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Dataset Title:	[AE1910 CTD Bottles] - Bottle data from R/V Atlantic Explorer cruise AE1910 during May 2019 (Collaborative Research: Diel physiological rhythms in a tropical oceanic copepod)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_774859)
Range:	longitude = -64.7887 to -64.4947°E, latitude = 32.1698 to 32.571°N, depth = 2.436 to 999.82m, time = 2019-05-20T16:18:15Z to 2019-05-23T14:23:52Z
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Subset | Data Access Form | Files

 

Graph Type:  lines linesAndMarkers markers sticks vectors X Axis:  cast latitude longitude Bottle Year Month Day depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time Y Axis:  cast latitude longitude Bottle Year Month Day depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time Color:  cast latitude longitude Bottle Year Month Day depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time   Constraints Optional Constraint #1 Optional Constraint #2 cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time     != =~ <= >= = < >     != =~ <= >= = < >     cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time     != =~ <= >= = < >     != =~ <= >= = < >     cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time     != =~ <= >= = < >     != =~ <= >= = < >     cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time     != =~ <= >= = < >     != =~ <= >= = < >     cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time     != =~ <= >= = < >     != =~ <= >= = < >       Server-side Functions  distinct() orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time cast latitude longitude Bottle Year Month Day Hours Minutes Seconds depth DepSM_stdev AltM_avg AltM_stdev CStarTr0_avg CStarTr0_stdev C0S_m_avg C0S_m_stdev FlC_avg FlC_stdev Sbeox0_avg Sbeox0_stdev Par_avg Par_stdev PrDE_avg PrDE_stdev Sal00_avg Sal00_stdev T090C_avg T090C_stdev Sigma_e00_avg Sigma_e00_stdev Scan_avg Scan_stdev time ")   Graph Settings Marker Type:  None Plus X Dot Square Filled Square Circle Filled Circle Up Triangle Filled Up Triangle Borderless Filled Square Borderless Filled Circle Borderless Filled Up Triangle  Size:  3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Color:  Color Bar:  BlackBlueWhite BlackGreenWhite BlackRedWhite BlackWhite BlueWhiteRed BlueWideWhiteRed LightRainbow Ocean OceanDepth Rainbow Rainbow2 Rainfall ReverseRainbow RedWhiteBlue RedWhiteBlue2 RedWideWhiteBlue Spectrum Topography TopographyDepth WhiteBlueBlack WhiteGreenBlack WhiteRedBlack WhiteBlack YellowRed KT_algae KT_amp KT_balance KT_curl KT_deep KT_delta KT_dense KT_gray KT_haline KT_ice KT_matter KT_oxy KT_phase KT_solar KT_speed KT_tempo KT_thermal KT_turbid  Continuity:  Continuous Discrete  Scale:  Linear Log    Minimum:   Maximum:   N Sections:  2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Draw land mask:  under over outline off Y Axis Minimum:   Maximum:    Ascending Descending Linear Log   Redraw the Graph (Please be patient. It may take a while to get the data.)   Optional: Then set the File Type: .asc .csv .csvp .csv0 .dataTable .das .dds .dods .esriCsv .fgdc .geoJson .graph .help .html .htmlTable .iso19115 .itx .json .jsonlCSV1 .jsonlCSV .jsonlKVP .mat .nc .ncHeader .ncCF .ncCFHeader .ncCFMA .ncCFMAHeader .nccsv .nccsvMetadata .ncoJson .odvTxt .subset .tsv .tsvp .tsv0 .wav .xhtml .kml .smallPdf .pdf .largePdf .smallPng .png .largePng .transparentPng (File Type information) and or view the URL: (Documentation / Bypass this form )

Click on the map to specify a new center point. Zoom:  Time range:  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 second(s) minute(s) hour(s) day(s) month(s) year(s)

 

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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.
   

