This dataset is composed of 1,153,507 zooplankton individuals, zooplankton parts, non-living particles and imaging artefacts, ranging from 300 µm to 3.39 mm Equivalent Spherical Diameter, individually imaged and measured with the ZooScan (Gorsky et al., 2010). The objects were sorted in 127 taxonomic and morphological groups. The imaged objects originate from samples collected on the Bay of Biscay continental shelf, in spring, from 2004 to 2016 during the PELGAS ecosystemic surveys (Doray et al., 2018). The samples were collected with a WP2 200 µm mesh size fitted with a Hydrobios (back-run stop) mechanical flowmeter, generally from 100 m depth to the surface, or 5 m above the sea floor (if bottom depth less than 100 m) in vertical hauls, at night. From 2004 to 2006, vertical WP2 net tows were performed in the anchovy core distribution area in the southern Bay of Biscay and North of it until the Loire estuary only. Since 2009, WP2 sampling has been carried out at all PELGAS stations, up to the southern coast of Brittany. The samples were preserved in 4% buffered formaldehyde seawater solution directly after collection, until 2019-2020 where they were imaged with the ZooScan, in the lab, on land. Each imaged object is geolocated, associated to a station, a cruise, a year and other metadata that enable the reconstruction of quantitative zooplankton communities for ecological studies (i.e. Grandrémy et al., 2023a). Each object is described by 46 morphological and grey level based features (8 bits encoding, 0 = black, 255 = white), including size, automatically extracted on each individual image by the Zooprocess. Each object was taxonomically identified using the web based application Ecotaxa with built-in, random forest and CNN based, semi-automatic sorting tools followed by expert validation or correction (Picheral et al., 2017). This dataset is intended to be used for ecological studies as well as machine learning applied to plankton studies. The archive contains: - One tab separated file (PELGAS ZooScan zooplankton dataset) containing all data and metadata associated to each imaged and identified object. Metadata and features are in columns (n =71) and objects are in rows (n = 1,153,507). - One comma separated file containing the name, type, definition and unit of each field (column) in the .tsv (dataset_descriptor_zooscan). - One comma separated file containing the taxonomic list of the dataset, with counts and nature of the content of the category, i.e. “T” for taxonomical category, and “M” for morphological category (taxonomy_descriptor_zooscan). - A individual_images directory containing images of each imaged object sorted in subdirectories named according to objects’ identifications object_taxon appended to an Ecotaxa internal taxon numerical id classif_id (i.e. taxon__123456789) across years and sampling stations. Within subdirectories, each object is named after its unique internal Ecotaxa identifier, objid. - A Map of the sampling station location over the 2004-2016 period

This dataset is composed of 702,111 zooplankton individuals, zooplankton pieces, non-living particles and imaging artefacts, ranging from 300 µm to 3.39 mm Equivalent Spherical Diameter, individually imaged and measured with the ZooCAM (Colas et al., 2018). The objects were sorted in 127 taxonomic and morphological groups. The imaged objects originate from samples collected on the Bay of Biscay continental shelf, in spring, from 2016 to 2019 during the PELGAS ecosystemic surveys (Doray et al., 2018). The samples were collected with a WP2 200 µm mesh size fitted with a Hydrobios (back-run stop) mechanical flowmeter, generally from 100 m depth to the surface, or 5 m above the sea floor (if bottom depth less than 100 m) in vertical hauls, at night. The samples were imaged on board, live, after collection and subsampling, and preserved in 4% buffered formaldehyde seawater. Each imaged object is geolocated, associated to a station, a cruise, a year and other metadata that enable the reconstruction of quantitative zooplankton communities for ecological studies (i.e. Grandrémy et al., 2023a). Each object is described by 52 morphological and grey level based features (8 bits encoding, 0 = black, 255 = white), including size, automatically extracted on each individual image by the ZooCAM software. Each object was taxonomically identified using the ZooCAM software and the web based application Ecotaxa with built-in, random forest and CNN based, semi-automatic sorting tools followed by expert validation or correction (Picheral et al., 2017). Images from 2016-2017 contain ROI bounding box limits, metadata at the bottom of each image, and non-homogenised background within and around the ROI bounding box; Images from 2018 contain non-homogenised background within the ROI bounding box only; images from 2019 have a completely homogeneous and thresholded background around the object.  The differences arose from successive ZooCAM software updates that do not modify the calculation of object’s features. This dataset is intended to be used for ecological studies as well as machine learning applied to plankton studies. The archive contains : - One tab separated file (PELGAS ZooCAM zooplankton dataset) containing all data and metadata associated to each imaged and identified object. Metadata and features are in columns (n =72) and objects are in rows (n = 702,111). - One comma separated file containing the name, type, definition and unit of each field (column) in the .tsv (dataset descriptor zoocam). - One comma separated file containing the taxonomic list of the dataset, with counts and nature of the content of the category, i.e. “T” for taxonomical category, and “M” for morphological category (taxonomy descriptor zoocam). - A individual_images directory containing images of each object, named according to the object id objid and sorted in subdirectories according to their taxonomic identification, across years and sampling stations. - A Map of the sampling station location over the 2016-2019 period.

