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Dataset Title:	Zooplankton densities collected from a seasonally hypoxic fjord on R/V Clifford A Barnes cruises from 2012-2013 (Pelagic Hypoxia project)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_682074)
Range:	longitude = -123.125 to -122.807°E, latitude = 47.371 to 47.812°N, time = 2012-06-11T14:10:00Z to (now?)
Information:	Summary \| License \| ISO 19115 \| Metadata \| Background \| 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:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  station {
    String bcodmo_name "station";
    String description "Station code where sampling occurred; DB=Dabob; UN=Union; HP=Hoodsport; DU=Duckabush; TW=Twanoh.";
    String long_name "Station";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 47.371, 47.812;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude; N 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 -123.125, -122.807;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude; S 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";
  }
  day_night {
    String bcodmo_name "unknown";
    String description "Indication of whether sampling occurred at day or night.";
    String long_name "Day Night";
    String units "unitless";
  }
  species {
    String bcodmo_name "species";
    String description "Species sampled";
    String long_name "Species";
    String units "unitless";
  }
  date {
    Int32 _FillValue 2147483647;
    Int32 actual_range 20120611, 20131003;
    String bcodmo_name "date";
    String description "Date sample was collected; Local time (PDT); YYYYMMDD";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  time_start {
    String bcodmo_name "time_start";
    String description "Start time of sampling; HH:MM";
    String long_name "Time Start";
    String units "unitless";
  }
  life_history_stage {
    String bcodmo_name "stage";
    String description "Description of life history stage at which sample was found";
    String long_name "Life History Stage";
    String units "unitless";
  }
  sample_code {
    String bcodmo_name "sample";
    String description "PI issued sample ID; sampling date + Station + D (day ) or N (night)  + Net code (e.g. m1) _mesh";
    String long_name "Sample Code";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  mesh_size {
    Int16 _FillValue 32767;
    Int16 actual_range 200, 335;
    String bcodmo_name "filter_size";
    String description "Size of mesh used in sampling.";
    String long_name "Mesh Size";
    String units "microns";
  }
  depth_max {
    Float32 _FillValue NaN;
    Float32 actual_range 5.0, 165.0;
    String bcodmo_name "depth_max";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Maximum depth sampled.";
    String long_name "Depth";
    String standard_name "depth";
    String units "meters";
  }
  depth_min {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 90.0;
    String bcodmo_name "depth_min";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Minimum depth sampled.";
    String long_name "Depth";
    String standard_name "depth";
    String units "meters";
  }
  FWC_DS {
    String bcodmo_name "unknown";
    String description "Full whole column (FWC) sampling or depth-stratified (DS) sampling";
    String long_name "FWC DS";
    String units "unitless";
  }
  density {
    Float64 _FillValue NaN;
    Float64 actual_range 7.9732e-4, 14125.0;
    String bcodmo_name "density";
    String description "Density of species sampled";
    String long_name "Density";
    String units "count per meter cubed";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.3394238e+9, NaN;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date/Time (UTC) ISO formatted";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"We conducted day/night paired zooplankton sampling in Hood Canal in June-
October, 2012 and 2013. Sampling stations included Dabob, Union, Hoodsport,
Duckabush, and Twanoh. A Hydrobios MultiNet (five-net capacity) was used to
collect depth-stratified and full water column samples. Net mouth area was
0.25 m2; 200- and 335-um mesh nets were used to sample different size
zooplankton. Nets were towed obliquely at 1-2.5 knots (slower tows for smaller
mesh size), with inner and outer flow meters to measure water volume sampled.
For the depth-stratified sampling, depth layers were based on the dissolved
oxygen profiles from CTD casts.
 
