Accessing BCO-DMO data
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| Dataset Title: | Sugar concentrations from the BATS site in the Sargasso Sea, 2001-2004 (Ocean Microbial Observatory project) 
|
| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_543771) |
| Information: | Summary
| License
| ISO 19115
| Metadata
| Background
| Subset
| Files
| Make a graph
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Attributes {
s {
cruise_id {
String bcodmo_name "cruise_id";
String description "UNOLS cruise identification";
String long_name "Cruise Id";
String units "unitless";
}
cruise_id2 {
String bcodmo_name "cruise_id";
String description "BATS cruise during which sample was collected";
String long_name "Cruise Id2";
String units "unitless";
}
cruise_code {
Int16 _FillValue 32767;
Int16 actual_range 10156, 10195;
String bcodmo_name "cruise_id";
String description "BATS cruise code";
String long_name "Cruise Code";
String units "unitless";
}
station {
Float32 _FillValue NaN;
Float32 actual_range 156.1, 195.1;
String bcodmo_name "station";
String description "BATS station label";
String long_name "Station";
String units "unitless";
}
cast_type {
String bcodmo_name "cast_type";
String description "B for bottle type of cast";
String long_name "Cast Type";
String units "unitless";
}
time {
String _CoordinateAxisType "Time";
Float64 actual_range 1.0002993e+9, 1.10251632e+9;
String axis "T";
String bcodmo_name "ISO_DateTime_UTC";
String description "date and time at start of cast [UTC] formatted as yyyy-mm-ddThh:mm:ss.sss";
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 "1970-01-01T00:00:00.000Z";
String units "seconds since 1970-01-01T00:00:00Z";
}
year_decimal {
Float64 _FillValue NaN;
Float64 actual_range 2001.697365, 2004.936081;
String bcodmo_name "year_decimal";
String description "decimal year formatted as yyyy.fraction_of_year";
String long_name "Year Decimal";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 31.593, 31.711;
String axis "Y";
String bcodmo_name "latitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "latitude at start of cast; north is positive";
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 -64.271, -64.092;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "longitude at start of cast; east is positive";
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_ {
Float32 _FillValue NaN;
Float32 actual_range 2.4, 253.11;
String bcodmo_name "depth";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "CTD depth";
String long_name "Depth";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
String standard_name "depth";
String units "meters";
}
depth {
String _CoordinateAxisType "Height";
String _CoordinateZisPositive "down";
Float64 _FillValue NaN;
Float64 actual_range 1.0, 250.0;
String axis "Z";
String bcodmo_name "depth_n";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "bottle target depth";
String ioos_category "Location";
String long_name "Depth";
String positive "down";
String standard_name "depth";
String units "m";
}
fucose {
Float32 _FillValue NaN;
Float32 actual_range 50.07, 487.88;
String bcodmo_name "unknown";
String description "concentration of Fucose";
String long_name "Fucose";
String units "nanomoles/liter";
}
rhamnose {
Float32 _FillValue NaN;
Float32 actual_range 35.0, 371.68;
String bcodmo_name "unknown";
String description "concentration of Rhamnose";
String long_name "Rhamnose";
String units "nanomoles/liter";
}
arabinose {
Float32 _FillValue NaN;
Float32 actual_range 25.38, 309.17;
String bcodmo_name "unknown";
String description "concentration of Arabinose";
String long_name "Arabinose";
String units "nanomoles/liter";
}
galactose {
Float32 _FillValue NaN;
Float32 actual_range 60.28, 968.33;
String bcodmo_name "unknown";
String description "concentration of Galactose";
String long_name "Galactose";
String units "nanomoles/liter";
}
glucose {
Float32 _FillValue NaN;
Float32 actual_range 110.82, 2082.69;
String bcodmo_name "unknown";
String description "concentration of Glucose";
String long_name "Glucose";
String units "nanomoles/liter";
}
mannose {
Float32 _FillValue NaN;
Float32 actual_range 98.09, 1193.59;
String bcodmo_name "unknown";
String description "concentration of Mannose";
String long_name "Mannose";
String units "nanomoles/liter";
}
DCNS {
Float32 _FillValue NaN;
Float32 actual_range 0.47, 4.24;
String bcodmo_name "unknown";
String description "dissolved combined neutral sugar concentration in micromolar carbon units";
String long_name "DCNS";
String units "nanomoles/liter";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
String acquisition_description
"Methodology is from Goldberg et al (2009).
