Accessing BCO-DMO data
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BCO-DMO ERDDAP
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| Dataset Title: | Size and chemical responses of two dinoflagellate species used in natural high light exposure experiments (Protist Signaling project) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_723277) |
| Information: | Summary
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| ISO 19115
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Attributes {
s {
Experiment_ID {
String bcodmo_name "exp_id";
String description "Experiment ID number";
String long_name "Experiment ID";
String units "unitless";
}
time {
String _CoordinateAxisType "Time";
Float64 actual_range 1.4369184e+9, 1.4418432e+9;
String axis "T";
String bcodmo_name "date";
String description "Experiment date; YYYY/MM/DD";
String ioos_category "Time";
String long_name "Experiment Date";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
String source_name "Experiment_Date";
String standard_name "time";
String time_origin "01-JAN-1970 00:00:00";
String time_precision "1970-01-01";
String units "seconds since 1970-01-01T00:00:00Z";
}
Dinoflagellate_species {
String bcodmo_name "species";
String description "Species of sample";
String long_name "Dinoflagellate Species";
String units "unitless";
}
Total_PAR_during_exposure_treatment {
Float32 _FillValue NaN;
Float32 actual_range 0.004, 9.897;
String bcodmo_name "PAR";
String description "Total dose of photosynthetically active radiation received during light exposure treatment";
String long_name "Total PAR During Exposure Treatment";
String units "mol photons m^-2";
}
Sampling_timepoint {
String bcodmo_name "unknown";
String description "Time sample was taken";
String long_name "Sampling Timepoint";
String units "unitless";
}
Replicate_cell_counts {
Int32 _FillValue 2147483647;
Int32 actual_range 1603, 34083;
String bcodmo_name "cell_concentration";
String description "Cell concentration in seawater media";
String long_name "Replicate Cell Counts";
String units "cells ml-1";
}
Replicate_cell_volume {
Float32 _FillValue NaN;
Float32 actual_range 119.98, 23641.0;
String bcodmo_name "volume";
String description "Volume of individual dinoflagellate cells";
String long_name "Replicate Cell Volume";
String units "um^3";
}
Replicate_determinations_chlorophyll_a {
Float32 _FillValue NaN;
Float32 actual_range 0.22, 42.73;
String bcodmo_name "chlorophyll a";
Float64 colorBarMaximum 30.0;
Float64 colorBarMinimum 0.03;
String colorBarScale "Log";
String description "Chlorophyll-a content of cells";
String long_name "Concentration Of Chlorophyll In Sea Water";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
String units "pg cell-1";
}
Replicate_determinations_chlorophyll_a_per_unit_cell_volume {
Float32 _FillValue NaN;
Float32 actual_range 1314.94, 8746.33;
String bcodmo_name "chlorophyll a";
Float64 colorBarMaximum 30.0;
Float64 colorBarMinimum 0.03;
String colorBarScale "Log";
String description "Intracellular concentration of chlorophyll-a";
String long_name "Concentration Of Chlorophyll In Sea Water";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
String units "mg L-1";
}
Replicate_determinations_particulate_DMSP_fmolcell1 {
Float32 _FillValue NaN;
Float32 actual_range 10.52, 3986.6;
String bcodmo_name "dimethylsulphoniopropionate";
String description "Dimethylsulfoniopropionate content of cells";
String long_name "Replicate Determinations Particulate DMSP Fmolcell1";
