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Dataset Title:  Date, time, location, and depth range for MOCNESS tows from R/V Oceanus in the
Eastern Tropical Pacific, Tropical Eastern Pacific from 2016-04-17 to 2016-05-02
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_787329)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
   or a List of Values ?
   Maximum ?
 
 cruise_id (unitless) ?      
   - +  ?
 Station (unitless) ?          "1"    "Test"
 MOC (unitless) ?          701    713
 Tow_Type (unitless) ?          "Deep Layers (600-8..."    "Surface to OMZ"
 time (ISO Date Time UTC, UTC) ?          2016-04-17T22:28:00Z    2016-05-02T21:03:00Z
  < slider >
 Date_Local (unitless) ?          "04172016"    "05022016"
 Date_UTC (unitless) ?          "04172016"    "05022016"
 Time_In_Local (unitless) ?          "0933"    "2200"
 Time_Out_Local (unitless) ?          "0237"    "2343"
 Time_In_UTC (unitless) ?          "0226"    "2228"
 Time_Out_UTC (unitless) ?          "0003"    "2325"
 latitude (degrees_north) ?          21.849    31.13
  < slider >
 longitude (degrees_east) ?          -126.27    -119.931
  < slider >
 Lat_Out (Latitude, decimal degrees) ?          21.872    31.145
 Lon_Out (Longitude, decimal degrees) ?          -126.3    -120.001
 Day_Night (unitless) ?          "D"    "N"
 Min_Depth (meters (m)) ?          0    600
 depth (Max Depth, m) ?          100.0    1000.0
  < slider >
 Comments (unitless) ?          "Equipment Test"    "Uncertain Net Trip..."
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")

File type: (more info)

(Documentation / Bypass this form ? )
 
(Please be patient. It may take a while to get the data.)


