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Dataset Title:	Zooplankton timeseries Marseille bay (NetCDF files)
Institution:	MIO UMR 7294 CNRS   (Dataset ID: mio_carlotti_zooplankton_54fe_0d31_5b8b)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Subset | Files | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum    or a List of Values	Maximum
station_name	!= =~ <= >= = < >		!= =~ <= >= = < >		"Marseille Bay"
time (datetime, UTC)	!= =~ <= >= = < >		!= =~ <= >= = < >		2005-02-10T00:00:00Z	2020-12-16T00:00:00Z
latitude (degrees_north)	!= =~ <= >= = < >		!= =~ <= >= = < >		43.2417
longitude (degrees_east)	!= =~ <= >= = < >		!= =~ <= >= = < >		5.29167
depth (m)	!= =~ <= >= = < >		!= =~ <= >= = < >		60
biomass_fraction_gt_2000_um (mg DW.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	63.04
biomass_fraction_1000_2000_um (mg DW.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	24.57
biomass_fraction_500_1000_um (mg DW.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.04	24.31
biomass_fraction_300_500_um (mg DW.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.08	14.8
biomass_fraction_200_300_um (mg DW.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	22.92
biomass_fraction_80_200_um (mg DW.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	5.43
Total_biomass (mg DW.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	74.06
Bivalvia (Bivalvia abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	140.19
Chaetognatha (Chaetognatha abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.14	105.08
Calanoida (nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		59.74	12955.07
Oithonoida (Oithonoida abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		7.27	979.79
Ergasilida (Ergasilida abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		7.98	554.62
Harpacticoida (Harpacticoida abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	185.36
Fish_Eggs (Fish Eggs abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	117.77
Nauplii (Nauplii abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		3.14	316.59
Salpida (Salpida abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.21	203.03
Crustacea (Crustacea abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		3.56	1811.7
Pteropoda (Pteropoda abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.29	435.24
Appendicularia (nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.29	1068.9
Cnidaria (Cnidaria abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		2.28	250.36
Others (others groups abundance, nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		5.28	574.13
Total_Abundance (nb.m-3)	!= =~ <= >= = < >		!= =~ <= >= = < >		115.63	14611.95

 

Server-side Functions

distinct()

orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" station_name time latitude longitude depth biomass_fraction_gt_2000_um biomass_fraction_1000_2000_um biomass_fraction_500_1000_um biomass_fraction_300_500_um biomass_fraction_200_300_um biomass_fraction_80_200_um Total_biomass Bivalvia Chaetognatha Calanoida Oithonoida Ergasilida Harpacticoida Fish_Eggs Nauplii Salpida Crustacea Pteropoda Appendicularia Cnidaria Others Total_Abundance station_name time latitude longitude depth biomass_fraction_gt_2000_um biomass_fraction_1000_2000_um biomass_fraction_500_1000_um biomass_fraction_300_500_um biomass_fraction_200_300_um biomass_fraction_80_200_um Total_biomass Bivalvia Chaetognatha Calanoida Oithonoida Ergasilida Harpacticoida Fish_Eggs Nauplii Salpida Crustacea Pteropoda Appendicularia Cnidaria Others Total_Abundance station_name time latitude longitude depth biomass_fraction_gt_2000_um biomass_fraction_1000_2000_um biomass_fraction_500_1000_um biomass_fraction_300_500_um biomass_fraction_200_300_um biomass_fraction_80_200_um Total_biomass Bivalvia Chaetognatha Calanoida Oithonoida Ergasilida Harpacticoida Fish_Eggs Nauplii Salpida Crustacea Pteropoda Appendicularia Cnidaria Others Total_Abundance station_name time latitude longitude depth biomass_fraction_gt_2000_um biomass_fraction_1000_2000_um biomass_fraction_500_1000_um biomass_fraction_300_500_um biomass_fraction_200_300_um biomass_fraction_80_200_um Total_biomass Bivalvia Chaetognatha Calanoida Oithonoida Ergasilida Harpacticoida Fish_Eggs Nauplii Salpida Crustacea Pteropoda Appendicularia Cnidaria Others Total_Abundance station_name time latitude longitude depth biomass_fraction_gt_2000_um biomass_fraction_1000_2000_um biomass_fraction_500_1000_um biomass_fraction_300_500_um biomass_fraction_200_300_um biomass_fraction_80_200_um Total_biomass Bivalvia Chaetognatha Calanoida Oithonoida Ergasilida Harpacticoida Fish_Eggs Nauplii Salpida Crustacea Pteropoda Appendicularia Cnidaria Others Total_Abundance ")

