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| Dataset Title: | [IEP February and May 2017] - Nutrient and nitrate isotope data from the southern Benguela upwelling system from February to August 2017 (Investigation of mechanisms leading to seasonal hypoxia in the Southern Benguela Upwelling System) 
|
| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_811839) |
| Information: | Summary
| License
| FGDC
| ISO 19115
| Metadata
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Attributes {
s {
Cruise {
String bcodmo_name "Cruise Name";
String description "name of the cruise";
String long_name "Cruise";
String units "unitless";
}
Month {
String bcodmo_name "month";
String description "Month of observation in text";
String long_name "Month";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MNTHXXXX/";
String units "unitless";
}
Year {
Int16 _FillValue 32767;
Int16 actual_range 2017, 2017;
String bcodmo_name "year";
String description "year of observation in yyyy format";
String long_name "Year";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
String units "unitless";
}
Station_ID {
String bcodmo_name "station";
String description "identifier for the station";
String long_name "Station ID";
String units "unitless";
}
Monitoring_line {
String bcodmo_name "site_descrip";
String description "identifier for the mooring line";
String long_name "Monitoring Line";
String units "unitless";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range -34.5593, -29.3817;
String axis "Y";
String bcodmo_name "latitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "latitude with negative values indicating South";
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 14.1348, 18.28933333;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "longitude with positive values indicating West";
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";
}
depth {
String _CoordinateAxisType "Height";
String _CoordinateZisPositive "down";
Float64 _FillValue NaN;
Float64 actual_range 0.818, 1014.47;
String axis "Z";
String bcodmo_name "depth";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "water depth of observation";
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";
}
Temperature {
Float32 _FillValue NaN;
Float32 actual_range 3.2, 21.4;
String bcodmo_name "temperature";
String description "Temperature";
String long_name "Temperature";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
String units "degrees Celsius (C)";
}
Salinity {
Float32 _FillValue NaN;
Float32 actual_range 33.6, 35.6;
String bcodmo_name "sal";
Float64 colorBarMaximum 37.0;
Float64 colorBarMinimum 32.0;
String description "Salinity";
String long_name "Sea Water Practical Salinity";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
String units "psu";
}
Sigma_theta {
Float32 _FillValue NaN;
Float32 actual_range 24.8, 27.5;
String bcodmo_name "sigma_theta";
String description "sigma-theta";
String long_name "Sea Water Sigma Theta";
String units "kilograms per meter cubed (kg/m3)";
}
NO3_NO2 {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 42.0;
String bcodmo_name "NO3_NO2";
Float64 colorBarMaximum 50.0;
Float64 colorBarMinimum 0.0;
String description "[NO3-+NO2-]";
String long_name "Mole Concentration Of Nitrate In Sea Water";
String units "microMole (uM)";
}
NO3_NO2_Stdev {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 1.9;
String bcodmo_name "NO3_NO2";
Float64 colorBarMaximum 50.0;
Float64 colorBarMinimum 0.0;
String description "standard deviation of [NO3-+NO2-]";
String long_name "Mole Concentration Of Nitrate In Sea Water";
String units "micr";
}
NO2 {
Float32 _FillValue NaN;
Float32 actual_range -0.01, 1.8;
String bcodmo_name "NO2";
Float64 colorBarMaximum 1.0;
Float64 colorBarMinimum 0.0;
String description "NO2-";
String long_name "Mole Concentration Of Nitrite In Sea Water";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/NTRIAAZX/";
String units "microMole (uM)";
}
NO2_Stdev {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 0.3;
String bcodmo_name "NO2";
Float64 colorBarMaximum 1.0;
Float64 colorBarMinimum 0.0;
String description "standard deviation of NO2-";
String long_name "Mole Concentration Of Nitrite In Sea Water";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/NTRIAAZX/";
String units "microMole (uM)";
}
PO43 {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 3.7;
String bcodmo_name "PO4";
String description "PO43-";
String long_name "PO43";
String units "microMole (uM)";
}
PO43_Stdev {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 0.7;
String bcodmo_name "PO4";
String description "standard deviation of PO43-";
String long_name "PO43 Stdev";
String units "microMole (uM)";
}
O2 {
Float32 _FillValue NaN;
Float32 actual_range 2.6, 372.0;
String bcodmo_name "dissolved Oxygen";
String description "O2";
String long_name "O2";
String units "microMole (uM)";
}
AOU {
Float32 _FillValue NaN;
Float32 actual_range -111.5, 282.8;
String bcodmo_name "AOU";
String description "Apparent Oxygen Utilization (AOU)";
String long_name "AOU";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/DOXY";
String units "microMole (uM)";
}
N15_NO3 {
Float32 _FillValue NaN;