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  cruise_id {
    String bcodmo_name "cruise_id";
    String description "identifier for the cruise as extracted from the file name";
    String long_name "Cruise Id";
    String units "unitless";
  }
  Station {
    String bcodmo_name "station";
    String description "Station number";
    String long_name "Station";
    String units "unitless";
  }
  MOC {
    Int16 _FillValue 32767;
    Int16 actual_range 701, 713;
    String bcodmo_name "unknown";
    String description "MOCNESS Number";
    String long_name "MOC";
    String units "unitless";
  }
  Tow_Type {
    String bcodmo_name "tow";
    String description "type of tow";
    String long_name "Tow Type";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.46093208e+9, 1.46222298e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date and time following the ISO8601 format";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String source_name "ISO_DateTime_UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  Date_Local {
    String bcodmo_name "date_local";
    String description "local date in mmddyyyy format";
    String long_name "Date Local";
    String units "unitless";
  }
  Date_UTC {
    String bcodmo_name "date_utc";
    String description "UTC date in mmddyyyy format";
    String long_name "Date UTC";
    String units "unitless";
  }
  Time_In_Local {
    String bcodmo_name "time_local";
    String description "Local time (UTC-700) in following format HHMM.";
    String long_name "Time In Local";
    String units "unitless";
  }
  Time_Out_Local {
    String bcodmo_name "time_local";
    String description "local time (UTC-700) out following format HHMM";
    String long_name "Time Out Local";
    String units "unitless";
  }
  Time_In_UTC {
    String bcodmo_name "unknown";
    String description "UTC time in following format HHMM";
    String long_name "Time In UTC";
    String units "unitless";
  }
  Time_Out_UTC {
    String bcodmo_name "unknown";
    String description "UTC time out following format HHMM";
    String long_name "Time Out UTC";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 21.849, 31.13;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude in decimal degrees with negative values indicating South";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String source_name "Lat_In";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -126.27, -119.931;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude in decimal degrees with negative values indicating West";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "Lon_In";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Lat_Out {
    Float32 _FillValue NaN;
    Float32 actual_range 21.872, 31.145;
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude in decimal degrees with negative values indicating South";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "decimal degrees";
  }
  Lon_Out {
    Float32 _FillValue NaN;
    Float32 actual_range -126.3, -120.001;
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude in decimal degrees with negative values indicating West";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "decimal degrees";
  }
  Day_Night {
    String bcodmo_name "unknown";
    String description "Designator if cast was during the day or night";
    String long_name "Day Night";
    String units "unitless";
  }
  Min_Depth {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 600;
    String bcodmo_name "depth";
    String description "minimum depth";
    String long_name "Min Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String units "meters (m)";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 100.0, 1000.0;
    String axis "Z";
    String bcodmo_name "depth";
    String description "maximum depth";
    String ioos_category "Location";
    String long_name "Max Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Comments {
    String bcodmo_name "unknown";
    String description "additional comments";
    String long_name "Comments";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"See Wishner et al. 2013, 2018, and 2019 (online preprint in review) for
details and results.\\u00a0 Sampling for zooplankton occurred on the upcast
portion of the tow.\\u00a0 Samples were preserved in borate-buffered
formaldehyde at sea.\\u00a0 Zooplankton, especially copepods, were sorted and
identified microscopically later in the lab.\\u00a0\\u00a0";
    String awards_0_award_nid "663014";
    String awards_0_award_number "OCE-1459243";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1459243";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"Date, time, location, and depth range for MOCNESS tows from 2016-04-17 to 2016-05-02 
  PI: Karen Wishner 
  Version: 2020-01-07";
    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 "2020-01-14T19:50:58Z";
    String date_modified "2020-01-30T14:11:29Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.787329.1";
    Float64 Easternmost_Easting -119.931;
    Float64 geospatial_lat_max 31.13;
    Float64 geospatial_lat_min 21.849;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -119.931;
    Float64 geospatial_lon_min -126.27;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 1000.0;
    Float64 geospatial_vertical_min 100.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2021-10-18T17:15:06Z (local files)
2021-10-18T17:15:06Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_787329.html";
    String infoUrl "https://www.bco-dmo.org/dataset/787329";
    String institution "BCO-DMO";
    String instruments_0_acronym "MOCNESS";
    String instruments_0_dataset_instrument_description "1 m2 MOCNESS";
    String instruments_0_dataset_instrument_nid "787340";
    String instruments_0_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_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/NETT0097/";
    String instruments_0_instrument_name "MOCNESS";
    String instruments_0_instrument_nid "511";
    String instruments_0_supplied_name "MOCNESS";
    String keywords "bco, bco-dmo, biological, chemical, comments, cruise, cruise_id, data, dataset, date, Date_Local, Date_UTC, day, Day_Night, depth, dmo, erddap, iso, Lat_Out, latitude, local, Lon_Out, longitude, management, max, Max_Depth, min, Min_Depth, moc, night, oceanography, office, out, preliminary, station, time, Time_In_Local, Time_In_UTC, Time_Out_Local, Time_Out_UTC, tow, Tow_Type, type";
    String license "https://www.bco-dmo.org/dataset/787329/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/787329";
    Float64 Northernmost_Northing 31.13;
    String param_mapping "{'787329': {'Lat_In': 'flag - latitude', 'Lon_In': 'flag - longitude', 'ISO_DateTime_UTC': 'flag - time', 'Max_Depth': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/787329/parameters";
    String people_0_affiliation "University of Rhode Island";
    String people_0_affiliation_acronym "URI-GSO";
    String people_0_person_name "Karen Wishner";
    String people_0_person_nid "50455";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of South Florida";
    String people_1_affiliation_acronym "USF";
    String people_1_person_name "Brad Seibel";
    String people_1_person_nid "51075";
    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 "Mathew Biddle";
    String people_2_person_nid "708682";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Metabolic Index";
    String projects_0_acronym "Metabolic Index";
    String projects_0_description 
"Description from NSF award abstract:
With climate change, ocean temperatures are expected to increase which in turn will reduce oxygen availability and increase metabolic oxygen demand in marine organisms. The investigators will conduct shipboard physiological experiments for various marine organisms and determine their distributions in relation to environmental conditions within an oxygen minimum zone (OMZ) in the Eastern Pacific Ocean. The goal will be to model and map a Metabolic Index (MI) to predict how vertical and horizontal distributions for these species might change throughout the world's oceans in the future. The MI is defined as the ratio between environmental oxygen supply and temperature-dependent oxygen demand. Oxygen supply includes both the environmental oxygen concentration across a habitat range and the physiological features of organisms that facilitate oxygen uptake, such as gills and circulatory systems. Thus, the MI will integrate measured tolerance and environmental exposure to low oxygen with environmental data. The investigators will measure tolerance to low oxygen, focusing on under-studied organisms, including the effect of temperature and organism size. They will sample along a natural gradient in oxygen content south of the California Current in the Eastern Pacific. The science team and a videographer will develop a blog about deep-sea biology and climate change using web-based and video technologies. Four graduate students will be funded on this project, and in conjunction with a recently developed course in pelagic ecology, several undergraduates will have the opportunity to participate in seagoing research.
This research fills a critical need for a physiology-based metric that can be used to predict changing marine communities as the oceans warm and hypoxic zones expand. Modern OMZs are extensive and characterized by deep-water (300-800 m) oxygen partial pressures lethal to most marine organisms, yet thriving communities exist there. Climate change is predicted to further deplete oxygen. The investigators will model and map a Metabolic Index (MI) for diverse marine species to help predict how in vertical and horizontal distributions of species may change throughout the world's oceans in the future. The MI will derive oxygen supply and demand data from published and planned measurements of the minimum environmental partial pressure of oxygen to which individual species are exposed (based on their distributions in the water column) and the minimum requirements to support routine aerobic metabolic demand (from shipboard respiration measurements of individuals). During research cruises in the Eastern Pacific along a gradient of OMZ intensity, the investigators will conduct shipboard physiological measurements to determine metabolic demand for understudied mesozooplankton and gelatinous taxa and determine the size- and temperature dependence for diverse species for incorporation into the MI. Vertically-stratified net sampling and in situ photography will identify and characterize unique OMZ community features, such as the lower oxycline biomass peak present in some OMZs and the oxygen-dependence of day and night habitat depths for vertically-migrating species. The MI will be mapped using climatological data to both test and generate hypotheses about the response of oceanic communities to climate change. In preliminary analysis, the MI suggests a metabolic constraint at a MI of ~2 that may act to limit vertical and horizontal habitat ranges.";
    String projects_0_end_date "2018-09";
    String projects_0_geolocation "Eastern Tropical North Pacific";
    String projects_0_name "Collaborative Research: A metabolic index to predict the consequences of climate change for midwater ecosystems";
    String projects_0_project_nid "663015";
    String projects_0_start_date "2015-10";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 21.849;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "cruise_id";
    String summary "Date, time, location, and depth range for MOCNESS tows";
    String time_coverage_end "2016-05-02T21:03:00Z";
    String time_coverage_start "2016-04-17T22:28:00Z";
    String title "Date, time, location, and depth range for MOCNESS tows from R/V Oceanus in the Eastern Tropical Pacific, Tropical Eastern Pacific from 2016-04-17 to 2016-05-02";
    String version "1";
    Float64 Westernmost_Easting -126.27;
    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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