Accessing BCO-DMO data
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| Dataset Title: | [ciliate abundance and biomass] - Abundance and biomass of ciliates from inverted microscope counts from samples taken on R/V Atlantic Explorer cruises AE1102, AE1118, AE1206, AE1219 in the Sargasso Sea, Bermuda Atlantic Time- Series Station in 2011-2012 (Trophic BATS project) (Plankton Community Composition and Trophic Interactions as Modifiers of Carbon Export in the Sargasso Sea ) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_4018) |
| Information: | Summary
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| ISO 19115
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Attributes {
s {
cruise_id {
String bcodmo_name "cruise_id";
String description "Official cruise identifier e.g. AE1102 = R/V Atlantic Explorer cruise number 1102.";
String long_name "Cruise Id";
String units "dimensionless";
}
cast {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 2, 38;
String bcodmo_name "cast";
String description "Cast number.";
String long_name "Cast";
String units "dimensionless";
}
station {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 6;
String bcodmo_name "station";
String description "Station number.";
String long_name "Station";
String units "dimensionless";
}
location_description {
String bcodmo_name "site_descrip";
String description "Description of sampling location.";
String long_name "Location Description";
String units "dimensionless";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 30.83, 33.48;
String axis "Y";
String bcodmo_name "latitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "Latitude. Positive values = 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 -64.83, -64.17;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "Longitude. Positive values = East.";
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 20.0, 100.0;
String axis "Z";
String bcodmo_name "depth";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "Sample depth.";
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";
}
total_biomass {
Int16 _FillValue 32767;
Int16 actual_range 0, 2957;
String bcodmo_name "biomass_C";
String description "Total biomass (ng C/L) at the particular cast and depth.";
String long_name "Total Biomass";
String units "nanograms C per Liter";
}
taxon {
String bcodmo_name "taxon";
String description "Name of the taxonomic group.";
String long_name "Taxon";
String units "dimensionless";
}
abundance {
Int16 _FillValue 32767;
Int16 actual_range 0, 3090;
String bcodmo_name "abundance";
String description "Abundance of planktonic ciliates (cells/L).";
String long_name "Abundance";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "cells per Liter";
}
abund_upper_95pcnt_CI {
Int16 _FillValue 32767;
Int16 actual_range 5, 1414;
String bcodmo_name "unknown";
String description "Upper 95% confidence interval for abundance.";
String long_name "Abund Upper 95pcnt CI";
String units "cells per Liter";
}
abund_lower_95pcnt_CI {
Int16 _FillValue 32767;
Int16 actual_range 0, 1270;
String bcodmo_name "unknown";
String description "Lower 95% confidence interval for abundance.";
String long_name "Abund Lower 95pcnt CI";
String units "cells per Liter";
}
biomass {
Int16 _FillValue 32767;
Int16 actual_range 0, 1497;
String bcodmo_name "biomass_C";
String description "Biomass (ng C/L) of planktonic ciliates.";
String long_name "Biomass";
String units "nanograms C per Liter";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
String acquisition_description
"Water Column Sampling:
Water column sampling was performed on four cruises during the spring and
the summer of 2011 and 2012 at the Bermuda Atlantic Time-series Study station
(31\\u201940\\u00b0N 64\\u201910\\u00b0W, BATS) and in the mesoscale eddies found
in the surrounding area of the Sargasso Sea. For each cruise, 2 stations were
sampled, usually in the center of a mesoscale eddy and at BATS. The edge of
the eddy was sample two times, as well. To be able to get a better
reproducibility of data, each experiment was replicated.
For each experiment, seawater samples were collected pre-dawn (on deck
2:30-4:00, local time) at four different depths within the euphotic zone (20m,
50m, 80m and the Deep Chlorophyll Maximum, DCM). Twenty-one 10L Niskin bottles
were attached to a rosette with conductivity, temperature, depth sensors
(CTD), and an in vivo fluorometer. This sensor allowed for recording in real
time of chlorophyll fluorescence and the DCM for each station. The water that
was collected from the 10L Niskin bottles was sampled for abundance and
biomass of the plankton community.
Microscopy Analyses:
Inverted microscopy was used to determine abundance and biomass of
planktonic ciliates. Seawater was collected into 200ml amber glass bottles
which had previously been supplied with 2.5% of Lugol\\u2019s dye (v/v).