Study site
The BATS site is located at 31\\u00b040'N, 64\\u00b010'W in the Northwestern
Sargasso Sea. There, the surface layer of the water column is thermally
stratified during summer and autumn months and concentrations of
macronutrients are generally below limits of detection (Steinberg et al.,
2001). Sub-tropical mode water (STMW), formed to the north before subducting
with subsequent southerly flow, lies below the surface layer at the BATS site,
occupying the 18 \\u00b0C thermostad between 150 and 400 m (Worthington, 1976;
Palter et al., 2005). Deep convective mixing that occurs during winter months
can entrain STMW, with elevated nutrient concentrations, into the surface
layer, supporting the annual winter/spring phytoplankton bloom.
Sample collection
Samples for DOC and DCNS were collected monthly to bimonthly between 2001
and 2004 at the BATS study site aboard the R/V Weatherbird II. Seawater was
collected in 12 L Niskin bottles using a conductivity, temperature, and depth
(CTD) profiler. Each sample was gravity filtered through an inline 47 mm glass
fiber filter (GF/F filters, Whatman) housed in an acid cleaned polycarbonate
cartridge (Gelman) and attached directly to the Niskin bottle spigot using
silicone tubing. Filtrate was collected in 40 mL combusted glass EPA vials,
frozen immediately, and stored at -20 \\u00b0C until analysis at University of
California Santa Barbara. For long-term storage, 4 mL aliquots of sample were
transferred into 5 mL glass ampoules, dried in a Savant Speed Vac, sealed with
Teflon tape, and stored in sealed polyethylene bags at -20 \\u00b0C. All
plasticware was washed with 10% hydrochloric acid (HCl; Fisher) and flushed
thoroughly with UV oxidized Nanopure\\u00ae water (Barnstead Thermoline). Glass
fiber (GF/F) filters and borosilicate vials were combusted at 450 \\u00b0C for
2-3 h prior to use. All samples were analyzed between October 2004 and July
2006.
To ensure run-to-run comparability, surface (1 m) and deep (200 m) seawater
references (same batch) were incorporated in each run. A large batch of
reference seawaters were collected during the summer of 2004 from the Santa
Barbara Channel, filtered, dried and stored in 5 mL glass ampoules as
described above.
Sample processing
All DCNS samples were analyzed in triplicate following the methodology of
Borch and Kirchman (1997) with slight modification of the hydrolysis time (see
recovery tests below). Prior to hydrolysis, dried samples were resuspended to
the initial volume with Nanopure\\u00ae water. Samples were then flame sealed
and hydrolyzed with H2SO4 (0.85 M; Fisher) for 21 h at 100 \\u00b0C. Samples
were cooled then pipetted into 30 mL polycarbonate tubes that had been pre-
cleaned with successive rinses of methanol (Fisher), 0.5 M HCl, 0.5 M NaOH
(Fisher), and Nanopure\\u00ae water. Samples were neutralized with 1.2 Meq
CaCO3 that had been precombusted at 450 \\u00b0C for 2-3 h and vortexed until a
pH of ~6 was achieved (Skoog and Benner, 1997). Samples were then placed in a
centrifuge and spun at 28,760g for 30 min at room temperature. The supernatant
was dispensed by pipette into 7 mL combusted glass scintillation vials
equipped with Teflon lined caps and refrigerated (4 \\u00b0C no longer than 72
h) in the dark prior to desalting. The desalting protocol was conducted
according to the methods of Mopper et al. (1992) in 20 mL BioRad (Hercules,
CA) HDPE columns that were cleaned with full bed volumes of NaOH (0.5 M), HCl
(0.5 M), and Nanopure\\u00ae water prior to resin loading. Columns were loaded
with 7 mL of mixed anion (AG 2-X8, 20-50 mesh, Bio-Rad) and cation (AG 50W-X8,
100-200 mesh, Bio-Rad) exchange resin that were then flushed 3\\u00d7 with two
bed volumes of Nanopure\\u00ae water and dried by purging with ultra high
purity He gas. Resin was primed 3 times with 400 \\u00b5L of sample and purged
immediately. Then, 900 \\u00b5L of sample was added to the resin and let stand
for 7 min before collection in 20 mL combusted glass scintillation vials.