'''Short description:''' Le modèle biogéochimique ECO-MARS3D sur la façade Manche Atlantique (PREVIMER_B1-ECOMARS3D-MANGA4000) est un modèle 3D de résolution spatiale 4km qui fournit les concentrations de nutriments et de plancton toutes les heures sur 30 niveaux (fenêtre de prévision à 4 jours). '''Paramètres calculés :''' Les paramètres calculés sont les suivants : * SAL : sea_water_salinity * TEMP : sea_water_temperature * suspended_inorganic_particulate_matter : mass_concentration_of_suspended_matter_in_sea_water * nanopicoplankton_nitrogen : mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_water * diatom_nitrogen : mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_water * dinoflagellate_nitrogen : mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_water * microzooplankton_nitrogen : mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_water * mesozooplankton_nitrogen : mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_water * colonial_phaeocystis_nitrogen : mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_water * phaeocystis_mucus : concentration_of_phaeocystis_mucus_expressed_as_mass_in_sea_water * ammonium : mole_concentration_of_ammonium_in_sea_water * nitrate : mole_concentration_of_nitrate_in_sea_water * dissolved_silicate : mole_concentration_of_silicate_in_sea_water * dissolved_phosphate : mole_concentration_of_phosphate_in_sea_water * dissolved_oxygen : dissolved_oxygen_in_water_column * cumulative_nanoflagellate_carbon_production : cumulative_nanoflagellate_production_expressed_as_carbon_in_sea_water * cumulative_diatom_carbon_production : cumulative_diatom_production_expressed_as_carbon_in_sea_water * cumulative_dinoflagellate_carbon_production : cumulative_dinoflagellate_production_expressed_as_carbon_in_sea_water * cumulative_phaeocystis_carbon_production : cumulative_phaeocystis_production_expressed_as_carbon_in_sea_water * organic_nitrogen_benth : mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthos Les paramètres diagnostiques calculés sont les suivants : * XE : sea_surface_height_above_geoid * maximum_de_diat : maximum_diatom_mass_concentration_in_sea_water * maximum_de_dino : maximum_dinoflagellate_mass_concentration_in_sea_water * maximum_de_nano : maximum_nanoflagellate_mass_concentration_in_sea_water * grad_vert_salinite : maximum_vertical_gradient_of_sea_water_salinity * grad_vert_temp : maximum_vertical_gradient_of_sea_water_temperature * extinction_lumineuse : light_extinction_in_sea_water * prod_diat : cumulated_production_of_diatoms_in_sea_water_column_expressed_in_carbon * prod_dino : cumulated_production_of_dinoflagellates_in_sea_water_column_expressed_in_carbon * prod_nano : cumulated_production_of_nanoflagellates_in_sea_water_column_expressed_in_carbon * chlorophylle_a : chlorophyll_mass_concentration_in_sea_water * prod_cumul_chloro : cumulated_total_production_in_sea_water_column_expressed_in_carbon * maximum_de_phaeocystis : maximum_phaeocystis_mass_concentration_in_sea_water * prod_phaeocystis : cumulated_production_of_phaeocystis_in_sea_water_column_expressed_in_carbon * oxygen_saturation : oxygen_saturation * ammoniumGIRON_tracer_sign: mole_concentration_of_ammonium_in_sea_waterGIRON_tracer_sign * ammoniumGIRON_tracer_age: mole_concentration_of_ammonium_in_sea_waterGIRON_tracer_age * nitrateGIRON_tracer_sign: mole_concentration_of_nitrate_in_sea_waterGIRON_tracer_sign * nitrateGIRON_tracer_age: mole_concentration_of_nitrate_in_sea_waterGIRON_tracer_age * nanopicoplankton_nitrogenGIRON_tracer_sign: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * nanopicoplankton_nitrogenGIRON_tracer_age: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * diatom_nitrogenGIRON_tracer_sign: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * diatom_nitrogenGIRON_tracer_age: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * dinoflagellate_nitrogenGIRON_tracer_sign: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * dinoflagellate_nitrogenGIRON_tracer_age: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * microzooplankton_nitrogenGIRON_tracer_sign: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * microzooplankton_nitrogenGIRON_tracer_age: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * mesozooplankton_nitrogenGIRON_tracer_sign: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * mesozooplankton_nitrogenGIRON_tracer_age: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * detrital_nitrogenGIRON_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * detrital_nitrogenGIRON_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * colonial_phaeocystis_nitrogenGIRON_tracer_sign: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * colonial_phaeocystis_nitrogenGIRON_tracer_age: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * phaeocystis_cells_nitrogenGIRON_tracer_sign: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * phaeocystis_cells_nitrogenGIRON_tracer_age: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * organic_nitrogen_benthGIRON_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosGIRON_tracer_sign * organic_nitrogen_benthGIRON_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosGIRON_tracer_age * phytoplankton_sign_N_GIRON: nitrogen_fraction_in_phytoplankton_from_source_GIRON * phytoplankton_age_N_GIRON: age_of_nitrogen_fraction_in_phytoplankton_from_source_GIRON * ammoniumLOIRE_tracer_sign: mole_concentration_of_ammonium_in_sea_waterLOIRE_tracer_sign * ammoniumLOIRE_tracer_age: mole_concentration_of_ammonium_in_sea_waterLOIRE_tracer_age * nitrateLOIRE_tracer_sign: mole_concentration_of_nitrate_in_sea_waterLOIRE_tracer_sign * nitrateLOIRE_tracer_age: mole_concentration_of_nitrate_in_sea_waterLOIRE_tracer_age * nanopicoplankton_nitrogenLOIRE_tracer_sign: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * nanopicoplankton_nitrogenLOIRE_tracer_age: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * diatom_nitrogenLOIRE_tracer_sign: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * diatom_nitrogenLOIRE_tracer_age: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * dinoflagellate_nitrogenLOIRE_tracer_sign: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * dinoflagellate_nitrogenLOIRE_tracer_age: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * microzooplankton_nitrogenLOIRE_tracer_sign: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * microzooplankton_nitrogenLOIRE_tracer_age: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * mesozooplankton_nitrogenLOIRE_tracer_sign: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * mesozooplankton_nitrogenLOIRE_tracer_age: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * detrital_nitrogenLOIRE_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * detrital_nitrogenLOIRE_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * colonial_phaeocystis_nitrogenLOIRE_tracer_sign: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * colonial_phaeocystis_nitrogenLOIRE_tracer_age: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * phaeocystis_cells_nitrogenLOIRE_tracer_sign: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * phaeocystis_cells_nitrogenLOIRE_tracer_age: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * organic_nitrogen_benthLOIRE_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosLOIRE_tracer_sign * organic_nitrogen_benthLOIRE_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosLOIRE_tracer_age * phytoplankton_sign_N_LOIRE: nitrogen_fraction_in_phytoplankton_from_source_LOIRE * phytoplankton_age_N_LOIRE: age_of_nitrogen_fraction_in_phytoplankton_from_source_LOIRE * ammoniumSEINE_tracer_sign: mole_concentration_of_ammonium_in_sea_waterSEINE_tracer_sign * ammoniumSEINE_tracer_age: mole_concentration_of_ammonium_in_sea_waterSEINE_tracer_age * nitrateSEINE_tracer_sign: mole_concentration_of_nitrate_in_sea_waterSEINE_tracer_sign * nitrateSEINE_tracer_age: mole_concentration_of_nitrate_in_sea_waterSEINE_tracer_age * nanopicoplankton_nitrogenSEINE_tracer_sign: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * nanopicoplankton_nitrogenSEINE_tracer_age: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * diatom_nitrogenSEINE_tracer_sign: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * diatom_nitrogenSEINE_tracer_age: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * dinoflagellate_nitrogenSEINE_tracer_sign: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * dinoflagellate_nitrogenSEINE_tracer_age: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * microzooplankton_nitrogenSEINE_tracer_sign: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * microzooplankton_nitrogenSEINE_tracer_age: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * mesozooplankton_nitrogenSEINE_tracer_sign: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * mesozooplankton_nitrogenSEINE_tracer_age: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * detrital_nitrogenSEINE_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * detrital_nitrogenSEINE_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * colonial_phaeocystis_nitrogenSEINE_tracer_sign: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * colonial_phaeocystis_nitrogenSEINE_tracer_age: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * phaeocystis_cells_nitrogenSEINE_tracer_sign: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * phaeocystis_cells_nitrogenSEINE_tracer_age: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * organic_nitrogen_benthSEINE_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosSEINE_tracer_sign * organic_nitrogen_benthSEINE_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosSEINE_tracer_age * phytoplankton_sign_N_SEINE: nitrogen_fraction_in_phytoplankton_from_source_SEINE * phytoplankton_age_N_SEINE: age_of_nitrogen_fraction_in_phytoplankton_from_source_SEINE

Here, we provide plankton image data that was sorted with the web applications EcoTaxa and MorphoCluster. The data set was used for image classification tasks as described in Schröder et. al (in preparation) and does not include any geospatial or temporal meta-data. Plankton was imaged using the Underwater Vision Profiler 5 (Picheral et al. 2010) in various regions of the world's oceans between 2012-10-24 and 2017-08-08. This data publication consists of an archive containing  "training.csv" (list of 392k training images for classification, validated using EcoTaxa), "validation.csv" (list of 196k validation images for classification, validated using EcoTaxa), "unlabeld.csv" (list of 1M unlabeled images), "morphocluster.csv" (1.2M objects validated using MorphoCluster, a subset of "unlabeled.csv" and "validation.csv") and the image files themselves. The CSV files each contain the columns "object_id" (a unique ID), "image_fn" (the relative filename), and "label" (the assigned name). The training and validation sets were sorted into 65 classes using the web application EcoTaxa (http://ecotaxa.obs-vlfr.fr). This data shows a severe class imbalance; the 10% most populated classes contain more than 80% of the objects and the class sizes span four orders of magnitude. The validation set and a set of additional 1M unlabeled images were sorted during the first trial of MorphoCluster (https://github.com/morphocluster). The images in this data set were sampled during RV Meteor cruises M92, M93, M96, M97, M98, M105, M106, M107, M108, M116, M119, M121, M130, M131, M135, M136, M137 and M138, during RV Maria S Merian cruises MSM22, MSM23, MSM40 and MSM49, during the RV Polarstern cruise PS88b and during the FLUXES1 experiment with RV Sarmiento de Gamboa. The following people have contributed to the sorting of the image data on EcoTaxa: Rainer Kiko, Tristan Biard, Benjamin Blanc, Svenja Christiansen, Justine Courboules, Charlotte Eich, Jannik Faustmann, Christine Gawinski, Augustin Lafond, Aakash Panchal, Marc Picheral, Akanksha Singh and Helena Hauss In Schröder et al. (in preparation), the training set serves as a source for knowledge transfer in the training of the feature extractor. The classification using MorphoCluster was conducted by Rainer Kiko. Used labels are operational and not yet matched to respective EcoTaxa classes.

