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

ERDDAP > tabledap > Data Access Form ?

Dataset Title:  Water column phosphate data from RV/Atlantic Explorer AE1812, May 2018 Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_762824)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   Maximum ?
 CTD_Cast (unitless) ?          2    53
 Station (unitless) ?          1    21
 time (Date, UTC) ?          2018-05-02    2018-05-15
  < slider >
 latitude (degrees_north) ?          31.67    41.19
  < slider >
 longitude (degrees_east) ?          -70.97    -63.48
  < slider >
 depth (m) ?          4.0    173.0
  < slider >
 MAGIC_SRP (nmol per liter) ?          "1.85"    "bdl"
 TPP (nmol per liter) ?          5.85    582.0
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.Hover here to see a list of options. Click on an option to select it.")

File type: (more info)

(Documentation / Bypass this form ? )
(Please be patient. It may take a while to get the data.)


The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  CTD_Cast {
    Byte _FillValue 127;
    Byte actual_range 2, 53;
    String bcodmo_name "cast";
    String description "Numeric identifier for the CTD cast where the data was collected.";
    String long_name "CTD Cast";
    String units "unitless";
  Station {
    Byte _FillValue 127;
    Byte actual_range 1, 21;
    String bcodmo_name "station";
    String description "Numeric identifier for the station where the data was collected.";
    String long_name "Station";
    String units "unitless";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.5252192e+9, 1.5263424e+9;
    String axis "T";
    String bcodmo_name "date_utc";
    String description "UTC Sampling date formatted as yyyy-mm-dd.";
    String ioos_category "Time";
    String long_name "Date";
    String source_name "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";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 31.67, 41.19;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude of sampling. Positiv evalues indicate North.";
    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 -70.97, -63.48;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude of sampling. Negative values indicate West.";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "Long";
    String standard_name "longitude";
    String units "degrees_east";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 4.0, 173.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth at which the 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";
    String bcodmo_name "PO4";
    String description "Soluble reactive phosphorus measured by magnesium induced co-precipitation.";
    String long_name "MAGIC SRP";
    String units "nmol per liter";
  TPP {
    Float32 _FillValue NaN;
    Float32 actual_range 5.85, 582.0;
    String bcodmo_name "Total Particulate Phosphorus";
    String description "Total particulate phosphorus.";
    String long_name "TPP";
    String units "nmol per liter";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"MAGIC Soluble reactive phosphorus (SRP) concentrations.\\u00a0 SRP (i.e.
phosphate) was determined in seawater samples (done in triplicate) and
incubations using MAGnesium Induced Coprecipitation (MAGIC) as described by
Karl and Tien (1992).\\u00a0
Total particulate phosphorus (TTP) concentrations. TPP was determined in
seawater samples using a wet chemical oxidation method using potassium
persulfate as described in Suzumura (2008). Briefly, 1 to 2 liters of seawater
were filtered onto 47 mm 0.2 \\u00b5m pore size polyvinylidene fluoride
membranes (Millipore) and frozen (-80\\u00b0C) until analysis. One fourth of
these filters were cut with clean stainless-steel scissors and placed in 8 mL
glass vials for oxidation. 2 mL of 5% (0.19 M) persulfate was added to each
vial and the samples were then autoclaved for 30 minutes at 120\\u00b0C. To
remove any residual material, the samples were filtered through 0.45 \\u00b5m
syringe filters (Millipore Millex-HV). The persulfate was shown to inhibit
color development when greater than 2%, therefore, the samples were diluted to
0.5% (0.019 M). As with the SRP samples, the TPP samples were analyzed via the
molybdenum blue method using a spectrophotometer (Thermo).";
    String awards_0_award_nid "704767";
    String awards_0_award_number "OCE-1558490";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1558490";
    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 "704773";
    String awards_1_award_number "OCE-1558506";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1558506";
    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 "746564";
    String awards_2_award_number "OCE-1536346";
    String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1536346";
    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 "Henrietta N Edmonds";
    String awards_2_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
"Water column phosphate data 
   from RV/Atlantic Explorer AE1812, May 2018 
   PI: T. Rynearson (URI) 
   version date: 2019-03-20";
    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 "2019-03-20T20:38:20Z";
    String date_modified "2019-03-21T21:09:18Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.762824.1";
    Float64 Easternmost_Easting -63.48;
    Float64 geospatial_lat_max 41.19;
    Float64 geospatial_lat_min 31.67;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -63.48;
    Float64 geospatial_lon_min -70.97;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 173.0;
    Float64 geospatial_vertical_min 4.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-06-02T07:34:34Z (local files)
2020-06-02T07:34:34Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_762824.html";
    String infoUrl "https://www.bco-dmo.org/dataset/762824";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_nid "762832";
