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Dataset Title:  Sampling data from Gelatinous Zooplankton project from R/V Hugh R. Sharp
multiple cruises in Chesapeake Bay from 2010-2011 (DeZoZoo project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_521596)
Range: longitude = -762532.7 to -76.194°E, latitude = 37.708 to 38.582°N, depth = 0.0 to 18.0m
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | 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 {
  cruise {
    String bcodmo_name "Cruise Name";
    String description "Internal cruise identifier: Dead Zone Zooplankton: First two digits denote Year (10=2010; 11=2011) Last two digits denote cruise number for that year";
    String long_name "Cruise";
    String units "text";
  }
  cruise_official {
    String bcodmo_name "Cruise Name";
    String description "UNOLS cruise identifier";
    String long_name "Cruise Official";
    String units "text";
  }
  station {
    Byte _FillValue 127;
    Byte actual_range 1, 18;
    String bcodmo_name "station";
    String description "Station Count";
    String long_name "Station";
    String units "number";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 37.708, 38.582;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude";
    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 -762532.67, -76.194;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude";
    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";
  }
  sample_ID {
    String bcodmo_name "sample";
    String description "Unique ID for each Sample (#-AAA-#-#) First number is station; Letters denote gear type; second number is gear deployment sequence [called cast by DMO]; third number is Net number per deployment; broken up into its component parts to be served";
    String long_name "Sample ID";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "alphanumeric";
  }
  cast {
    Byte _FillValue 127;
    Byte actual_range 1, 6;
    String bcodmo_name "cast";
    String description "gear deployment sequence";
    String long_name "Cast";
    String units "number";
  }
  net {
    Byte _FillValue 127;
    Byte actual_range 1, 6;
    String bcodmo_name "net";
    String description "net number per deployment";
    String long_name "Net";
    String units "number";
  }
  occupation {
    String bcodmo_name "unknown";
    String description "relative geolocation: South station near mouth of Rappohannock River; North station near mouth of Choptank River";
    String long_name "Occupation";
    String units "text";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2010, 2011;
    String bcodmo_name "year";
    String description "Year";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "4-digit year";
  }
  month_local {
    Byte _FillValue 127;
    Byte actual_range 5, 9;
    String bcodmo_name "month_local";
    String description "month";
    String long_name "Month Local";
    String units "number";
  }
  day_local {
    Byte _FillValue 127;
    Byte actual_range 21, 31;
    String bcodmo_name "day_local";
    String description "day of the month";
    String long_name "Day Local";
    String units "number";
  }
  time_local {
    String bcodmo_name "time";
    String description "time of net tow";
    String long_name "Time Local";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "HH:MM;24-hour clock";
  }
  gear {
    String bcodmo_name "instrument";
    String description "type of trawl";
    String long_name "Gear";
    String units "text";
  }
  mesh {
    Int16 _FillValue 32767;
    Int16 actual_range 200, 4000;
    String bcodmo_name "net_mesh";
    String description "Size of Mesh";
    String long_name "Mesh";
    String units "microns";
  }
  depth_relative {
    String bcodmo_name "depth_comment";
    String description "Depth of a net: surface= surface to above pycnocline; pycnocline = through pycnocline; below pycnocline = between bottom and pycnocline; bottom = bottom to below pycnocline";
    String long_name "Depth";
    String standard_name "depth";
    String units "text";
  }
  depth_start_nom {
    Float32 _FillValue NaN;
    Float32 actual_range 2.5, 24.0;
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Sampling depth at start of tow";
    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 0.0, 18.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Sampling depthat end of tow";
    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";
  }
  preservation {
    String bcodmo_name "unknown";
    String description "Type of preservative used for the samples";
    String long_name "Preservation";
    String units "text";
  }
  tow_duration {
    Byte _FillValue 127;
    Byte actual_range 1, 20;
    String bcodmo_name "unknown";
    String description "Time a net actively fished";
    String long_name "Tow Duration";
    String units "minutes";
  }
  vol_filt {
    Float32 _FillValue NaN;
    Float32 actual_range 36.0, 786.8;
    String bcodmo_name "vol_filt";
    String description "Amount of water filtered";
    String long_name "Vol Filt";