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .dataTable - A JSON file formatted for use with the Google Visualization client library (Google Charts). .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriCsv - Download a ISO_8859_1 .csv file for ESRI's ArcGIS 9.x and below (separate date and time columns). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .geoJson - Download longitude,latitude,otherColumns data as a UTF-8 GeoJSON .json file. .graph - View a Make A Graph web page. .help - View a web page with a description of tabledap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each response column becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a flat, table-like, NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncCF - Download a NetCDF-3 CF Discrete Sampling Geometries file (Contiguous Ragged Array). .ncCFHeader - View the UTF-8 header (the metadata) for the .ncCF file. .ncCFMA - Download a NetCDF-3 CF Discrete Sampling Geometries file (Multidimensional Array). .ncCFMAHeader - View the UTF-8 header (the metadata) for the .ncCFMA file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download longitude,latitude,time,otherColumns as an ISO-8859-1 ODV Generic Spreadsheet File (.txt). .subset - View an HTML form which uses faceted search to simplify picking subsets of the data. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .kml - View a .kml file, suitable for Google Earth. .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  station_name {
    String cf_role "timeseries_id";
    String ioos_category "Identifier";
    String long_name "Station Name";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.1079936e+9, 1.6080768e+9;
    String axis "T";
    String calendar "julian";
    String ioos_category "Time";
    String long_name "datetime";
    String origin "01-JAN-1970 00:00:00";
    String source_name "datetime";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 43.2417, 43.2417;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 5.29167, 5.29167;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 _FillValue 2147483647;
    Int32 actual_range 60, 60;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  biomass_fraction_gt_2000_um {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 63.04;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Unknown";
    String long_name "biomass fraction > 2000 um";
    String standard_name "biomass fraction > 2000 um";
    String units "mg DW.m-3";
  }
  biomass_fraction_1000_2000_um {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 24.57;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Unknown";
    String long_name "biomass fraction 1000-2000 um";
    String standard_name "biomass fraction 1000-2000 um";
    String units "mg DW.m-3";
  }
  biomass_fraction_500_1000_um {
    Float32 _FillValue NaN;
    Float32 actual_range 0.04, 24.31;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Unknown";
    String long_name "biomass fraction 500-1000 um";
    String standard_name "biomass fraction 500-1000 um";
    String units "mg DW.m-3";
  }
  biomass_fraction_300_500_um {
    Float32 _FillValue NaN;
    Float32 actual_range 0.08, 14.8;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Unknown";
    String long_name "biomass fraction 300-500 um";
    String standard_name "biomass fraction 300-500 um";
    String units "mg DW.m-3";
  }
  biomass_fraction_200_300_um {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 22.92;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Unknown";
    String long_name "biomass fraction 200-300 um";
    String standard_name "biomass fraction 200-300 um";
    String units "mg DW.m-3";
  }
  biomass_fraction_80_200_um {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 5.43;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Unknown";
    String long_name "biomass fraction 80-200 um";
    String standard_name "biomass fraction 80-200 um";
    String units "mg DW.m-3";
  }
  Total_biomass {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 74.06;
    String ioos_category "Unknown";
    String long_name "total biomass";
    String standard_name "total biomass";
    String units "mg DW.m-3";
  }
  Bivalvia {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 140.19;
    String ioos_category "Unknown";
    String long_name "Bivalvia abundance";
    String standard_name "sdn:p01::z510m00z";
    String units "nb.m-3";
  }
  Chaetognatha {
    Float32 _FillValue NaN;
    Float32 actual_range 0.14, 105.08;
    String ioos_category "Unknown";
    String long_name "Chaetognatha abundance";
    String standard_name "sdn:p01::z130m00z";
    String units "nb.m-3";
  }
  Calanoida {
    Float32 _FillValue NaN;
    Float32 actual_range 59.74, 12955.07;
    String ioos_category "Unknown";
    String long_name "Calanoida";