    String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends.  The bottles can be attached individually on a hydrowire or deployed in 12, 24 or 36 bottle Rosette systems mounted on a frame and combined with a CTD.  Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
    String instruments_0_instrument_name "Niskin bottle";
    String instruments_0_instrument_nid "413";
    String instruments_1_acronym "CTD";
    String instruments_1_dataset_instrument_nid "762831";
    String instruments_1_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_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
    String instruments_1_instrument_name "CTD profiler";
    String instruments_1_instrument_nid "417";
    String instruments_2_acronym "Sed Trap - Part Int";
    String instruments_2_dataset_instrument_description 
"\"Based on the design of a closing plankton net capable�of collecting large amounts (~1 g) of very fresh sinking particulate material in short time periods (24-36 h) to�facilitate microbial decomposition experiment.\" (Peterson et al, 2005)
    String instruments_2_dataset_instrument_nid "762833";
    String instruments_2_description "A Particle Interceptor Trap is a prototype sediment trap designed in the mid 1990s to segregate 'swimmers' from sinking particulate material sampled from the water column. The prototype trap used 'segregation plates' to deflect and segregate 'swimmers' while a series of funnels collected sinking particles in a chamber (see Dennis A. Hansell and Jan A. Newton. September 1994. Design and Evaluation of a \"Swimmer\"-Segregating Particle Interceptor Trap, Limnology and Oceanography, Vol. 39, No. 6, pp. 1487-1495).";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/33/";
    String instruments_2_instrument_name "Sediment Trap - Particle Interceptor";
    String instruments_2_instrument_nid "550";
    String instruments_2_supplied_name "free-floating NetTrap";
    String instruments_3_acronym "Spectrophotometer";
    String instruments_3_dataset_instrument_description "Used to measure total particulate phosphate concentrations";
    String instruments_3_dataset_instrument_nid "762838";
    String instruments_3_description "An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples.";
    String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB20/";
    String instruments_3_instrument_name "Spectrophotometer";
    String instruments_3_instrument_nid "707";
    String instruments_3_supplied_name "spectrophotometer (Thermo)";
    String instruments_4_dataset_instrument_nid "762834";
    String instruments_4_description "A device mounted on a ship that holds water samples under conditions of controlled temperature or controlled temperature and illumination.";
    String instruments_4_instrument_name "Shipboard Incubator";
    String instruments_4_instrument_nid "629001";
    String instruments_5_dataset_instrument_description "Used to collect precipitate for�soluble reactive phosphorus (SRP) measurements.";
    String instruments_5_dataset_instrument_nid "762848";
    String instruments_5_description "A machine with a rapidly rotating container that applies centrifugal force to its contents, typically to separate fluids of different densities (e.g., cream from milk) or liquids from solids.";
    String instruments_5_instrument_name "Centrifuge";
    String instruments_5_instrument_nid "629890";
    String keywords "bco, bco-dmo, biological, cast, chemical, conductivity, ctd, CTD_Cast, data, dataset, date, depth, dmo, erddap, latitude, longitude, magic, MAGIC_SRP, management, oceanography, office, preliminary, sonde, srp, station, temperature, time, tpp";
    String license "https://www.bco-dmo.org/dataset/762824/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/762824";
    Float64 Northernmost_Northing 41.19;
    String param_mapping "{'762824': {'Date': 'flag - time', 'Lat': 'master - latitude', 'Depth': 'master - depth', 'Long': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/762824/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Benjamin A.S. Van Mooy";
    String people_0_person_nid "50975";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Rhode Island";
    String people_1_affiliation_acronym "URI-GSO";
    String people_1_person_name "Tatiana Rynearson";
    String people_1_person_nid "511706";
    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 "Nancy Copley";
    String people_2_person_nid "50396";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "North Atlantic Diatoms,Phosphorus Redox Cycling";
    String projects_0_acronym "North Atlantic Diatoms";
    String projects_0_description 
"NSF abstract:
About half of photosynthesis on earth is generated by marine phytoplankton, single celled organisms that drift with tides and currents. Within the phytoplankton, the diatoms conduct nearly half of this photosynthesis, exerting profound control over global carbon cycling. Despite their importance, there are surprisingly fundamental gaps in understanding how diatoms function in their natural environment, in part because methods to assess in situ physiology are lacking. This project focuses on the application of a powerful new approach, called Quantitative Metabolic Fingerprinting (QMF), to address this knowledge gap and examine species-specific physiology in the field. The project will provide transformative insights into how ocean geochemistry controls the distribution of diatoms, the metabolic responses of individual diatom species, and how metabolic potential is partitioned between diatom species, thus providing new insights into the structure and function of marine systems. The overarching goal is to examine how diatom species respond to changes in biogeochemistry across marine provinces, from the coast to the open ocean, by following shifts in diatom physiology using QMF. This research is critical to understand future changes in oceanic phytoplankton in response to climate and environmental change. Furthermore, activities on this project will include supporting a graduate student and postdoctoral fellow and delivering the Artistic Oceanographer Program (AOP) to diverse middle school age children and teachers in the NYC metropolitan area and to middle-school girls in the Girl Scouts of RI, reaching an anticipated 60 children and 30 teachers annually. The programs will foster multidisciplinary hands-on learning and will directly impact STEM education at a critical point in the pipeline by targeting diverse middle-school aged groups in both NY and RI.