String units "fmol cell-1";
}
Replicate_determinations_particulate_DMSP_mmolL_cellvol1 {
Float32 _FillValue NaN;
Float32 actual_range 71.34, 199.38;
String bcodmo_name "dimethylsulphoniopropionate";
String description "Intracellular concentration of dimethylsulfoniopropionate";
String long_name "Replicate Determinations Particulate DMSP Mmol L Cellvol1";
String units "mmol L cell vol-1";
}
Replicate_determinations_dissolved_DMSP_nmolL1 {
Float32 _FillValue NaN;
Float32 actual_range 7.11, 1037.85;
String bcodmo_name "dimethylsulphoniopropionate";
String description "Concentration of dimethylsulfoniopropionate dissolved in seawater medium normalized to cell concentration in medium";
String long_name "Replicate Determinations Dissolved DMSP Nmol L1";
String units "nmol L-1";
}
Replicate_determinations_dissolved_DMSP_fmolcell1 {
Float32 _FillValue NaN;
Float32 actual_range 0.27, 601.65;
String bcodmo_name "dimethylsulphoniopropionate";
String description "Concentration of dimethylsulfoniopropionate dissolved in seawater medium normalized to cell concentration in medium";
String long_name "Replicate Determinations Dissolved DMSP Fmolcell1";
String units "fmol cell-1";
}
Replicate_determinations_total_DMSP {
Float32 _FillValue NaN;
Float32 actual_range 0.01, 9.28;
String bcodmo_name "dimethylsulphoniopropionate";
String description "Concentration of dissolved plus particulate dimethylsulfoniopropionate";
String long_name "Replicate Determinations Total DMSP";
String units "umol L-1";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"Dinoflagellate culturing:\\u00a0Alexandrium fundyense (strain CCMP 1911) was
obtained from the National Center for Marine Algae and Microbiota (NCMA). The
strain was originally isolated from Sequim Bay, Washington, USA. Heterocapsa
rotundata (strain K-0483), obtained from the Scandanavian Culture Collection
of Algae and Protozoa, was isolated from the southern Kattegat Sea near
Denmark. Dinoflagellate cultures were maintained in f/2 medium without added
silicate at 15\\u00b0C under a 12L:12D light cycle and transferred every two to
three weeks into new media. Growth irradiance for A. fundyense was 53
\\u00b5mol photons m-2 s-1; growth irradiance for H. rotundata was 12 \\u00b5mol
photons m-2 s-1.
Cell concentration and cell volume: Cell concentration (cells mL-1) and cell
volume (\\u00b5m3 cell-1) estimates for H. rotundata were obtained from live
samples measured with a Beckman Coulter Z2 Particle Count and Size Analyzer
with Z2 AccuComp software. For A. fundyense, samples were preserved in acid
Lugol\\u2019s solution (final concentration 2%). Cells were counted in a 1 ml
Sedgewick Rafter chamber using light microscopy; cell volume was estimated
from length and width of cells (n = 42 or 83 cells per sample) measured with
Leica Application Suite X image analysis software and assuming cell shape was
approximated by an oblate ellipsoid.
Chlorophyll-a: Chl-a concentrations were measured by filtering samples through
0.7 \\u00b5m effective pore size 25 mm glass fiber filters. Pigments were then
extracted in 90% acetone for 24 h (dark, -20\\u00b0C) and fluorescence was
measured on a Turner 10-AU fluorometer using the acidification method.
Concentrations are reported per cell and per unit cell volume.
Dissolved and particulate dimethylsulfoniopropionate (DMSP):\\u00a0 DMSP
samples (4 ml) were gravity-filtered through precombusted 0.7 \\u00b5m
effective pore size 25 mm glass fiber filters so as not to rupture the cells.