Float32 actual_range 5.4, 19.9;
String bcodmo_name "dN15_NO3";
Float64 colorBarMaximum 50.0;
Float64 colorBarMinimum 0.0;
String description "15N_NO3";
String long_name "Mole Concentration Of Nitrate In Sea Water";
String units "parts per thousand";
}
N15_stdev {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 0.4;
String bcodmo_name "unknown";
String description "standard deviation of δ15N";
String long_name "N15 Stdev";
String units "parts per thousand";
}
O18_NO3 {
Float32 _FillValue NaN;
Float32 actual_range 1.6, 12.4;
String bcodmo_name "d18O_NO3";
Float64 colorBarMaximum 50.0;
Float64 colorBarMinimum 0.0;
String description "18O_NO3";
String long_name "Mole Concentration Of Nitrate In Sea Water";
String units "parts per thousand";
}
O18_stdev {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 0.6;
String bcodmo_name "d18O_NO3";
String description "standard deviation of δ18O";
String long_name "O18 Stdev";
String units "parts per thousand";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
String acquisition_description
"The methods on how the samples were collected and processed for the attached
dataset can be found in the methodology section of Flynn et al. (2019).\\u00a0
Hydrographic measurements were made using a conductivity-temperature-depth
(CTD) profiler fitted with a temperature, salinity and oxygen sensor.\\u00a0
Nitrate+nitrite concentrations were measured following published auto-analysis
protocols (Diamond 1994; Grasshoff 1976), and nitrite and phosphate
concentrations were determined using benchtop colourimetric methods
(Strickland and Parsons 1968; Bendschneider and Robinson 1952; Parsons et al.
1984).\\u00a0
Nitrate N and O isotope ratios were measured using the \\u201cdenitrifier
method\\u201d (Sigman et al. 2001; Casciotti et al. 2002; McIlvin and Casciotti
2011).
Seawater samples were collected at discrete depths from the surface to the
seafloor using a tethered rosette holding twelve 6-L Niskin bottles. At each
CTD station, nutrient and nitrate isotope samples were collected filtered
(0.22 \\u00b5m PES membrane syringe filter) throughout the water column in 60
mL HDPE bottles. Each bottle was rinsed three times prior to being filled, and
then immediately frozen at -20\\u00b0C pending analysis. All nutrient samples
were analysed within a year from collection, and nitrate isotopes within 18
months of collection.\\u00a0";
String awards_0_award_nid "809301";
String awards_0_award_number "OCE-1924270";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1924270";
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 "Dr Simone Metz";
String awards_0_program_manager_nid "51479";
String cdm_data_type "Other";
String comment
"Nutrient and nitrate isotope data from the southern Benguela upwelling system
PI: Julie Granger
Version: 2020-05-19";
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 dataset_current_state "Final and no updates";
String date_created "2020-05-19T18:41:00Z";
String date_modified "2020-05-20T17:01:02Z";
String defaultDataQuery "&time<now";
String doi "10.26008/1912/bco-dmo.811839.1";
Float64 Easternmost_Easting 18.28933333;
Float64 geospatial_lat_max -29.3817;
Float64 geospatial_lat_min -34.5593;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max 18.28933333;
Float64 geospatial_lon_min 14.1348;
String geospatial_lon_units "degrees_east";
Float64 geospatial_vertical_max 1014.47;
Float64 geospatial_vertical_min 0.818;
String geospatial_vertical_positive "down";
String geospatial_vertical_units "m";
String history
"2024-12-22T10:54:38Z (local files)
2024-12-22T10:54:38Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_811839.html";
String infoUrl "https://www.bco-dmo.org/dataset/811839";
String institution "BCO-DMO";
String instruments_0_acronym "CTD";
String instruments_0_dataset_instrument_description "Hydrographic measurements were made using a conductivity-temperature-depth (CTD) profiler fitted with a temperature, salinity and oxygen sensor.";
String instruments_0_dataset_instrument_nid "811851";
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 profiler";
String instruments_1_acronym "IR Mass Spec";
String instruments_1_dataset_instrument_description "The N and O isotope ratios of the N2O gas were analysed using a Delta V Advantage continuous flow isotope ratio mass spectrometer interfaced with an online N2O extraction and purification system.";
String instruments_1_dataset_instrument_nid "811850";
String instruments_1_description "The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer).";
String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
String instruments_1_instrument_name "Isotope-ratio Mass Spectrometer";
String instruments_1_instrument_nid "469";
String instruments_1_supplied_name "Delta V Advantage continuous flow isotope ratio mass spectrometer";
String instruments_2_acronym "FIA";
String instruments_2_dataset_instrument_description "Nitrate+nitrite concentrations were measured using a Lachat QuickChem flow injection analysis platform in a configuration with a detection limit of 0.1 µM.";
String instruments_2_dataset_instrument_nid "811848";