    String standard_name "sdn:p01::z366m00z";
    String units "nb.m-3";
  }
  Oithonoida {
    Float32 _FillValue NaN;
    Float32 actual_range 7.27, 979.79;
    String ioos_category "Unknown";
    String long_name "Oithonoida abundance";
    String standard_name "sdn::p01:z306m00z";
    String units "nb.m-3";
  }
  Ergasilida {
    Float32 _FillValue NaN;
    Float32 actual_range 7.98, 554.62;
    String ioos_category "Unknown";
    String long_name "Ergasilida abundance";
    Float64 standard_name NaN;
    String units "nb.m-3";
  }
  Harpacticoida {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 185.36;
    String ioos_category "Unknown";
    String long_name "Harpacticoida abundance";
    String standard_name "sdn:p01::z363m00z";
    String units "nb.m-3";
  }
  Fish_Eggs {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 117.77;
    String ioos_category "Biology";
    String long_name "Fish Eggs abundance";
    String standard_name "sdn:p01::z830m00t";
    String units "nb.m-3";
  }
  Nauplii {
    Float32 _FillValue NaN;
    Float32 actual_range 3.14, 316.59;
    String ioos_category "Unknown";
    String long_name "Nauplii abundance";
    String standard_name "sdn:p01::zu03m00z";
    String units "nb.m-3";
  }
  Salpida {
    Float32 _FillValue NaN;
    Float32 actual_range 0.21, 203.03;
    String ioos_category "Unknown";
    String long_name "Salpida abundance";
    String standard_name "sdn:p01::sal10052";
    String units "nb.m-3";
  }
  Crustacea {
    Float32 _FillValue NaN;
    Float32 actual_range 3.56, 1811.7;
    String ioos_category "Unknown";
    String long_name "Crustacea abundance";
    String standard_name "sdn:p01::acr01605";
    String units "nb.m-3";
  }
  Pteropoda {
    Float32 _FillValue NaN;
    Float32 actual_range 0.29, 435.24;
    String ioos_category "Unknown";
    String long_name "Pteropoda abundance";
    String standard_name "sdn:p01::c97a5113";
    String units "nb.m-3";
  }
  Appendicularia {
    Float32 _FillValue NaN;
    Float32 actual_range 0.29, 1068.9;
    String ioos_category "Unknown";
    String long_name "Appendicularia abundance";
    String standard_name "sdn:p01::g146m00z";
    String units "nb.m-3";
  }
  Cnidaria {
    Float32 _FillValue NaN;
    Float32 actual_range 2.28, 250.36;
    String ioos_category "Unknown";
    String long_name "Cnidaria abundance";
    String standard_name "sdn:p01::acx08115";
    String units "nb.m-3";
  }
  Others {
    Float32 _FillValue NaN;
    Float32 actual_range 5.28, 574.13;
    String ioos_category "Unknown";
    String long_name "others groups abundance";
    String standard_name "others groups abundance";
    String units "nb.m-3";
  }
  Total_Abundance {
    Float32 _FillValue NaN;
    Float32 actual_range 115.63, 14611.95;
    String ioos_category "Unknown";
    String long_name "total abundance";
    String standard_name "total abundance";
    String units "nb.m-3";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "TimeSeries";
    String cdm_timeseries_variables "station_name,latitude,longitude";
    String contact "francois.carlotti@mio.osupytheas.fr";
    String contributor_name "maurice.libes@osupytheas.fr";
    String contributor_name2 "Loic Guilloux; Theo Garcia; Salome Chen; Katty Donoso; Antoine Nowaxzyk; Virginie Riandey; Emmanuel Dieval; Karim Morsly; Nada Neffati; Baptiste Lebourg; Antony Dron";
    String contributor_role "raw data conversion, and data formating in NetCDF";
    String contributor_role2 "sampling and processing of the samples";
    String Conventions "SeaDataNet_1.0,COARDS, CF-1.10, ACDD-1.3";
    String creator_email "francois.carlotti@mio.osupytheas.fr";
    String creator_name "Francois Carlotti";
    String creator_type "person";
    String data_type "time-series data";
    String date_created "2023-07-19";
    String defaultGraphQuery "time%2Cbiomass_fraction_80_200_um%2C&.draw=linesAndMarkers&.marker=6|3&.color=0x000000&.colorBar=|||||&.bgColor=0xffccccff";
    String doi "10.34930/6da3237c-4732-4c71-b7f1-140c7b2dcdaa";
    Float64 Easternmost_Easting 5.29167;
    String featureType "TimeSeries";
    String featuretype "timeseries";
    Float64 geospatial_lat_max 43.2417;
    Float64 geospatial_lat_min 43.2417;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 5.29167;
    Float64 geospatial_lon_min 5.29167;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 60.0;
    Float64 geospatial_vertical_min 60.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"The sampling is carried out twice a month at a fixed station in the center of the bay of Marseille (43.2417 N; 5.29167 E) with a depth of 60m (see https://www.somlit.fr/marseille/ ).  The WP2 net (200?m mesh) is hauled vertically from 55 to the surface. Sample preserved in 4% buffered formalin and stored over the long term at the MIO.  Sample have bee scanned on a ZooScan, images processed with ZooProcess and sorted taxonomically on Particle Trieur, within the Plateforme Microscopie et IMagerie (MIM).
