Accessing BCO-DMO data
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BCO-DMO ERDDAP
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| Dataset Title: | [grazing and growth rates] - Protist rates from epifluorescence counts; cyanobacteria rates from flow cytometry; bulk rates from extracted chlorophyll- a from R/V Atlantic Explorer cruises AE1102, AE1118, AE1206, AE1219 in the Sargasso Sea, BATS, 2011-2012 (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_545844) |
| Information: | Summary
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| FGDC
| 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";
}
experiment_num {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 19;
String bcodmo_name "unknown";
String description "Experiment number.";
String long_name "Experiment Num";
String units "dimensionless";
}
date {
String bcodmo_name "date";
String description "2-digit month, 2-digit day, and 4-digit year of sampling. Reported in UTC. Format: mmddYYYY";
String long_name "Date";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
String units "unitless";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 30.05, 33.5;
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 -65.8, -63.48;
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";
}
taxon {
String bcodmo_name "taxon";
String description "Name of the taxonomic group.";
String long_name "Taxon";
String units "dimensionless";
}
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";
}
u {
Float32 _FillValue NaN;
Float32 actual_range -3.52, 11.46;
String bcodmo_name "growth";
String description "Instantaneous growth rate (mu).";
String long_name "U";
String units "per day";
}
g {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 11.17;
String bcodmo_name "unknown";
String description "Grazing mortality; absolute values.";
String long_name "G";
String units "per day";
}
}
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, two stations
were sampled, usually in the center of a mesoscale eddy and at BATS. The edge
of the eddy was sampled 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.
Dilution experiments:
The growth and grazing rates of the phytoplankton community were determined
using the dilution method with a two-point modification (Landry et al. 1984,
Landry et al. 2008a, Selph et al. 2011). To check the applicability and
resolution of the two point modification, two experiments at two different
stations (one replicate of C3 and one replicate of B3) were carried out with a
complete set of dilutions (25, 50, 75 and 100%) on-deck; the results of these
experiments confirmed the validity of the 2 point dilution experiment (data
not shown). The Landry-Hassett dilution method was used because it can
separate autotrophic and heterotrophic processes with relatively little
manipulation (Landry & Hassett, 1982, Landry et al 1984). The method is based
on the concept that the dilution lowers the encounter probability of grazer
and prey and enables one to calculate from the net phytoplankton population
growth (k) in the diluted and undiluted incubation bottles the instantaneous
growth rate (u) and grazing mortality (g), where k= u - g (Landry & Hassett,
1982). This method is based on three assumptions. \\u00a0The first one is that
the instantaneous growth rate of any phytoplankton group is not influenced by
the dilution of the \\u201cseawater/sample\\u201d with particle free water. The
second assumption is that the probability of a phytoplankton to be grazed by
the consumer is directly related to the abundance of the consumer itself,
which means that with a higher density of grazers the probability of the prey
to be grazed is higher as well, making the grazing a function of the dilution.
The third assumption is the sum of the first two assumptions, that the change
in the abundance of the phytoplankton community over time can be expressed by
the exponential growth equation:
Pt=P0 e ^ [(u -xg)t]
where P0 and Pt \\u00a0are the initial and the final abundances or biomass of
bulk or specific phytoplankton groups, t is time in day (d), u is the
instantaneous phytoplankton growth rate (d-1), g is the grazing mortality
(d-1), and x represents the dilution factor (Landry and Hassett 1982; Landry
et al. 1984; Neuer and Cowles 1994). M and g are calculated as the y-intercept
and the slope of the linear regression plotted against the dilution factors
where k=1/t ln (Pt/P0) (Landry & Hassett, 1982; Landry et al. 1984). For the
two-point dilution, this converts mathematically to solving the equations for
u and g (Landry et al., 2008a).
Bulk measurements:
Chlorophyll-a was extracted from seawater (250 ml and 400 ml depending on
the dilution), with 90% acetone and measured after 24hrs at 4 degrees C in the
dark onboard the ship using a TD 700 Laboratory Fluorometer using the non-
acidification technique (Welschmeyer 1994). These data were used as a proxy
for the phytoplankton biomass in the water column and to calculate the bulk
growth and grazing rates of the phytoplankton community.";
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
"Protist rates based on epifluorescence counts;
cyanobacteria rates based on flow cytometry data;
bulk rates based on extracted chlorophyll
PI: Susanne Neuer (Arizona State U.)
Version: 16 January 2015";
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 "2015-01-16T16:30:36Z";
String date_modified "2019-08-05T19:37:37Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.545844.1";
Float64 Easternmost_Easting -63.48;
Float64 geospatial_lat_max 33.5;
Float64 geospatial_lat_min 30.05;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -63.48;
Float64 geospatial_lon_min -65.8;
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
"2024-12-24T18:47:42Z (local files)
2024-12-24T18:47:42Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_545844.html";
String infoUrl "https://www.bco-dmo.org/dataset/545844";
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 "545856";
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 "TD-700";
String instruments_1_dataset_instrument_description "Chlorophyll-a was extracted from seawater (250 ml and 400 ml depending on the dilution), with 90% acetone and measured after 24hrs at 4 degrees C in the dark onboard ship using a TD 700 Laboratory Fluorometer using the non-acidification technique (Welschmeyer 1994).";
String instruments_1_dataset_instrument_nid "545857";
String instruments_1_description "The TD-700 Laboratory Fluorometer is a benchtop fluorometer designed to detect fluorescence over the UV to red range. The instrument can measure concentrations of a variety of compounds, including chlorophyll-a and fluorescent dyes, and is thus suitable for a range of applications, including chlorophyll, water quality monitoring and fluorescent tracer studies. Data can be output as concentrations or raw fluorescence measurements.";
String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0510/";
String instruments_1_instrument_name "Turner Designs 700 Laboratory Fluorometer";
String instruments_1_instrument_nid "694";
String instruments_1_supplied_name "TD 700 Laboratory Fluorometer";
String keywords "bco, bco-dmo, biological, cast, chemical, cruise, cruise_id, data, dataset, date, depth, description, dmo, erddap, experiment, experiment_num, latitude, location_description, longitude, management, num, oceanography, office, preliminary, station, taxon, u";
String license "https://www.bco-dmo.org/dataset/545844/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/545844";
Float64 Northernmost_Northing 33.5;
String param_mapping "{'545844': {'lat': 'master - latitude', 'depth': 'master - depth', 'lon': 'master - longitude'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/545844/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 30.05;
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Protist rates from epifluorescence counts; cyanobacteria rates from flow cytometry; bulk rates from extracted chlorophyll-a from R/V Atlantic Explorer cruises AE1102, AE1118, AE1206, AE1219 in the Sargasso Sea, BATS, 2011-2012.";
String title "[grazing and growth rates] - Protist rates from epifluorescence counts; cyanobacteria rates from flow cytometry; bulk rates from extracted chlorophyll-a from R/V Atlantic Explorer cruises AE1102, AE1118, AE1206, AE1219 in the Sargasso Sea, BATS, 2011-2012 (Plankton Community Composition and Trophic Interactions as Modifiers of Carbon Export in the Sargasso Sea \t)";
String version "1";
Float64 Westernmost_Easting -65.8;
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.