For measurement of particulate (intracellular) DMSP (DMSPp), filters were
placed into sealed 20-ml glass vials containing 3 ml of 5 N NaOH. For
measurement of DMSP in the dissolved (extracellular) phase (DMSPd), the first
4.5 mL of each sample\\u2019s filtrate were caught in a 5 ml polystyrene
culture tube, which was capped and stored at -80\\u00b0C. Later, DMSPd samples
were thawed and sparged with N2 gas for 1 min to remove any dimethyl sulfide
(DMS) already present. Each sparged sample (4 ml) was then dispensed into a
20-ml vial containing 1 ml of 5 N NaOH, and sealed. Upon being sealed,
prepared vials for either analysis were allowed to equilibrate for at least 24
h, allowing for the 1:1 conversion of DMSP to gaseous DMS, detectable via gas
chromatography. Standards for DMSPp were prepared from pre-diluted DMSP
solutions at the same time that samples were filtered and sealed into vials,
while DMSPd standards were made at the same time that samples were sparged and
sealed into vials. Samples and standards were analyzed using a Shimadzu Gas
Chromatograph 14-A equipped with a flame photometric detector and a Supelco
packed Chromosil 330 column. The chromatograph was operated isothermally at
90\\u00b0C with flow rates of hydrogen, air, and helium (carrier gas) at 50,
60, and 150 kPa, respectively. DMSPp samples and standards were measured via
direct injection while DMSPd samples and standards were measured with a
headspace sweep (He flow rate 40 kPa). DMSPp concentrations are reported per
cell and per unit cell volume. DMSPd concentrations are reported per cell and
per unit seawater volume.";
String awards_0_award_nid "614837";
String awards_0_award_number "OCE-1434842";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1434842";
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 cdm_data_type "Other";
String comment
"Dinoflagellate culturing
S. Strom, PI
Version 11 January 2018";
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 "2018-01-11T20:06:39Z";
String date_modified "2019-03-15T20:12:34Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.723277.1";
String history
"2024-04-26T07:07:07Z (local files)
2024-04-26T07:07:07Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_723277.html";
String infoUrl "https://www.bco-dmo.org/dataset/723277";
String institution "BCO-DMO";
String instruments_0_acronym "Gas Chromatograph";
String instruments_0_dataset_instrument_description "Used to analyze samples and standards";
String instruments_0_dataset_instrument_nid "723350";
String instruments_0_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_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB02/";
String instruments_0_instrument_name "Gas Chromatograph";
String instruments_0_instrument_nid "661";
String instruments_0_supplied_name "Shimadzu Gas Chromatograph";
String instruments_1_acronym "ACC";
String instruments_1_dataset_instrument_description "Used to determine cell concentration";
String instruments_1_dataset_instrument_nid "723351";
String instruments_1_description "Automated Cell Counter (ACC) - a tool used for counting live and/or dead cells in a culture. It can also be used to size particles.";
String instruments_1_instrument_name "Automated Cell Counter";
String instruments_1_instrument_nid "651528";
String instruments_1_supplied_name "Beckman Coulter Z2 Particle Count and Size Analyzer";
String keywords "available, bco, bco-dmo, biological, cell, cellvol1, chemical, chemistry, chlorophyll, concentration, concentration_of_chlorophyll_in_sea_water, counts, data, dataset, date, defense, determinations, dinoflagellate, Dinoflagellate_species, dissolved, dmo, dmsp, during, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, erddap, experiment, Experiment_ID, exposure, fmolcell1, management, meteorological, mmol, nmol, ocean, oceanography, oceans, office, par, particulate, photosynthetically, preliminary, program, radiation, replicate, Replicate_cell_counts, Replicate_cell_volume, Replicate_determinations_chlorophyll_a, Replicate_determinations_chlorophyll_a_per_unit_cell_volume, Replicate_determinations_dissolved_DMSP_fmolcell1, Replicate_determinations_dissolved_DMSP_nmolL1, Replicate_determinations_particulate_DMSP_fmolcell1, Replicate_determinations_particulate_DMSP_mmolL_cellvol1, Replicate_determinations_total_DMSP, sampling, Sampling_timepoint, satellite, science, sea, seawater, species, time, timepoint, total, Total_PAR_during_exposure_treatment, treatment, volume, water";
String keywords_vocabulary "GCMD Science Keywords";
String license "https://www.bco-dmo.org/dataset/723277/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/723277";
String param_mapping "{'723277': {'Experiment_Date': 'flag - time'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/723277/parameters";
String people_0_affiliation "Western Washington University - Shannon Point Marine Center";
String people_0_affiliation_acronym "SPMC";
String people_0_person_name "Suzanne Strom";