String instruments_2_description "An instrument that performs flow injection analysis. Flow injection analysis (FIA) is an approach to chemical analysis that is accomplished by injecting a plug of sample into a flowing carrier stream. FIA is an automated method in which a sample is injected into a continuous flow of a carrier solution that mixes with other continuously flowing solutions before reaching a detector. Precision is dramatically increased when FIA is used instead of manual injections and as a result very specific FIA systems have been developed for a wide array of analytical techniques.";
String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB36/";
String instruments_2_instrument_name "Flow Injection Analyzer";
String instruments_2_instrument_nid "657";
String instruments_2_supplied_name "Lachat QuickChem flow injection analysis platform";
String instruments_3_acronym "Spectrophotometer";
String instruments_3_dataset_instrument_description "Phosphate and nitrite concentrations were measured using a Thermo Scientific Genesis 30 Visible spectrophotometer in a configuration with a detection limit of 0.05 µM.";
String instruments_3_dataset_instrument_nid "811849";
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 "Thermo Scientific Genesis 30 Visible spectrophotometer";
String keywords "aou, apparent, bco, bco-dmo, biological, chemical, chemistry, concentration, cruise, data, dataset, density, depth, deviation, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Nitrate, Earth Science > Oceans > Salinity/Density > Density, Earth Science > Oceans > Salinity/Density > Salinity, erddap, latitude, line, longitude, management, mole, mole_concentration_of_nitrate_in_sea_water, mole_concentration_of_nitrite_in_sea_water, monitoring, Monitoring_line, month, n02, n15, N15_NO3, N15_stdev, nitrate, nitrite, NO2, NO2_Stdev, no3, NO3_NO2, NO3_NO2_Stdev, o18, O18_NO3, O18_stdev, O2, ocean, oceanography, oceans, office, oxygen, po43, PO43_Stdev, practical, preliminary, salinity, science, sea, sea_water_practical_salinity, sea_water_sigma_theta, seawater, sigma, Sigma_theta, standard, standard deviation, station, Station_ID, stdev, temperature, theta, utilization, water, year";
String keywords_vocabulary "GCMD Science Keywords";
String license "https://www.bco-dmo.org/dataset/811839/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/811839";
Float64 Northernmost_Northing -29.3817;
String param_mapping "{'811839': {'Latitude': 'flag - latitude', 'Depth': 'flag - depth', 'Longitude': 'flag - longitude'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/811839/parameters";
String people_0_affiliation "University of Connecticut";
String people_0_affiliation_acronym "UConn";
String people_0_person_name "Julie Granger";
String people_0_person_nid "528937";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "University of Connecticut";
String people_1_affiliation_acronym "UConn";
String people_1_person_name "Samantha Siedlecki";
String people_1_person_nid "809305";
String people_1_role "Principal Investigator";
String people_1_role_type "originator";
String people_2_affiliation "University of Cape Town";
String people_2_affiliation_acronym "UCT";
String people_2_person_name "Raquel Flynn";
String people_2_person_nid "811844";
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 "Mathew Biddle";
String people_3_person_nid "708682";
String people_3_role "BCO-DMO Data Manager";
String people_3_role_type "related";
String project "SBUS Hypoxia";
String projects_0_acronym "SBUS Hypoxia";
String projects_0_description
"NSF Award Abstract:
The Southern Benguela Upwelling System (SBUS) in the eastern Atlantic Ocean ranks among the most fertile region in the world ocean, host to economically important fishing grounds. Unfortunately, waters of the SBUS are subject to events wherein dissolved oxygen is severely depleted, a condition also known as seasonal hypoxia, which have been observed to cause substantial fish kills. To gain a better understanding of the processes triggering severe hypoxic events, the study will combine field observations (analyzing water samples for dissolved nitrate, nitrite, ammonium, soluble reactive phosphorus, and silicic acid, as well as nitrate isotopic ratios to identify the origin and fate of nutrients in upwelling systems) and modeling. This combined approach is a powerful means of identifying the processes that contribute to the development of hypoxia in the SBUS and the mechanisms gleaned from the proposed study are likely to extend beyond the SBUS to other upwelling regions, such as the Northern Benguela, California and Peru Upwelling Systems. For outreach activities, graduate students would create a short film on their research in South Africa. This film, made available on the University of Connecticut and the University of Cape Town websites and YouTube, would serve as a means of communicating the science to broader audiences. Two graduate students would be supported and trained as part of this project. These students would have the opportunity to work with the South African collaborators at the University of Cape Town, Drs. Sarah Fawcett and Jennifer Veitch, involved in the study.