Sample salinity was randomly checked with a refractometer. Only one lot of
mixed anion and cation exchange resin was used throughout this study and was
regenerated over the extended period of analysis to ensure consistency in
sugar recovery, as demonstrated with reference water runs.
HPLC analysis
DCNS were analyzed via pulsed amperometric detection high performance liquid
chromatography (PAD-HPLC) using a Dionex (Sunnyvale, CA) Bio-LC 600 equipped
with a GS-50 pump, ED-50 detector, and AS-50 autosampler. Chromeleon 6.2
integration software was used for data integration. Sugars were isocratically
eluted at 18 mM NaOH (50% w/w, Fisher) and separated with Dionex CarboPac
PA-10 analytical and guard columns. The electrochemical detector was equipped
with an Au working electrode and an Ag/Cl pH reference electrode. A 200 mM
NaOH wash (10 min) was used to minimize CO3 buildup on the columns and was
performed after each sample. A known Dionex mono-standard (100 nM) of 6 sugars
(fucose, galactosamine, glucosamine, galactose, glucose and mannose) was
analyzed every 8th sample to assess variability associated with the electrodes
and PA-10 columns. This standard was also used to determine if the PAD-HPLC
system was stable for each analytical run. Runs were aborted when the decrease
in sensitivity approached 20% of initial standard values. A mono-standard mix
of 7 sugars including fucose, rhamnose, arabinose, galactose, glucose,
mannose, and fructose (Absolute Standards Inc., Hamden, CT) was used for
standardization via a 4-point standard curve (10, 75, 125, 250 nM). Desalting
and hydrolysis recoveries for aldoses in the quantification standard were
within the range of 70-90% and 55-60%, respectively, for all neutral sugars.
The values for DCNS in field samples were normalized to hydrolyzed and
desalted quantification standards, similar to Kirchman et al. (2001).
Concentrations reported have been corrected for blank levels measured with
hydrolyzed Nanopure\\u00ae water. Fructose is degraded or destroyed during acid
hydrolysis, and is therefore not reported. Similar to other studies of DCNS in
oceanic settings (Borch and Kirchman, 1997; Rich et al., 1997; Kirchman et
al., 2001), the peaks for mannose and xylose co-eluted and are referred to as
mannose+xylose hereafter.
Vials containing surface and deep reference seawater material processed with
every batch of samples were analyzed to track total analytical variability
over time. Surface and deep reference waters were analyzed in triplicate at
the beginning, middle, and end of each run to assess protocol efficiency,
cleanliness and consistency within and between runs.
Ancillary data
Supporting data such as DOC concentration, primary production (PP),
temperature, and sigma-theta were provided by the BATS time-series program and
are available at ([http://bats.bbsr.edu/](\\\\\"http://bats.bbsr.edu/\\\\\")). DOC
concentrations were determined according to the method of Farmer and Hansell
(2007), and the analytical variability was <2% for field (Hansell and Carlson,
2001; Carlson et al., 2004) and seawater culture samples. There is minimal
contribution of particles to TOC at the BATS site (Hansell and Carlson, 2001),
and DOC concentrations reported herein reflect values determined from
unfiltered samples. The methods used to make the remaining ancillary
measurements are described in Knap et al. (1997).
Data analyses
Multivariate statistical analysis (EOF) was performed to assess vertical and
temporal variability of organic carbon constituents including concentrations
of bulk DOC, bulk DCNS, and individual neutral sugars (i.e. fucose, rhamnose,
arabinose, galactose, glucose, and mannose+xylose) measured from 2001 to 2004
(n=228 time points) over the upper 250 m at the BATS study site. All data were
mean-centered and normalized to their standard deviation at each sampling
depth (i.e. 0, 40, 80, 100, 140, 250 m). Correlation coefficients and p-values
between EOF modal amplitudes, mol% DCNS values, DCNS yield, temperature, and
sigma-theta were calculated with Statview 5.0 (SAS). Figures were made using
Deltagraph and Matlab and all contour plots were generated using Ocean Data
View (Schlitzer, 2007).
Seawater cultures
Seawater culture experiments using natural assemblages of heterotrophic
bacterioplankton followed the methods of Carlson et al. (2004). They were
designed to assess the turnover of DCNS and DOC that accumulated in the
stratified surface seawater at or in the vicinity of the BATS study site.