Samples were stored in the dark and at room temperature onboard ship and in
the laboratory at ASU. 100 ml of sample were settled onto settling chambers
for 48hr according to the Uterm\\u00f6hl method (Uterm\\u00f6hl, 1931). A Nikon
Elipse TE300 inverted microscope was used at 40x magnification to count the
entire slide and all the ciliates found were measured and classified based on
the classification system introduced by Agatha (2004) and Agatha & Struder-
Kypke (2007). Ciliates were classified into 4 standard shapes: prolate
spheroid, sphere, cone, cone + half sphere.
Biomass calculations were done for each category of organism counted.
Biovolume for each group was determined based on size and shape of the
organism by approximating the closest geometric shape (Hillebrand et al. 1999)
and then converted into units of carbon based on the carbon to volume ratio
(Menden-Deuer and Lessard 2000). To determine the carbon biomass of the
ciliates, carbon to volume conversion factors were used, as in Putt and
Stoecker (1989). The 95% confidence intervals were calculated according to
Lund et al. (1958).";
String awards_0_award_nid "55163";
String awards_0_award_number "OCE-1030476";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1030476&HistoricalAwards=false";
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
"Abundance and biomass of ciliates
based on inverted microscope counts
PI: Susanne Neuer (Arizona State U.)
Version: 22 Aug 2013";
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 "2013-08-22T15:43:29Z";
String date_modified "2019-08-05T18:55:51Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.4018.1";
Float64 Easternmost_Easting -64.17;
Float64 geospatial_lat_max 33.48;
Float64 geospatial_lat_min 30.83;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -64.17;
Float64 geospatial_lon_min -64.83;
String geospatial_lon_units "degrees_east";
Float64 geospatial_vertical_max 100.0;
Float64 geospatial_vertical_min 20.0;
String geospatial_vertical_positive "down";
String geospatial_vertical_units "m";
String history
"2024-11-21T08:52:08Z (local files)
2024-11-21T08:52:08Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_4018.html";
String infoUrl "https://www.bco-dmo.org/dataset/4018";
String institution "BCO-DMO";
String instruments_0_acronym "Niskin bottle";
String instruments_0_dataset_instrument_description "Samples were collected using 10-Liter Niskin bottles attached to a CTD rosette.";
String instruments_0_dataset_instrument_nid "6242";
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 "Inverted Microscope";
String instruments_1_dataset_instrument_description "Ciliate abundance and biomass was determined using bright-field inverted microscopy (Amacher et al. 2009; Neuer and Cowles 1994). A Nikon Elipse TE300 inverted microscope was used at 40x magnification to count the entire slide.";
String instruments_1_dataset_instrument_nid "6243";
String instruments_1_description
"An inverted microscope is a microscope with its light source and condenser on the top, above the stage pointing down, while the objectives and turret are below the stage pointing up. It was invented in 1850 by J. Lawrence Smith, a faculty member of Tulane University (then named the Medical College of Louisiana).
Inverted microscopes are useful for observing living cells or organisms at the bottom of a large container (e.g. a tissue culture flask) under more natural conditions than on a glass slide, as is the case with a conventional microscope. Inverted microscopes are also used in micromanipulation applications where space above the specimen is required for manipulator mechanisms and the microtools they hold, and in metallurgical applications where polished samples can be placed on top of the stage and viewed from underneath using reflecting objectives.