String people_0_person_nid "50471";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Woods Hole Oceanographic Institution";
String people_1_affiliation_acronym "WHOI BCO-DMO";
String people_1_person_name "Hannah Ake";
String people_1_person_nid "650173";
String people_1_role "BCO-DMO Data Manager";
String people_1_role_type "related";
String project "Protist signaling";
String projects_0_acronym "Protist signaling";
String projects_0_description
"Description from NSF proposal:
This proposal arises from the central premise that the oxidative stress response is an emergent property of phototrophic cellular systems, with implications for nearly every aspect of a phytoplankton cell’s life in the upper ocean. Oxidative stress (OS) arises from the uncompensated production of reactive oxygen species (ROS) within a cell, which can occur in response to a myriad of environmental stressors (e.g. nutrient limitation, temperature extremes, toxins, variable light exposure). In addition to the biochemical damage and physiological impairment that OS can cause, the phytoplankton OS response also includes increased net production and extracellular release of ROS, osmolytes, and other compounds that are known or suspected to be potent signals regulating protist behavior. We hypothesize that, through chemical signaling, oxidative stress acts to govern relationships among environmental variability, phytoplankton condition, and protist predation. Our proposed study of these integrated signaling and response processes has three overarching objectives: 1) Create and characterize oxidatively stressed phytoplankton. We will use light stress (variable exposure to visible light and UV) to create oxidatively stressed phytoplankton in the laboratory. Common coastal taxa with contrasting stress responses will be characterized using an array of fluorescent probes, biochemical measurements, and physiological assays. In addition, intracellular production and extracellular release of ROS and the associated chemical signal DMSP will be quantified. Use of Phaeodactylum tricornutum light stress mutants will add an independent means of connecting OS to signal production and predation response. 2) Examine protist predator responses to oxidatively stressed phytoplankton and associated chemical signals. Responses will be investigated by means of manipulation experiments and thorough characterization of associated signal chemistry. Assessment of predator response will be via predation rate measurements and population aggregation/dispersal behaviors in structured columns. 3) Investigate the prevalence of OS, its environmental correlates, and the microzooplankton predation response in the natural waters of a well-characterized local embayment. Application of ROS probes and OS assays to the natural environment and the design of OS manipulation experiments will be informed by the laboratory experiments using local protist species.
Our work will help to elucidate some of the multiple ways in which the OS response can affect phytoplankton fitness, contributing information that can be used to characterize the position of key coastal species along an OS response spectrum. Ultimately such information could be used in trait-based conceptual and numerical models in a manner analogous to cell size and other 'master traits'. Our research will also inform the relatively new and exciting field of chemical signaling in planktonic communities, exploring DMSP- and ROS-based signaling between two of the most significant groups in the plankton, the eukaryotic phytoplankton and their protist predators. Finally, findings will help elucidate the links between environmental stress, phytoplankton response, and predation in planktonic ecosystems. These links relate to central issues in biological oceanography, including the predator-prey interactions that influence bloom demise, and the mechanisms by which protists feed selectively and thereby structure prey communities. The proposed research is a cross-cutting endeavor that unites subjects usually studied in isolation through a novel conceptual framework. Thus the findings have the potential to generate broadly applicable new insights into the ecological and evolutionary regulation of this key trophic link in planktonic food webs.";
String projects_0_end_date "2017-08";
String projects_0_geolocation "Salish Sea: 48.5, -122.75";
String projects_0_name "Environmental stress and signaling based on reactive oxygen species among planktonic protists";
String projects_0_project_nid "614838";
String projects_0_start_date "2014-09";
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 summary "Size and chemical responses of two dinoflagellate species used in natural high light exposure experiments (Protist Signaling project)";
String time_coverage_end "2015-09-10";
String time_coverage_start "2015-07-15";
String title "Size and chemical responses of two dinoflagellate species used in natural high light exposure experiments (Protist Signaling project)";
String version "1";
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.