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Dataset Title:  Georges Bank Fish Larvae Data collected in Bongo Nets from R/V Albatross IV, R/
V Endeavor, and R/V Oceanus during U.S. GLOBEC broadscale cruises in the Gulf
of Maine and Georges Bank from 1995-1999 (GB project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_2323)
Range: longitude = -69.142 to -65.677°E, latitude = 40.228 to 42.325°N
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  cruiseid {
    String bcodmo_name "cruiseid";
    String description "Cruise id, e.g.  EN330, for Endeavor cruise 330";
    String long_name "Cruiseid";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 1995, 1999;
    String bcodmo_name "year";
    String description "Four digit year, local time";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
  }
  inst {
    String bcodmo_name "instrument";
    String description "Instrument identifier (Bongo versus MOCNESS-1)";
    String long_name "Inst";
  }
  tow {
    Int16 _FillValue 32767;
    Int16 actual_range 1, 139;
    String bcodmo_name "tow";
    String description "Bongo plankton tow station number on a cruise";
    String long_name "Tow";
  }
  station_std {
    Byte _FillValue 127;
    Byte actual_range 1, 100;
    String bcodmo_name "station_std";
    String description "Standard station number on a cruise";
    String long_name "Station Std";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 40.228, 42.325;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude, at start of tow";
    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 -69.142, -65.677;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude, at start of tow";
    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";
  }
  month_local {
    String bcodmo_name "month_local";
    String description "Month of year (01-12), local time";
    String long_name "Month Local";
  }
  day_local {
    String bcodmo_name "day_local";
    String description "Day of year (01-31), local time";
    String long_name "Day Local";
  }
  time_local {
    String bcodmo_name "time_local";
    String description "Time at start of tow, local time";
    String long_name "Time Local";
    String units "hours/minutes";
  }
  depth_tow_max {
    Int16 _FillValue 32767;
    Int16 actual_range 24, 438;
    String bcodmo_name "depth_tow_max";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Maximum depth of the tow";
    String long_name "Depth";
    String standard_name "depth";
    String units "meters";
  }
  net {
    String bcodmo_name "net";
    String description "Net identifier";
    String long_name "Net";
  }
  haul_factor_std {
    Float32 _FillValue NaN;
    Float32 actual_range 1.37, 29.57;
    String bcodmo_name "haul_factor_std";
    String description "Standard Haul Factor1";
    String long_name "Haul Factor Std";
  }
  taxon {
    String bcodmo_name "taxon";
    String description "Taxonomic name of larval fish species";
    String long_name "Taxon";
  }
  num_caught {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 6279;
    String bcodmo_name "num_caught";
    String description "Number of the specific fish larvae caught";
    String long_name "Num Caught";
    String units "number of fish caught";
  }
  num_measure {
    Byte _FillValue 127;
    Byte actual_range 0, 117;
    String bcodmo_name "num_measure";
    String description "Number of fish larvae measured";
    String long_name "Num Measure";
  }
  fish_len {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 215.6;
    String bcodmo_name "fish_len";
    String description "Length of each fish larvae measured";
    String long_name "Fish Len";
    String units "millimeters";
  }
  num_fish_len {
    Byte _FillValue 127;
    Byte actual_range 0, 27;
    String bcodmo_name "num_fish_len";
    String description "Number of fish larvae at that length";
    String long_name "Num Fish Len";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"GLOBEC Fish Larvae collected by Bongo nets,Standard Haul Factor: numerical
factor (multiplier) used to standardize catches to be expressed as number
caught per 10m2 of sea surface area. Most haul factors range from 1 to 10. The
Standard Haul Factor has not been applied to the data reported here.";
    String awards_0_award_nid "54610";
    String awards_0_award_number "unknown GB NSF";
    String awards_0_funder_name "National Science Foundation";
    String awards_0_funding_acronym "NSF";
    String awards_0_funding_source_nid "350";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String awards_1_award_nid "54626";
    String awards_1_award_number "unknown GB NOAA";
    String awards_1_funder_name "National Oceanic and Atmospheric Administration";
    String awards_1_funding_acronym "NOAA";
    String awards_1_funding_source_nid "352";
    String cdm_data_type "Other";
    String comment 
"GLOBEC Fish Larvae collected by Bongo nets 
  Donna Johnson, SI 
    AL9906, station_std typo corrected from 35 to 7.  mda 02/26/04";
    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 "2009-11-25T13:38:33Z";
    String date_modified "2019-02-18T19:20:24Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.2323.1";
    Float64 Easternmost_Easting -65.677;
    Float64 geospatial_lat_max 42.325;