In the laboratory, zooplankton were quantitatively subsampled and
microscopically counted. All individuals were identified to species or larger
taxonomic grouping, and by life stages for some species, within each sample.";
    String awards_0_award_nid "557503";
    String awards_0_award_number "OCE-1154648";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1154648";
    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 
"Zooplankton Densities 
  J. Keister et al. 
  Version 8 February 2017";
    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 "2017-02-11T00:19:13Z";
    String date_modified "2019-04-04T16:46:00Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.682074.1";
    Float64 Easternmost_Easting -122.807;
    Float64 geospatial_lat_max 47.812;
    Float64 geospatial_lat_min 47.371;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -122.807;
    Float64 geospatial_lon_min -123.125;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-04-19T11:22:09Z (local files)
2024-04-19T11:22:09Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_682074.das";
    String infoUrl "https://www.bco-dmo.org/dataset/682074";
    String institution "BCO-DMO";
    String instruments_0_acronym "SBE-43 DO";
    String instruments_0_dataset_instrument_nid "682096";
    String instruments_0_description "The Sea-Bird SBE 43 dissolved oxygen sensor is a redesign of the Clark polarographic membrane type of dissolved oxygen sensors. more information from Sea-Bird Electronics";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0036/";
    String instruments_0_instrument_name "Sea-Bird SBE 43 Dissolved Oxygen Sensor";
    String instruments_0_instrument_nid "552";
    String instruments_0_supplied_name "SBE 43";
    String instruments_1_acronym "MultiNet";
    String instruments_1_dataset_instrument_description "Used to collect water column samples";
    String instruments_1_dataset_instrument_nid "682100";
    String instruments_1_description "The MultiNet© Multiple Plankton Sampler is designed as a  sampling system for horizontal and vertical collections in successive water layers. Equipped with 5 or 9 net bags, the MultiNet© can be delivered in 3 sizes (apertures) : Mini (0.125 m2), Midi (0.25 m2) and Maxi (0.5 m2). The system consists of a shipboard Deck Command Unit and a stainless steel frame to which 5 (or 9) net bags are attached by means of zippers to canvas. The net bags are opened and closed by means of an arrangement of levers that are triggered by a battery powered Motor Unit. The commands for actuation of the net bags are given via single or multi-conductor cable between the Underwater Unit and the Deck Command Unit.  Although horizontal collections typically use a mesh size of 300 microns, mesh sizes from 100 to 500 may also be used. Vertical collections are also common.  The shipboard Deck Command Unit displays all relevant system data, including the actual operating depth of the net system.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/NETT0099/";
    String instruments_1_instrument_name "MultiNet";
    String instruments_1_instrument_nid "559";
    String instruments_1_supplied_name "Hydrobios MultiNet (five-net capacity)";
    String keywords "bco, bco-dmo, biological, chemical, code, data, dataset, date, day, day_night, density, depth, depth_max, depth_min, dmo, erddap, fwc, FWC_DS, history, iso, ISO_DateTime_UTC, latitude, life, life_history_stage, longitude, management, mesh, mesh_size, night, oceanography, office, preliminary, sample, sample_code, size, species, stage, start, station, time, time_start";
    String license "https://www.bco-dmo.org/dataset/682074/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/682074";
    Float64 Northernmost_Northing 47.812;
    String param_mapping "{'682074': {'lat': 'master - latitude', 'lon': 'master - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/682074/parameters";
    String people_0_affiliation "University of Washington";
    String people_0_affiliation_acronym "UW";
    String people_0_person_name "Dr Julie E. Keister";
    String people_0_person_nid "51330";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Washington";
    String people_1_affiliation_acronym "UW";
    String people_1_person_name "Dr Timothy Essington";
    String people_1_person_nid "557506";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Washington";
    String people_2_affiliation_acronym "UW";
    String people_2_person_name "Dr John K. Horne";
    String people_2_person_nid "557509";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Northwest Fisheries Science Center - Seattle";
    String people_3_affiliation_acronym "NOAA NWFSC";
    String people_3_person_name "Dr Sandra Parker-Stetter";
    String people_3_person_nid "557511";
    String people_3_role "Co-Principal Investigator";
    String people_3_role_type "originator";
    String people_4_affiliation "University of Washington";
    String people_4_affiliation_acronym "UW";
    String people_4_person_name "Dr Julie E. Keister";
    String people_4_person_nid "51330";
    String people_4_role "Contact";
    String people_4_role_type "related";
    String people_5_affiliation "Woods Hole Oceanographic Institution";
    String people_5_affiliation_acronym "WHOI BCO-DMO";
    String people_5_person_name "Hannah Ake";
    String people_5_person_nid "650173";
    String people_5_role "BCO-DMO Data Manager";
    String people_5_role_type "related";
    String project "PelagicHypoxia";
    String projects_0_acronym "PelagicHypoxia";
    String projects_0_description 
"Description from NSF award abstract:
Low dissolved oxygen (hypoxia) is one of the most pronounced, pervasive, and significant disturbances in marine ecosystems. Yet, our understanding of the ecological impacts of hypoxia on pelagic food webs is incomplete because of our limited knowledge of how organism responses to hypoxia affect critical ecosystem processes. In pelagic food webs, distribution shifts of mesozooplankton and their predators may affect predator-prey overlap and dictate energy flow up food webs. Similarly, hypoxia may induce shifts in zooplankton community composition towards species that impede energy flow to planktivorous fish. However, compensatory responses by species and communities might negate these effects, maintaining trophic coupling and sustaining productivity of upper trophic level species. The PIs propose to answer the question \"Does hypoxia affect energy flow from mesozooplankton to pelagic fish?\" They approach this question with a nested framework of hypotheses that considers two sets of processes alternatively responsible for either changes or maintenance of pelagic ecosystem energy flows. They will conduct their study in the Hood Canal, WA. Unlike most hypoxia-impacted estuaries, hypoxic regions of Hood Canal are in close proximity to sites that are not affected. This makes it logistically easier to conduct a comparative study and reduces the number of potential confounding factors when comparing areas that are far apart.
Improved understanding of how hypoxia impacts marine ecosystems will benefit the practical application of ecosystem-based management (EBM) in coastal and estuarine ecosystems. Effective application of EBM requires that the impacts of human activities are well understood and that ecological effects can be tracked using indicators. This project will contribute to both of these needs. The PIs will share their findings on local and national levels with Federal, State, Tribal, and County biologists. To increase exposure of science to underrepresented groups, the PIs also will provide Native American youth with opportunities to participate in field collections and laboratory processing through summer internships. The PIs will collaborate with the NSF-funded Pacific Northwest Louis Stokes Alliance for Minority Participation and tribes from the Hood Canal region to recruit and mentor students for potential careers in marine science. This project will support several undergraduate researchers, two Ph.D. students, a post-doc, and two early-career scientists.";
    String projects_0_end_date "2016-05";
    String projects_0_geolocation "Puget Sound, WA (47 N, 123 W)";
    String projects_0_name "Consequences of hypoxia on food web linkages in a pelagic marine ecosystem";
    String projects_0_project_nid "557504";
    String projects_0_start_date "2012-06";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 47.371;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Zooplankton densities collected from a seasonally hypoxic fjord on R/V Clifford A Barnes cruises from 2012-2013 (Pelagic Hypoxia project)";
    String time_coverage_start "2012-06-11T14:10:00Z";
    String title "Zooplankton densities collected from a seasonally hypoxic fjord on R/V Clifford A Barnes cruises from 2012-2013 (Pelagic Hypoxia project)";
    String version "1";
    Float64 Westernmost_Easting -123.125;
    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.

(easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

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.