The stage on an inverted microscope is usually fixed, and focus is adjusted by moving the objective lens along a vertical axis to bring it closer to or further from the specimen. The focus mechanism typically has a dual concentric knob for coarse and fine adjustment. Depending on the size of the microscope, four to six objective lenses of different magnifications may be fitted to a rotating turret known as a nosepiece. These microscopes may also be fitted with accessories for fitting still and video cameras, fluorescence illumination, confocal scanning and many other applications.";
String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB05/";
String instruments_1_instrument_name "Inverted Microscope";
String instruments_1_instrument_nid "675";
String instruments_1_supplied_name "Inverted Microscope";
String keywords "95pcnt, abund, abund_lower_95pcnt_CI, abund_upper_95pcnt_CI, abundance, bco, bco-dmo, biological, biomass, cast, chemical, cruise, cruise_id, data, dataset, depth, description, dmo, erddap, latitude, location_description, longitude, lower, management, oceanography, office, preliminary, station, taxon, total, total_biomass, upper";
String license "https://www.bco-dmo.org/dataset/4018/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/4018";
Float64 Northernmost_Northing 33.48;
String param_mapping "{'4018': {'lat': 'master - latitude', 'depth': 'flag - depth', 'lon': 'master - longitude'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/4018/parameters";
String people_0_affiliation "Arizona State University";
String people_0_affiliation_acronym "ASU";
String people_0_person_name "Susanne Neuer";
String people_0_person_nid "51336";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Arizona State University";
String people_1_affiliation_acronym "ASU";
String people_1_person_name "Francesca De Martini";
String people_1_person_nid "51719";
String people_1_role "Student";
String people_1_role_type "related";
String people_2_affiliation "Arizona State University";
String people_2_affiliation_acronym "ASU";
String people_2_person_name "Susanne Neuer";
String people_2_person_nid "51336";
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 "Shannon Rauch";
String people_3_person_nid "51498";
String people_3_role "BCO-DMO Data Manager";
String people_3_role_type "related";
String project "Trophic BATS";
String projects_0_acronym "Trophic BATS";
String projects_0_description
"Fluxes of particulate carbon from the surface ocean are greatly influenced by the size, taxonomic composition and trophic interactions of the resident planktonic community. Large and/or heavily-ballasted phytoplankton such as diatoms and coccolithophores are key contributors to carbon export due to their high sinking rates and direct routes of export through large zooplankton. The potential contributions of small, unballasted phytoplankton, through aggregation and/or trophic re-packaging, have been recognized more recently. This recognition comes as direct observations in the field show unexpected trends. In the Sargasso Sea, for example, shallow carbon export has increased in the last decade but the corresponding shift in phytoplankton community composition during this time has not been towards larger cells like diatoms. Instead, the abundance of the picoplanktonic cyanobacterium, Synechococccus, has increased significantly. The trophic pathways that link the increased abundance of Synechococcus to carbon export have not been characterized. These observations helped to frame the overarching research question, \"How do plankton size, community composition and trophic interactions modify carbon export from the euphotic zone\". Since small phytoplankton are responsible for the majority of primary production in oligotrophic subtropical gyres, the trophic interactions that include them must be characterized in order to achieve a mechanistic understanding of the function of the biological pump in the oligotrophic regions of the ocean.
This requires a complete characterization of the major organisms and their rates of production and consumption. Accordingly, the research objectives are: 1) to characterize (qualitatively and quantitatively) trophic interactions between major plankton groups in the euphotic zone and rates of, and contributors to, carbon export and 2) to develop a constrained food web model, based on these data, that will allow us to better understand current and predict near-future patterns in export production in the Sargasso Sea.
The investigators will use a combination of field-based process studies and food web modeling to quantify rates of carbon exchange between key components of the ecosystem at the Bermuda Atlantic Time-series Study (BATS) site. Measurements will include a novel DNA-based approach to characterizing and quantifying planktonic contributors to carbon export. The well-documented seasonal variability at BATS and the occurrence of mesoscale eddies will be used as a natural laboratory in which to study ecosystems of different structure. This study is unique in that it aims to characterize multiple food web interactions and carbon export simultaneously and over similar time and space scales. A key strength of the proposed research is also the tight connection and feedback between the data collection and modeling components.
Characterizing the complex interactions between the biological community and export production is critical for predicting changes in phytoplankton species dominance, trophic relationships and export production that might occur under scenarios of climate-related changes in ocean circulation and mixing. The results from this research may also contribute to understanding of the biological mechanisms that drive current regional to basin scale variability in carbon export in oligotrophic gyres.";
String projects_0_end_date "2014-09";
String projects_0_geolocation "Sargasso Sea, BATS site";
String projects_0_name "Plankton Community Composition and Trophic Interactions as Modifiers of Carbon Export in the Sargasso Sea";
String projects_0_project_nid "2150";
String projects_0_start_date "2010-10";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing 30.83;
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Abundance and biomass of ciliates from inverted microscope counts from samples taken on R/V Atlantic Explorer cruises AE1102, AE1118, AE1206, AE1219 in the Sargasso Sea, Bermuda Atlantic Time-Series Station in 2011-2012.";
String title "[ciliate abundance and biomass] - Abundance and biomass of ciliates from inverted microscope counts from samples taken on R/V Atlantic Explorer cruises AE1102, AE1118, AE1206, AE1219 in the Sargasso Sea, Bermuda Atlantic Time-Series Station in 2011-2012 (Trophic BATS project) (Plankton Community Composition and Trophic Interactions as Modifiers of Carbon Export in the Sargasso Sea \t)";
String version "1";
Float64 Westernmost_Easting -64.83;
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.