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  cast {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 8;
    String bcodmo_name "cast";
    String description "CTD cast number (based on file name)";
    String long_name "Cast";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 32.1698, 32.571;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "NMEA Latitude from bottle file header; 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 -64.7887, -64.4947;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "NMEA Longitude from bottle file header; 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";
  }
  Bottle {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 24;
    String bcodmo_name "bottle";
    String description "Bottle number";
    String long_name "Bottle";
    String units "unitless";
  }
  Year {
    Int16 _FillValue 32767;
    Int16 actual_range 2019, 2019;
    String bcodmo_name "year";
    String description "Four digit year; format: YYYY";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  }
  Month {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 5, 5;
    String bcodmo_name "month";
    String description "One digit month (5 = May)";
    String long_name "Month";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MNTHXXXX/";
    String units "unitless";
  }
  Day {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 20, 23;
    String bcodmo_name "day";
    String description "Two digit day of month";
    String long_name "Day";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DAYXXXXX/";
    String units "unitless";
  }
  Hours {
    String bcodmo_name "hour_gmt";
    String description "Two digit hours portion of time";
    String long_name "Hours";
    String units "unitless";
  }
  Minutes {
    String bcodmo_name "minute_gmt";
    String description "Two digit minutes portion of time";
    String long_name "Minutes";
    String units "unitless";
  }
  Seconds {
    String bcodmo_name "seconds_gmt";
    String description "Two digit seconds portion of time";
    String long_name "Seconds";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 2.436, 999.82;
    String axis "Z";
    String bcodmo_name "depth";
    String description "Depth average";
    String ioos_category "Location";
    String long_name "Dep SM Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  DepSM_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.025, 0.604;
    String bcodmo_name "depth";
    String description "Depth standard deviation";
    String long_name "Dep SM Stdev";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String units "meters (m)";
  }
  AltM_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 58.4, 99.52;
    String bcodmo_name "altitude";
    String description "Altimeter average";
    String long_name "Alt M Avg";
    String units "meters (m)";
  }
  AltM_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 46.28;
    String bcodmo_name "altitude";
    String description "Altimeter standard deviation";
    String long_name "Alt M Stdev";
    String units "meters (m)";
  }
  CStarTr0_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 123.293, 126.3652;
    String bcodmo_name "transmission";
    String description "Beam transmission (WET Labs C-Star) average";
    String long_name "CStar Tr0 Avg";
    String units "percent?";
  }
  CStarTr0_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.3265;
    String bcodmo_name "transmission";
    String description "Beam transmission (WET Labs C-Star) standard deviation";
    String long_name "CStar Tr0 Stdev";
    String units "percent?";
  }
  C0S_m_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 3.60054, 5.442266;
    String bcodmo_name "conductivity";
    String description "Conductivity average";
    String long_name "C0 S M Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/CNDC/";
    String units "siemens per meter (S/m)";
  }
  C0S_m_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 2.9e-5, 0.003884;
    String bcodmo_name "conductivity";
    String description "Conductivity standard deviation";
    String long_name "C0 S M Stdev";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/CNDC/";
    String units "siemens per meter (S/m)";
  }
  FlC_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0159, 0.3065;
    String bcodmo_name "fluorescence";
    String description "Fluorescence (Chelsea Aqua 3) average";
    String long_name "Fl C Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
    String units "micrograms per liter (ug/L)";
  }
  FlC_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 4.0e-4, 0.0132;
    String bcodmo_name "fluorescence";
    String description "Fluorescence (Chelsea Aqua 3) standard deviation";
    String long_name "Fl C Stdev";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
    String units "micrograms per liter (ug/L)";
  }
  Sbeox0_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 138.62, 214.167;
    String bcodmo_name "dissolved Oxygen";
    String description "Oxygen (SBE 43) average (Named \"Sbeox0Mm/Kg in original CTD file; renamed to avoid confusion because units of measurement are actually umol/kg.)";
    String long_name "Sbeox0 Avg";
    String units "micromoles per kilogram (umol/kg)";
  }
  Sbeox0_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.029, 0.982;
    String bcodmo_name "dissolved Oxygen";
    String description "Oxygen (SBE 43) standard deviation. (Named \"Sbeox0Mm/Kg in original CTD file; renamed to avoid confusion because units of measurement are actually umol/kg.)";
    String long_name "Sbeox0 Stdev";
    String units "micromoles per kilogram (umol/kg)";
  }
  Par_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 1.0e-12, 769.0;
    String bcodmo_name "PAR";
    String description "PAR/Irradiance (Biospherical/Licor) average";
    String long_name "Par Avg";
    String units "?";
  }
  Par_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 84.2;
    String bcodmo_name "PAR";
    String description "PAR/Irradiance (Biospherical/Licor) standard deviation";
    String long_name "Par Stdev";
    String units "?";
  }
  PrDE_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 3.558, 1463.861;