In laboratory studies with cultured isolates, there are profound differences among diatom species' responses to nutrient limitation. Thus, it is likely that different species contribute differently to nutrient uptake, carbon flux and burial. However, marine ecosystem models often rely on physiological attributes drawn from just one species and apply those attributes globally (e.g. coastal species used to model open ocean dynamics) or choose a single average value to represent all species across the world's oceans. In part, this is due to a relatively poor understanding of diatom physiological ecology and a limited tool set for assessing in situ diatom physiological ecology. This research project will address this specific challenge by explicitly tracking metabolic pathways, measuring their regulation and determining their taxonomic distribution in a suite of environmentally significant diatoms using a state of the art, species-specific approach. A research expedition is set in the North Atlantic, a system that plays a major role in carbon cycling. Starting with a New England coastal shelf site, samples will be collected from the coast where diatoms thrive, to the open ocean and a site of a long term ocean time series station (the Bermuda Atlantic Time Series) where diatom growth is muted by nutrient limitation. This research takes advantage of new ocean observatories initiative (OOI) and time series information. Through the research expedition and downstream laboratory experiments, the molecular pathways of nutrient metabolism and related gene expression in a suite of environmentally significant diatoms will be identified. Data will be combined to predict major limiting factors and potentially important substrates for diatoms across marine provinces. Importantly, this integrated approach takes advantage of new advances in molecular and bioinformatics tools to examine in situ physiological ecology at the species-specific level, a key knowledge gap in the field.";
    String projects_0_end_date "2019-08";
    String projects_0_geolocation "North Atlantic";
    String projects_0_name "Collaborative Research: Defining the biogeochemical drivers of diatom physiological ecology in the North Atlantic";
    String projects_0_project_nid "704768";
    String projects_0_start_date "2016-09";
    String projects_1_acronym "Phosphorus Redox Cycling";
    String projects_1_description 
"NSF Award Abstract:
Redox Cycling of Phosphorus in the Western North Atlantic Ocean
Benjamin Van Mooy
ID: 1536346
Understanding controls on the growth of plankton in the upper ocean, which plays an essential role in the sequestration of carbon dioxide, is an important endeavor for chemical oceanography. Phosphorus is an essential element for marine plankton, and has been a research focus of chemical oceanography for nearly a century. Yet, phosphorus redox cycling rates are almost completely unknown throughout the ocean, and the specific molecular identities of the phosphonates, a form of phosphate, in seawater have defied elucidation. This project will explore and refine entirely new pathways for the biological cycling of phosphorus. This project will support teaching and learning by funding the PhD research of a graduate student, and through the continuation of conducting K-12 classroom laboratory modules and hosting 6-8th grade science fair participants in the investigator's lab.
Phosphorus has never been viewed by oceanographers as an element that actively undergoes chemical redox reactions in the water column, and it was believed to occur only in the +5 valence state, in compounds such as phosphate. However, over the last 17 years, numerous lines of geochemical and genomic information have emerged to show that phosphorus in the +3 valence state (P(+3)), particularly dissolved phosphonate compounds, may play a very important role within open ocean planktonic communities. This is particularly true in oligotrophic gyres such as the Sargasso Sea, where growth of phytoplankton can be limited by the scarcity of phosphate. To better understand these new data, the investigators will design and execute a research program that spans at-sea chemical oceanographic experimentation, state-of-the-art chromatography and mass spectrometry, and novel organic synthesis of 33P-labeled P(+3) compounds. Specifically, they will answer questions about rates of production and consumption of low molecular weight P(+3) compounds, the impact of phosphate availability on the production and consumption of P(+3) compounds, and the groups of phytoplankton that utilize low molecular weight P(+3) compounds. Results of this project have the potential to contribute to the transformation of our understanding of the marine phosphorus cycle.";
    String projects_1_end_date "2018-09";
    String projects_1_geolocation "western north Atlantic";
    String projects_1_name "Redox Cycling of Phosphorus in the Western North Atlantic Ocean";
    String projects_1_project_nid "746565";
    String projects_1_start_date "2015-10";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 31.67;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "This dataset includes water column phosphate data from RV/Atlantic Explorer AE1812, May 2018.";
    String time_coverage_end "2018-05-15";
    String time_coverage_start "2018-05-02";
    String title "Water column phosphate data from RV/Atlantic Explorer AE1812, May 2018";
    String version "1";
    Float64 Westernmost_Easting -70.97;
    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