The Southern Benguela Upwelling System (SBUS), off the coasts of South Africa and Namibia, is subject to severe seasonal hypoxia which has been observed to have catastrophic impacts on wildlife, fisheries, and national economies. Researcher from the University of Connecticut posit that the propensity for hypoxic events in this region is linked to the extent of nutrient trapping on the shelf inshore of the hydrographic fronts. This, in turn, influences the intensity of subsequent blooms, and the consequent oxygen demand when this organic material is ultimately decomposed at the shelf bottom. To confirm the role of nutrient cycling in modulating hypoxic event, the scientists will utilize a combination of observations and quantitative simulations. Analyses of dissolved nutrients and nitrate isotope ratios from water samples collected on quarterly monitoring cruises in the SBUS will be used to assess the role of nutrient cycling in modulating hypoxic events. Concurrently, an idealized circulation model of the SBUS will be initiated to test the hypotheses surrounding inshore nutrient trapping and incident hypoxia. Specifically, the focus will be on the potential roles of wind intensity and periodicity, shelf frontal structure, and the alongshore pressure gradient in modulating the burden of recycled nutrients trapped on the shelf and its association with hypoxia. Finally, the ocean circulation and biogeochemistry of the SBUS will be modeled using a realistic hind-cast model forced with realistic atmospheric, tidal, and ocean boundary conditions to make hind-cast simulations of the 3-D circulation and hydrography throughout the domain. This coupled physical-biogeochemical model would be queried to fully investigate the proposed nutrient trapping mechanism and define its role in modulating the intensity of hypoxia inter-annually and from which a prognostic model can be developed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.";
String projects_0_end_date "2022-08";
String projects_0_geolocation "Southern Benguela Upwelling System";
String projects_0_name "Investigation of mechanisms leading to seasonal hypoxia in the Southern Benguela Upwelling System";
String projects_0_project_nid "809302";
String projects_0_start_date "2019-09";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing -34.5593;
String standard_name_vocabulary "CF Standard Name Table v55";
String subsetVariables "Cruise,Year";
String summary "Analysed Particulate Organic Matter data, Nutrient data and Nitrate isotope data from the 2017 Integrated Ecosystem Programme: Southern Benguela (IEP:SB) cruises conducted in February, May, and August 2017. The IEP:SB is a multi-disciplinary, multi-institutional platform to undertake relevant science in the Southern Benguela; also functioning as a platform for collaboration and learning. \\r\\n\\r\\nNitrate+nitrite concentrations were measured on a Lachat QuickChem flow injection analysis platform in a configuration with a detection limit of 0.1 \\u00b5M, while phosphate and nitrite concentrations were measured using standard benchtop techniques on a Thermo Scientific Genesis 30 Visible spectrophotometer in a configuration with a detection limit of 0.05 \\u00b5M. The N and O isotope ratios of the N2O gas were analysed using a Delta V Advantage continuous flow isotope ratio mass spectrometer interfaced with an online N2O extraction and purification system.";
String title "[IEP February and May 2017] - Nutrient and nitrate isotope data from the southern Benguela upwelling system from February to August 2017 (Investigation of mechanisms leading to seasonal hypoxia in the Southern Benguela Upwelling System)";
String version "1";
Float64 Westernmost_Easting 14.1348;
String xml_source "osprey2erddap.update_xml() v1.5";
}
}
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.