2024-10-30T05:42:48Z (local files)
2024-10-30T05:42:48Z http://erddap.osupytheas.fr/erddap/tabledap/mio_carlotti_zooplankton_54fe_0d31_5b8b.html";
    String infoUrl "https://dataset.osupytheas.fr/geonetwork/srv/fre/catalog.search#/metadata/6da3237c-4732-4c71-b7f1-140c7b2dcdaa";
    String institution "MIO UMR 7294 CNRS";
    String institution_edmo_code "3078";
    String institution_edmo_uri "https://edmo.seadatanet.org/report/3078";
    String keywords "abundance, abundances, acr01605, acx08115, appendicularia, baie de marseille, bay, biology, biomass, bivalvia, c97a5113, calanoida, chaetognatha, cnidaria, cnrs, crustacea, data, depth, eggs, ergasilida, files, fish, Fish_Eggs, fraction_1000_2000_um, fraction_2000_um, fraction_200_300_um, fraction_300_500_um, fraction_500_1000_um, fraction_80_200_um, g146m00z, groups, harpacticoida, identifier, latitude, longitude, marseille, mio, name, nauplii, oithonoida, osu pytheas, others, others groups abundance, p01, pteropoda, sal10052, salpida, sdn, sdn::p01:z306m00z, sdn:p01::acr01605, sdn:p01::acx08115, sdn:p01::c97a5113, sdn:p01::g146m00z, sdn:p01::sal10052, sdn:p01::z130m00z, sdn:p01::z363m00z, sdn:p01::z366m00z, sdn:p01::z510m00z, sdn:p01::z830m00t, sdn:p01::zu03m00z, serie temporelle, size fractions, station, station_name, time, timeserie, timeseries, total, total abundance, total biomass, Total_Abundance, Total_biomass, umr, z130m00z, z306m00z, z363m00z, z366m00z, z510m00z, z830m00t, zooplancton, zooplankton, zu03m00z";
    String license "CC-BY-4.0";
    String license_uri "https://creativecommons.org/licenses/by/4.0/";
    String network "SOMLIT https://www.somlit.fr/marseille/";
    Float64 Northernmost_Northing 43.2417;
    String principal_investigator "Francois Carlotti";
    String principal_investigator_email "francois.carlotti@mio.osupytheas.fr";
    String project "SOMLIT : Zooplankton timeseries Marseille bay";
    String qc_indicator "good values";
    String request_for_aknowledgement "If you use these data in publications or presentation, please acknowledge francois.carlotti@mio.osupytheas.fr (of OSU Pytheas).  Also, we would appreciate receiving a preprint and/or reprint of publications using the data for inclusion in our bibliography. Relevant publications should be sent to: patrick.raimbault@mio.osupytheas.fr MIO UMR 7294 CNRS, Campus de Luminy 13288 Marseille cedex9";
    String source "MIO UMR 7294 CNRS";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 43.2417;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "station_name, latitude, longitude, depth";
    String summary "This series is part of the long-term planktonic monitoring of Marseille Oceanographic Laboratories (successively Centre Océanographique de Marseille, Laboratoire d’Océanographie Biologique, Laboratoire d’Océanographie Physique et Biogéochimique, and presently Mediterranean Institute of oceanography / OSU Pytheas ).  It aims at describing the dynamics of the mesozooplankton community both in term of biomass and taxonomic groups.  This dataset contains the planktonic organisms collected by a WP2 net (Diameter 55 cm; Length : 3 m; Mesh size: 200μm mesh) and therefore covering zooplanktonic organisms from 200µm to ~2cm.  The sampling is carried out twice a month at a fixed station in the center of the bay of Marseille (43.2417°N; 5.29167°E) with a depth of 60m (see https://www.somlit.fr/marseille/ ).  The WP2 net (200μm mesh) is hauled vertically from 55 to the surface. Sample preserved in 4% buffered formalin and stored over the long term at the MIO.  Sample have bee scanned on a ZooScan, images processed with ZooProcess and sorted taxonomically on Particle Trieur, within the Plateforme Microscopie et IMagerie (MIM).  The data collection and processing has been funded by several projects over its lifetime. It is currently supported directly by the Mediterranean Institute of oceanography (MIO), as part of its long-term monitoring effort associated with SOMLIT. (https://www.somlit.fr/marseille/). Sont remerciés pour leur contributions à l’échantillonnage et/ou au traitement des échantillons Loic Guilloux; Theo Garcia; Salome Chen; Katty Donoso; Antoine Nowaxzyk; Virginie Riandey; Emmanuel Dieval; Karim Morsly; Nada Neffati; Baptiste Lebourg; Antony Dron";
    String time_coverage_end "2020-12-16T00:00:00Z";
    String time_coverage_start "2005-02-10T00:00:00Z";
    String title "Zooplankton timeseries Marseille bay (NetCDF files)";
    Float64 Westernmost_Easting 5.29167;
  }
}

 

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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 2.23
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