    String units "cubic meters";
  }
  O2_mg_L_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 10.4;
    String bcodmo_name "Dissolved_Oxygen";
    String description "Dissolved Oxygen averaged over the depth of a fishing net";
    String long_name "O2 Mg L Mean";
    String units "milligrams per liter";
  }
  time_accuracy {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 100.0;
    String bcodmo_name "unknown";
    String description "Percent of time net fished within designated depths to an accuracy of plus or minus 1 minute";
    String long_name "Time Accuracy";
    String units "minutes";
  }
  ISO_DateTime_Local {
    String bcodmo_name "ISO_DateTime_Local";
    String description "ISO standard formatted Time";
    String long_name "ISO Date Time Local";
    String units "alphanumeric";
  }
  comments {
    String bcodmo_name "comment";
    String description "notes";
    String long_name "Comments";
    String units "text";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description "\"\"";
    String awards_0_award_nid "518410";
    String awards_0_award_number "OCE-0961924";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=0961924";
    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 
"Master DeZoZoo Database 
  Cruise Log  
  Note: South station near mouth of Rappohannock River 
    North station near mouth of Choptank River";
    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 "2014-08-07T20:11:50Z";
    String date_modified "2017-06-30T17:55:52Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.687984";
    Float64 Easternmost_Easting -76.194;
    Float64 geospatial_lat_max 38.582;
    Float64 geospatial_lat_min 37.708;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -76.194;
    Float64 geospatial_lon_min -762532.67;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 18.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-04-20T13:47:37Z (local files)
2024-04-20T13:47:37Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_521596.das";
    String infoUrl "https://www.bco-dmo.org/dataset/521596";
    String institution "BCO-DMO";
    String instruments_0_acronym "Tucker Trawl";
    String instruments_0_dataset_instrument_description "Gelatinous zooplankton samples were collected with a 280 micron-meshed Tucker Trawl.";
    String instruments_0_dataset_instrument_nid "521606";
    String instruments_0_description "The original Tucker Trawl, a net with a rectangular mouth opening first built in 1951 by G.H. Tucker, was not an opening/closing system, but shortly thereafter it was modified so that it could be opened and closed.  The original had a 183 cm by 183 cm flexible rectangular mouth opening 914 cm long net with 1.8 cm stretched mesh for the first 457 cm and 1.3 cm mesh for last 457 cm. 152 cm of coarse plankton or muslin netting lined the end of the net. Tucker designed the net to collect animals associated with the deep scattering layers, principally euphausiids, siphonophores, and midwater fish. (from Wiebe and Benfield, 2003). Currently used Tucker Trawls usually have 1-m2 openings and can have a single net or multiple nets on the frame.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/NETT0161/";
    String instruments_0_instrument_name "Tucker Trawl";
    String instruments_0_instrument_nid "450";
    String instruments_0_supplied_name "Tucker Trawl";
    String instruments_1_acronym "MOCNESS";
    String instruments_1_dataset_instrument_nid "521607";
    String instruments_1_description "The Multiple Opening/Closing Net and Environmental Sensing System or MOCNESS is a family of net systems based on the Tucker Trawl principle. There are currently 8 different sizes of MOCNESS in existence which are designed for capture of different size ranges of zooplankton and micro-nekton  Each system is designated according to the size of the net mouth opening and in two cases, the number of nets it carries. The original MOCNESS (Wiebe et al, 1976) was a redesigned and improved version of a system described by Frost and McCrone (1974).(from MOCNESS manual)  This designation is used when the specific type of MOCNESS (number and size of nets) was not specified by the contributing investigator.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/NETT0097/";
    String instruments_1_instrument_name "MOCNESS";
    String instruments_1_instrument_nid "511";
    String instruments_1_supplied_name "MOCNESS";
    String keywords "accuracy, bco, bco-dmo, biological, cast, chemical, comments, cruise, cruise_official, data, dataset, date, day, day_local, depth, depth_end_nom, depth_relative, depth_start_nom, dmo, duration, erddap, filt, gear, iso, ISO_DateTime_Local, latitude, local, longitude, management, mean, mesh, month, month_local, net, O2, O2_mg_L_mean, occupation, oceanography, office, official, oxygen, preliminary, preservation, sample, sample_ID, station, time, time_accuracy, time_local, tow, tow_duration, vol, vol_filt, year";
    String license "https://www.bco-dmo.org/dataset/521596/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/521596";