    String bcodmo_name "pressure";
    String description "Pressure average";
    String long_name "Pr DE Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PRESPR01/";
    String units "psi";
  }
  PrDE_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 0.037, 0.887;
    String bcodmo_name "pressure";
    String description "Pressure standard deviation";
    String long_name "Pr DE Stdev";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PRESPR01/";
    String units "psi";
  }
  Sal00_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 35.1311, 36.966;
    String bcodmo_name "sal";
    String description "Salinity average";
    String long_name "Sal00 Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "PSU";
  }
  Sal00_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 3.0e-4, 0.0089;
    String bcodmo_name "sal";
    String description "Salinity standard deviation";
    String long_name "Sal00 Stdev";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "PSU";
  }
  T090C_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 7.1361, 23.8432;
    String bcodmo_name "temperature";
    String description "Temperature average";
    String long_name "T090 C Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "ITS-90, degrees C";
  }
  T090C_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 2.0e-4, 0.0327;
    String bcodmo_name "temperature";
    String description "Temperature standard deviation";
    String long_name "T090 C Stdev";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "ITS-90, degrees C";
  }
  Sigma_e00_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 25.1636, 27.5405;
    String bcodmo_name "sigma_theta";
    String description "Density [sigma-theta] average";
    String long_name "Sigma E00 Avg";
    String units "kilograms per cubic meter (kg/m^3)";
  }
  Sigma_e00_stdev {
    Float32 _FillValue NaN;
    Float32 actual_range 2.0e-4, 0.0097;
    String bcodmo_name "sigma_theta";
    String description "Density [sigma-theta] standard deviation";
    String long_name "Sigma E00 Stdev";
    String units "kilograms per cubic meter (kg/m^3)";
  }
  Scan_avg {
    Int32 _FillValue 2147483647;
    Int32 actual_range 17796, 100471;
    String bcodmo_name "scan";
    String description "Scan number average";
    String long_name "Scan Avg";
    String units "unitless";
  }
  Scan_stdev {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 14, 14;
    String bcodmo_name "scan";
    String description "Scan number standard deviation";
    String long_name "Scan Stdev";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.558369095e+9, 1.558621432e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date and time (UTC) formatted to ISO8601 standard; format: YYYY-mm-ddTHH:MM:SSZ";
    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";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"The CTD + 24 bottle sampling rosette was run using standard operating
procedures. The bottles were fired on the up cast, 30 seconds after the unit
was stopped.";
    String awards_0_award_nid "764113";
    String awards_0_award_number "OCE-1829318";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1829318";
    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 awards_1_award_nid "764119";
    String awards_1_award_number "OCE-1829378";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1829378";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "David L. Garrison";
    String awards_1_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"CTD Bottle Files 
   from R/V Atlantic Explorer cruise AE1910 
  PI: Amy Maas (BIOS) 
  Co-PIs: Leocadio Blanco-Bercial (BIOS) & Ann Tarrant (WHOI) 
  Version date: 29-August-2019";
    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 "2019-08-07T19:59:40Z";
    String date_modified "2019-09-25T16:38:27Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.774859.1";
    Float64 Easternmost_Easting -64.4947;
    Float64 geospatial_lat_max 32.571;
    Float64 geospatial_lat_min 32.1698;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -64.4947;
    Float64 geospatial_lon_min -64.7887;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 999.82;
    Float64 geospatial_vertical_min 2.436;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-08T06:14:31Z (local files)
2024-11-08T06:14:31Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_774859.das";
    String infoUrl "https://www.bco-dmo.org/dataset/774859";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_nid "774870";
    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_1_acronym "CTD SBE 911plus";
    String instruments_1_dataset_instrument_nid "774869";
    String instruments_1_description "The Sea-Bird SBE 911plus is a type of CTD instrument package for continuous measurement of conductivity, temperature and pressure.  The SBE 911plus includes the SBE 9plus Underwater Unit and the SBE 11plus Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9plus and SBE 11plus is called a SBE 911plus.  The SBE 9plus uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3plus and SBE 4). The SBE 9plus CTD can be configured with up to eight auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorescence, light (PAR), light transmission, etc.). more information from Sea-Bird Electronics";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0058/";
    String instruments_1_instrument_name "CTD Sea-Bird SBE 911plus";
    String instruments_1_instrument_nid "591";
    String instruments_1_supplied_name "Sea-Bird SBE 9 11+ V 5.2";
    String keywords "AltM_avg, AltM_stdev, available, average, bco, bco-dmo, biological, bottle, C0S_m_avg, C0S_m_stdev, cast, chemical, cstar, CStarTr0_avg, CStarTr0_stdev, data, dataset, date, day, dep, DepSM_avg, DepSM_stdev, deviation, dmo, e00, erddap, FlC_avg, FlC_stdev, hours, iso, latitude, longitude, management, minutes, month, oceanography, office, par, Par_avg, Par_stdev, photosynthetically, PrDE_avg, PrDE_stdev, preliminary, radiation, sal00, Sal00_avg, Sal00_stdev, sbeox0, Sbeox0_avg, Sbeox0_stdev, scan, Scan_avg, Scan_stdev, seconds, sigma, Sigma_e00_avg, Sigma_e00_stdev, standard, standard deviation, stdev, t090, T090C_avg, T090C_stdev, time, tr0, year";