    Float64 geospatial_lat_min 40.228;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -65.677;
    Float64 geospatial_lon_min -69.142;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-03-28T09:47:40Z (local files)
2024-03-28T09:47:40Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_2323.das";
    String infoUrl "https://www.bco-dmo.org/dataset/2323";
    String institution "BCO-DMO";
    String instruments_0_acronym "Bongo Net";
    String instruments_0_dataset_instrument_description "60 cm diameter Bongo nets (0.335 millimeter mesh).";
    String instruments_0_dataset_instrument_nid "4091";
    String instruments_0_description "A Bongo Net consists of paired plankton nets, typically with a 60 cm diameter mouth opening and varying mesh sizes, 10 to 1000 micron. The Bongo Frame was designed by the National Marine Fisheries Service for use in the MARMAP program. It consists of two cylindrical collars connected with a yoke so that replicate samples are collected at the same time. Variations in models are designed for either vertical hauls (OI-2500 = NMFS Pairovet-Style, MARMAP Bongo, CalVET) or both oblique and vertical hauls (Aquatic Research). The OI-1200 has an opening and closing mechanism that allows discrete \"known-depth\" sampling. This model is large enough to filter water at the rate of 47.5 m3/minute when towing at a speed of two knots. More information: Ocean Instruments, Aquatic Research, Sea-Gear";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/NETT0009/";
    String instruments_0_instrument_name "Bongo Net";
    String instruments_0_instrument_nid "410";
    String instruments_0_supplied_name "Bongo Nets";
    String keywords "bco, bco-dmo, biological, caught, chemical, cruiseid, data, dataset, day, day_local, depth, depth_tow_max, dmo, erddap, factor, fish, fish_len, haul, haul_factor_std, inst, latitude, len, local, longitude, management, measure, month, month_local, net, num, num_caught, num_fish_len, num_measure, oceanography, office, preliminary, profiler, salinity, salinity-temperature-depth, station, station_std, std, taxon, temperature, time, time_local, tow, year";
    String license "https://www.bco-dmo.org/dataset/2323/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/2323";
    Float64 Northernmost_Northing 42.325;
    String param_mapping "{'2323': {'lat': 'master - latitude', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/2323/parameters";
    String people_0_affiliation "National Marine Fisheries Service";
    String people_0_affiliation_acronym "NMFS";
    String people_0_person_name "Dr Donna  L. Johnson";
    String people_0_person_nid "50416";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Ms Dicky Allison";
    String people_1_person_nid "50382";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "GB";
    String projects_0_acronym "GB";
    String projects_0_description 
"The U.S. GLOBEC Georges Bank Program is a large multi- disciplinary multi-year oceanographic effort. The proximate goal is to understand the population dynamics of key species on the Bank - Cod, Haddock, and two species of zooplankton (Calanus finmarchicus and Pseudocalanus) - in terms of their coupling to the physical environment and in terms of their predators and prey. The ultimate goal is to be able to predict changes in the distribution and abundance of these species as a result of changes in their physical and biotic environment as well as to anticipate how their populations might respond to climate change.
The effort is substantial, requiring broad-scale surveys of the entire Bank, and process studies which focus both on the links between the target species and their physical environment, and the determination of fundamental aspects of these species' life history (birth rates, growth rates, death rates, etc).
Equally important are the modelling efforts that are ongoing which seek to provide realistic predictions of the flow field and which utilize the life history information to produce an integrated view of the dynamics of the populations.
The U.S. GLOBEC Georges Bank Executive Committee (EXCO) provides program leadership and effective communication with the funding agencies.";
    String projects_0_geolocation "Georges Bank, Gulf of Maine, Northwest Atlantic Ocean";
    String projects_0_name "U.S. GLOBEC Georges Bank";
    String projects_0_project_nid "2037";
    String projects_0_project_website "http://globec.whoi.edu/globec_program.html";
    String projects_0_start_date "1991-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 40.228;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "inst";
    String summary "Georges Bank Fish Larvae Data collected in Bongo Nets from R/V Albatross IV, R/V Endeavor, and R/V Oceanus during U.S. GLOBEC broadscale cruises in the Gulf of Maine and Georges Bank from 1995-1999";
    String title "Georges Bank Fish Larvae Data collected in Bongo Nets from R/V Albatross IV, R/V Endeavor, and R/V Oceanus during U.S. GLOBEC broadscale cruises in the Gulf of Maine and Georges Bank from 1995-1999 (GB project)";
    String version "1";
    Float64 Westernmost_Easting -69.142;
    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
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.


 
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