    Float64 Northernmost_Northing 38.582;
    String param_mapping "{'521596': {'lat': 'master - latitude', 'depth_end_nom': 'master - depth', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/521596/parameters";
    String people_0_affiliation "University of Maryland Center for Environmental Science";
    String people_0_affiliation_acronym "UMCES/HPL";
    String people_0_person_name "James J. Pierson";
    String people_0_person_nid "51109";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Yale University";
    String people_1_person_name "Mary Beth Decker";
    String people_1_person_nid "518408";
    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 "Ms Dicky Allison";
    String people_2_person_nid "50382";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "DeZoZoo";
    String projects_0_acronym "DeZoZoo";
    String projects_0_description 
"Description from NSF award abstract:
The occurrence of low-oxygen waters, often called \"dead zones\" in coastal ecosystems throughout the world is increasing. Despite these increases, the pelagic food-web consequences of low-oxygen waters remain poorly understood. Laboratory research has demonstrated that hypoxic water (< 2 mg l-1) can result in mortality, reduced fitness and lower egg production of planktonic copepods, a major link in food webs supporting pelagic fish. Observations in the sea indicate that hypoxic bottom waters usually have depressed abundances of copepods compared to normoxic waters (> 2 mg l-1). The gradient of declining oxygen concentration with respect to depth (oxycline) can be a critical interface in coastal pelagic ecosystems by altering the migratory behavior and depth distribution of copepods and their spatial coherence with potential predators and prey. This project will result in a mechanistic understanding of how behavior and fitness of copepods are affected by hypoxia. The PIs will compare bottom-up and top-down controls on the ecology of copepods in Chesapeake Bay waters experiencing seasonal hypoxia and those that are normoxic.
Specific objectives of this project are to:
1) analyze changes in migratory behavior and fine-scale (meter) distribution of copepods across the oxycline over hourly and diel time scales while simultaneously examining the distribution and abundance of their food (phytoplankton and microzooplankton) and predators (fish, gelatinous zooplankton);
2) estimate effects of hypoxia on the \"fitness\" of copepods using a suite of measurements (length/weight ratios, feeding, egg production, and egg hatching success) to develop condition indices of copepods captured at different times and depths in hypoxic and normoxic waters; and
3) evaluate effects of hypoxia on copepod mortality by hypoxia-induced, stage-specific copepod mortality in hypoxic bottom waters and by changes in top-down control of copepods from predation by fish and gelatinous zooplankton.
Oxyclines may be a barrier to vertical migration of copepods and thus disruptive to predator avoidance behavior. Faced with increased predation risk from fish and jellyfish, copepods may seek refuge in hypoxic waters for part of the day and/or make short-term vertical excursions between hypoxic and normoxic waters. By regulating vertical migrations, copepods may increase utilization of microzooplankton prey concentrated in the oxycline. Hypoxic waters may elevate consumption of copepods by jellyfish and depress consumption by pelagic fish. This project will evaluate copepod distribution and migration behavior, individual fitness and stage-specific mortality in hypoxic and normoxic waters. It will examine food-web consequences of increased or decreased spatial coherence of copepods and their predators and prey in regions with hypoxic bottom waters and will contribute to fundamental understanding of food-web processes in eutrophic coastal ecosystems.
Project acronym \"DeZoZoo\" = \"Dead Zone Zooplankton\"";
    String projects_0_end_date "2015-02";
    String projects_0_geolocation "Chesapeake Bay";
    String projects_0_name "Hypoxia in Marine Ecosystems: Implications for Neritic Copepods";
    String projects_0_project_nid "518411";
    String projects_0_project_website "http://www.planktoneer.com/research.html#HYPOX";
    String projects_0_start_date "2010-03";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 37.708;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary 
"Cruise metadata from the Gelatinous Zooplankton portion of the Dead Zone
Zooplankton project.\\u00a0 Includes gear types and mesh sizes, locations,
dissolved oxygen in the water column,depths sampled and volume of water
filtered.";
    String title "Sampling data from Gelatinous Zooplankton project from R/V Hugh R. Sharp multiple cruises in Chesapeake Bay from 2010-2011 (DeZoZoo project)";
    String version "1";
    Float64 Westernmost_Easting -762532.67;
    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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