    String license "https://www.bco-dmo.org/dataset/774859/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/774859";
    Float64 Northernmost_Northing 32.571;
    String param_mapping "{'774859': {'latitude': 'flag - latitude', 'DepSM_avg': 'flag - depth', 'longitude': 'flag - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/774859/parameters";
    String people_0_affiliation "Bermuda Institute of Ocean Sciences";
    String people_0_affiliation_acronym "BIOS";
    String people_0_person_name "Amy Maas";
    String people_0_person_nid "51589";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Bermuda Institute of Ocean Sciences";
    String people_1_affiliation_acronym "BIOS";
    String people_1_person_name "Leocadio Blanco-Bercial";
    String people_1_person_nid "51108";
    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";
    String people_2_person_name "Ann M. Tarrant";
    String people_2_person_nid "51430";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    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 "Zooplankton Diel Rhythm";
    String projects_0_acronym "Zooplankton Diel Rhythm";
    String projects_0_description 
"NSF Award Abstract:
The daily vertical migration (DMV) of zooplankton and fish across hundreds of meters between shallow and deep waters is a predominant pattern in pelagic ecosystems. This migration has consequences for biogeochemical cycling as it moves a substantial portion of fixed carbon and nitrogen (an estimated 15 to 40 % of the total global organic export) from the surface directly to depth where it feeds the midwater food chain and sequesters nutrients away from atmospheric mixing. Estimates and predictions of these fluxes are, however, poorly understood at present. New observations have shown that one source of uncertainty is due to the assumption that metabolic rates and processes do not vary over the course of the day, except based on changes in temperature and oxygen availability. Rates are, however, also driven by differences in feeding, swimming behavior, and underlying circadian cycles. The objective of this project is to improve the ability of scientists to understand and predict zooplankton contributions to the movement of carbon and nitrogen in the ocean by detailing daily changes in physiological processes of these organisms. By producing a set of respiration and excretion measurements over a daily time series, paired with simultaneously collected gene and protein expression patterns for an abundant vertically migratory species, the investigators will provide unprecedented and predictive insight into how changes in the environment affect the contribution of zooplankton to biogeochemical fluxes. The sampling design of the project will advance discovery and understanding by providing hands-on training opportunities to at least two undergraduate researchers. The project will broaden dissemination of the research via development of an educational module, focusing on rhythms in the ocean. The module will initially be piloted with the Bermuda Institute of Ocean Sciences (BIOS) summer camp students and then disseminated through the BIOS Explorer program, the Teacher Resources Page on the BIOS website, and published in a peer-reviewed educational journal.
This project will characterize the metabolic consequences of daily physiological rhythms and DVM for a model zooplankton species, the abundant subtropical copepod Pleuromamma xiphias. Flux processes (oxygen consumption, carbon dioxide production, production of ammonium and fecal pellet production) will be interrogated using directed experiments testing the effects of temperature, feeding and circadian cycle. Circadian cycling will further be examined using transcriptomic and proteomic profiling. These experiments will be related to field samples taken at 6-h intervals over the course of the diel migration using an integrated suite of molecular and organismal metrics. Combined organismal, transcriptomic and proteomic profiles will provide an understanding of which metabolic pathways and associated flux products vary in relation to particular environmental variables (food, light cycle, temperature). Diel variation in metabolic rates will also be assessed across seasons and species using other important migratory groups (pteropod, euphausiid, and another copepod). The metabolic data will then be contextualized with abundance estimates from archived depth-stratified tows to allow scaling to community-level patterns and will be used to improve calculations of zooplankton contribution to particulate organic carbon, nitrogen and respiratory active flux. The results of this study will both improve our flux estimates and provide predictive insight into how various environmental variables influence the underlying physiological pathways generating carbon and nitrogen flux.
Cruise reports are available from the completed cruises:SD031019AE1910AE1918";
    String projects_0_end_date "2021-09";
    String projects_0_geolocation "Bermuda";
    String projects_0_name "Collaborative Research: Diel physiological rhythms in a tropical oceanic copepod";
    String projects_0_project_nid "764114";
    String projects_0_start_date "2018-10";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 32.1698;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "Year,Month,Scan_stdev";
    String summary "Bottle data from R/V Atlantic Explorer cruise AE1910 during May 2019.";
    String time_coverage_end "2019-05-23T14:23:52Z";
    String time_coverage_start "2019-05-20T16:18:15Z";
    String title "[AE1910 CTD Bottles] - Bottle data from R/V Atlantic Explorer cruise AE1910 during May 2019 (Collaborative Research: Diel physiological rhythms in a tropical oceanic copepod)";
    String version "1";
    Float64 Westernmost_Easting -64.7887;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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 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.

• (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.

 

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ERDDAP, Version 2.22
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