0
3. Heat to 80 degrees celsius\\u00a0for 10 min in the dark
4. Cool at RT for 5 min
5. Analyze via flow cytometry
Analysis (for bacterial and viral abundances)
Samples are analyzed on Influx Model 209S Mariner flow cytometer using BD
Software (BD Biosciences).
1. An initial Forward Scatter (FSC) vs Side Scatter (SSC) configuration is determined using Molecular Probes Flow Cytometry Sub-micron particles size reference kit (Cat#F13839) consisting of 0.02, 0.1, 0.5, 1.0 and 2.0 um fluorescent beads.
2. A gating hierarchy is established using both beads and previously determined virus and bacteria populations as\\u00a0reference\\u00a0(Sybr Gold Fluorescence versus SSC cytogram).
3. Samples are analyzed using a 488 nm laser for excitation and a minimum trigger threshold is established using 542/15 nm (SYBR Gold) emission.
Analysis (for\\u00a0chlorophyll containing\\u00a0cells)
Samples are analyzed on a BD Accuri C6. Fixed, frozen samples are thawed and
analyzed immediately.
1. An initial Forward Scatter (FSC) vs Side Scatter (SSC) configuration is determined using various sized fluorescent beads as reference points (1.0, 2.0, 3.0, 6.0 and 10 um).
2. Gating is established using both beads and previously determined phytoplankton populations as\\u00a0reference\\u00a0(Chlorophyll Fluorescence versus FSC cytogram).
3. Samples are analyzed using 488nm laser for excitation and the default BD Accuri threshold (80,000 RFU) on FSC is used.
TE buffer with SYBR Gold recipe
1X TE (for 100\\u00a0mls)
1 ml of 1M Tris, pH 8.0
1 ml of 0.5 mM EDTA
98\\u00a0mls\\u00a0MQ water
Store 4 degrees celsius
1X TE + SYBR Gold (for 10\\u00a0mls)
1. Filter 10\\u00a0mls\\u00a01 TE buffer, 0.22 um filter
2. 1:20,0000 dilution of SYBR Gold (Molecular Probes) stock (0.5 ul stock to 10\\u00a0mls\\u00a0TE buffer)";
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
"Bacteria and Virus Abundance
and Chlorophyll Containing Particles
K. Thamatrakoln and M. Brzezinski, PIs
Version 19 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 "2016-07-20T13:46:06Z";
String date_modified "2019-06-06T15:46:38Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.652223.1";
Float64 Easternmost_Easting -120.81017;
Float64 geospatial_lat_max 43.65434;
Float64 geospatial_lat_min 34.55467;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -120.81017;
Float64 geospatial_lon_min -124.48169;
String geospatial_lon_units "degrees_east";
Float64 geospatial_vertical_max 1200.0;
Float64 geospatial_vertical_min 1.0;
String geospatial_vertical_positive "down";
String geospatial_vertical_units "m";
String history
"2024-11-19T07:34:08Z (local files)
2024-11-19T07:34:08Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_652223.html";
String infoUrl "https://www.bco-dmo.org/dataset/652223";
String institution "BCO-DMO";
String instruments_0_acronym "Flow Cytometer";
String instruments_0_dataset_instrument_description "Samples were analyzed on flow cytometer using BD Software (BD Biosciences). Bacterial and viral abundances were analyzed on this flow cytometer.";
String instruments_0_dataset_instrument_nid "652272";
String instruments_0_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_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB37/";
String instruments_0_instrument_name "Flow Cytometer";
String instruments_0_instrument_nid "660";
String instruments_0_supplied_name "Influx Model 209S Mariner Flow Cytometer";
String instruments_1_acronym "Flow Cytometer";
String instruments_1_dataset_instrument_description "Chlorophyll containing cells analyzed on this flow cytometer.";
String instruments_1_dataset_instrument_nid "652273";
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 "BD Accuri C6";
String keywords "bacteria, bco, bco-dmo, biological, cast, chemical, chl, chl_total, chlorophyll, cruise, cruise_id, data, dataset, date, date_local, date_utc, depth, dmo, erddap, iso, latitude, local, longitude, management, oceanography, office, preliminary, station, time, time_local, time_utc, total, virus";
String license "https://www.bco-dmo.org/dataset/652223/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/652223";
Float64 Northernmost_Northing 43.65434;
String param_mapping "{'652223': {'lat': 'master - latitude', 'depth': 'flag - depth', 'lon': 'master - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/652223/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)";
Float64 Southernmost_Northing 34.55467;
String standard_name_vocabulary "CF Standard Name Table v55";
String subsetVariables "cruise_id";
String summary "Abundance of bacteria viruses and chlorophyll containing cells collected from the R/V Oceanus OC1504A in the Oregon/California Coastal Upwelling Zone, between 34-44N and 120-124W during 2015";
String time_coverage_end "2015-05-01T16:46:00Z";
String time_coverage_start "2015-04-20T02:18:00Z";
String title "[MUSiCC OC1504A - Bacteria Virus and Chlorophyll Containing Cell Abundance] - Abundance of bacteria viruses and chlorophyll containing cells collected from the R/V Oceanus OC1504A in the Oregon/California Coastal Upwelling Zone, between 34-44N and 120-124W during 2015 (Linking physiological and molecular aspects of diatom silicification in field populations)";
String version "1";
Float64 Westernmost_Easting -124.48169;
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
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.