Seawater was collected at BATS in September of 2005 aboard the R/V Weatherbird
II and along the A20 (30 \\u00b054'N, 52\\u00b020'W) US CLIVAR Repeat
Hydrography transect in October of 2003 aboard the R/V Knorr. Upon recovery of
the CTD, a filtrate of surface seawater was collected in a clean polycarbonate
carboy by gravity filtration through a 0.2 \\u00b5m pore size 142 mm Costar
Membra-Fil filter housed in a 142 mm plastic filter holder. Costar Membra-Fil
filters leach DOC upon initial use (Carlson et al., 2004), and so were flushed
with >2 L of Nanopure\\u00ae water and >0.5 L of seawater prior to collecting
the filtrate to prevent organic contamination. Whole surface seawater was
diluted by 70% with the 0.2 \\u00b5m filtrate for all experimental treatments,
and final volumes were 10 and 8 L respectively for the BATS and A20
experiments. All cultures were incubated at in situ temperatures in the dark
in Precision laboratory incubators for 8-31 days. Bacterioplankton samples for
cellular abundance were collected and fixed with 0.2 \\u00b5m filtered 10%
formalin (final concentration 3.5%; Fisher). These samples were stored at 4
\\u00b0C until slides were prepared (within 48 h of collection). Cells were
filtered onto 0.2 \\u00b5m polycarbonate filters pre-stained with Irgalan black
that were subsequently stained with 4'-6'-diamidino-2-phenylidole (DAPI)
according to the methods of Porter and Feig (1980). An Olympus AX70 or BX-51
epifluorescence microscope was used to enumerate DAPI stained cells.";
String awards_0_award_nid "514363";
String awards_0_award_number "OCE-0802004";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=0802004";
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
"Sugars at BATS site, 2001-2004
C. Carlson (UC-SB)
version: 2014-12-16";
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 "2014-12-23T15:26:06Z";
String date_modified "2020-05-11T19:39:47Z";
String defaultDataQuery "&time<now";
String doi "10.26008/1912/bco-dmo.543771.1";
Float64 Easternmost_Easting -64.092;
Float64 geospatial_lat_max 31.711;
Float64 geospatial_lat_min 31.593;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -64.092;
Float64 geospatial_lon_min -64.271;
String geospatial_lon_units "degrees_east";
Float64 geospatial_vertical_max 250.0;
Float64 geospatial_vertical_min 1.0;
String geospatial_vertical_positive "down";
String geospatial_vertical_units "m";
String history
"2024-04-18T11:59:57Z (local files)
2024-04-18T11:59:57Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_543771.html";
String infoUrl "https://www.bco-dmo.org/dataset/543771";
String institution "BCO-DMO";
String instruments_0_acronym "Niskin bottle";
String instruments_0_dataset_instrument_description "12 liter Niskin bottles";
String instruments_0_dataset_instrument_nid "543806";
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_0_supplied_name "Niskin bottle";
String instruments_1_acronym "CTD";
String instruments_1_dataset_instrument_nid "543807";
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_1_supplied_name "CTD";
String instruments_2_acronym "HPLC";
String instruments_2_dataset_instrument_description "DCNS were analyzed via pulsed amperometric detection highperformance liquid chromatography (PAD-HPLC) using a Dionex (Sunnyvale, CA) Bio-LC600 equipped with a GS-50 pump, ED-50 detector, and AS-50 autosampler. Chromeleon 6.2 integration software was used for data integration.";
String instruments_2_dataset_instrument_nid "543805";
String instruments_2_description "A High-performance liquid chromatograph (HPLC) is a type of liquid chromatography used to separate compounds that are dissolved in solution. HPLC instruments consist of a reservoir of the mobile phase, a pump, an injector, a separation column, and a detector. Compounds are separated by high pressure pumping of the sample mixture onto a column packed with microspheres coated with the stationary phase. The different components in the mixture pass through the column at different rates due to differences in their partitioning behavior between the mobile liquid phase and the stationary phase.";
String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB11/";
String instruments_2_instrument_name "High Performance Liquid Chromatograph";
String instruments_2_instrument_nid "506";
String instruments_2_supplied_name "PAD-HPLC";
String keywords "arabinose, bco, bco-dmo, biological, cast, cast_type, chemical, code, cruise, cruise_code, cruise_id, cruise_id2, data, dataset, date, dcns, decimal, depth, depth_n, dmo, erddap, fucose, galactose, glucose, id2, iso, latitude, longitude, management, mannose, oceanography, office, preliminary, rhamnose, station, time, type, year, year_decimal";
String license "https://www.bco-dmo.org/dataset/543771/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/543771";
Float64 Northernmost_Northing 31.711;
String param_mapping "{'543771': {'lat': 'master - latitude', 'lon': 'master - longitude', 'ISO_DateTime_UTC': 'flag - time', 'depth_n': 'flag - depth'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/543771/parameters";
String people_0_affiliation "University of California-Santa Barbara";
String people_0_affiliation_acronym "UCSB";
String people_0_person_name "Craig Carlson";
String people_0_person_nid "50575";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Oregon State University";
String people_1_affiliation_acronym "OSU";
String people_1_person_name "Dr Stephen Giovannoni";
String people_1_person_nid "514364";
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 "Ocean Microbial Observatory";
String projects_0_acronym "Ocean Microbial Observatory";
String projects_0_description
"(Adapted from the NSF award abstract)
The premise of this project is that stratified bacterioplankton clades engage in specialized biogeochemical activities that can be identified by integrated oceanographic and microbiological approaches. Specifically, the objective of this project is to assess if the mesopelagic microbial community rely on diagenetically altered organic matter and subcellular fragments that are produced by microbial processes in the euphotic zone and delivered into the upper mesopelagic by sinking or mixing. In past efforts this microbial observatory had greater success cultivating members of the euphotic zone microbial community, and revealed an unanticipated growth requirement for reduced sulfur compounds in alphaproteobacteria of the SAR11 clade. Genomic information showed that intense competition for substrates imposes trade-offs on bacterioplankton - there are regions of N dimensional nutrient space where specialists win. We postulate that specific growth requirements may explain some the regular spatial and temporal patterns that have been observed in upper mesopelagic bacterioplankton communities, and the difficulties of culturing some of these organisms.
The specific objectives of this project are: 1) to produce 13C and 15N labeled subcellular (e.g., soluble, cell wall, and membrane) and DOM fractions from photosynthetic plankton cultures and use stable isotope probing to identify specific clades in the surface and upper mesopelagic microbial community that assimilate fractions of varying composition and lability. 2) to use fluorescence in situ hybridization approaches to monitor temporal and spatial variability of specific microbial populations identified from the SIP and HTC experiments. To increase resolution we will use CARD-FISH protocols. 3) to measure the proteomes of bacterioplankton communities to identify highly translated genes in the surface layer and upper mesopelagic, and community responses to seasonal nutrient limitation. 4) and, to cultivate these organisms via high throughput culturing (HTC) by pursuing the hypothesis that they require specific nutrient factors and/or diagenetically altered organic substrates. Complete genome sequences from key organisms will be sought and used as queries to study patterns of natural variation in genes and populations that have been associated with biogeochemically important functions.";
String projects_0_end_date "2014-07";
String projects_0_geolocation "Bermuda Atlantic Time-Series study site";
String projects_0_name "Transitions in the Surface Layer and the Role of Vertically Stratified Microbial Communities in the Carbon Cycle - An Oceanic Microbial Observatory";
String projects_0_project_nid "514365";
String projects_0_project_website "http://www.bios.edu/research/projects/oceanic-microbial-observatory/";
String projects_0_start_date "2008-08";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing 31.593;
String standard_name_vocabulary "CF Standard Name Table v55";
String subsetVariables "cruise_id,cast_type";
String summary "Sugar concentrations and dissolved combined neutral sugar (DCNS) dynamics were measured from samples for DCNS collected monthly to bimonthly between 2001 and 2004 at the BATS study site aboard the R/V Weatherbird II, Western Sargasso Sea.";
String time_coverage_end "2004-12-08T14:32:00.000Z";
String time_coverage_start "2001-09-12T12:55:00.000Z";
String title "Sugar concentrations from the BATS site in the Sargasso Sea, 2001-2004 (Ocean Microbial Observatory project)";
String version "1";
Float64 Westernmost_Easting -64.271;
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.