Plankton was sampled with various nets, from bottom or 500m depth to the surface, in many oceans of the world. Samples were imaged with a ZooScan. The full images were processed with ZooProcess which generated regions of interest (ROIs) around each individual object and a set of associated features measured on the object (see Gorsky et al 2010 for more information). The same objects were re-processed to compute features with the scikit-image toolbox http://scikit-image.org. The 1,451,745 resulting objects were sorted by a limited number of operators, following a common taxonomic guide, into 98 taxa, using the web application EcoTaxa http://ecotaxa.obs-vlfr.fr. For the purpose of training machine learning classifiers, the images in each class were split into training, validation, and test sets, with proportions 70%, 15% and 15%. The folder ZooScanNet_data.tar contains : taxa.csv.gz Table of the classification of each object in the dataset, with columns : - objid: unique object identifier in EcoTaxa (integer number) - taxon_level1: taxonomic name corresponding to the level 1 classification - lineage_level1: taxonomic lineage corresponding to the level 1 classification - taxon_level2: name of the taxon corresponding to the level 2 classification  - plankton: if the object is a plankton or not (boolean) - set: class of the image corresponding to the taxon (train : training, val : validation, or test) - img_path: local path of the image corresponding to the taxon (of level 1), named according to the object id features_native.csv.gz Table of metadata of each object including the different features processed by ZooProcess. All features are computed on the object only, not the background. All area/length measures are in pixels. All grey levels are in encoded in 8 bits (0=black, 255=white). With columns: - objid: unique object identifier in EcoTaxa (integer number) And 48 features: - area - mean - stddev - mode - min/max - perim. - width,height  - major,minor - circ. - feret - intden - median - skew,kurt - %area - area_exc - fractal - skelarea - slope - histcum1,2,3 - nb1,2,3 - symetrieh,symetriev - symetriehc,symetrievc - convperim,convarea - fcons - thickr:  - esd - elongation - range - centroids - sr - perimareaexc - feretareaexc - perimferet/perimmajor - circex - cdexc See the “ZooScan” sheet - OBJECT metadata, annotation and measurements - , at https://doi.org/10.5281/zenodo.14704250 for definitions. features_skimage.csv.gz Table of morphological features recomputed with skimage.measure.regionprops on the ROIs produced by ZooProcess. See http://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.regionprops for documentation. inventory.tsv Tree view of the taxonomy and number of images in each taxon, displayed as text. With columns : - lineage_level1: taxonomic lineage corresponding to the level 1 classification - taxon_level1: name of the taxon corresponding to the level 1 classification - n: number of objects in each taxon class          2. Second folder ZooScanNet_imgs.tar contains : imgs Directory containing images of each object, named according to the object id objid and sorted in subdirectories according to their taxon.         3. And : map.png Map of the sampling locations, to give an idea of the diversity sampled in this dataset.  

This dataset gathers results of monthly sampling with a WP2 plankton net within the Gironde plume (Bay of Biscay) in 2008 from March to August, as part of the ECLAIR suite of surveys. The sampling in May was part of the ECLAIR time-series but was performed onboard the THALASSA vessel during the PELGAS 2008 survey. Results are made of anchovy and sardine egg abundances, as well as size-fractionnated zooplankton biomass.

The Sir Alister Hardy Foundation for Ocean Science (SAHFOS) is an international charity that operates the Continuous Plankton Recorder (CPR) Survey. The dataset covers the North Atlantic and the North Sea on since 1958.

ICES hosts data collected from both net trawl surveys (primarily bottom trawling), and from echo sounding (acoustic sampling in the pelagic zone). The net trawls are primarily hosted in the DATRAS data portal, and the acoustics in the acoustic trawl surveys portal. DATRAS (the Database of Trawl Surveys) stores data collected primarily from bottom trawl fish surveys coordinated by ICES expert groups. The survey data are covering the Baltic Sea, Skagerrak, Kattegat, North Sea, English Channel, Celtic Sea, Irish Sea, Bay of Biscay and the eastern Atlantic from the Shetlands to Gibraltar. At present, there are more than 45 years of continuous time series data in DATRAS, and survey data are continuously updated by national institutions. The acoustic database hosts information on fisheries observations collected from various pelagic surveys coordinated by ICES and falls into two categories: acoustic data, derived from readings taken on vessels, and those obtained through trawls in the open ocean – pelagic – zone. Combined, this provides key biological data on fish stocks such as herring, mackerel and blue whiting as well as krill and other prey species. The data from both systems are used for stock assessments and fish community studies by the ICES community and form the basis of management advice to the relevant regulatory bodies.

'''Short description:''' Global Ocean - near real-time (NRT) in situ quality controlled observations, hourly updated and distributed by INSTAC within 24-48 hours from acquisition in average. Data are collected mainly through global networks (Argo, OceanSites, GOSUD, EGO) and through the GTS '''DOI (product) :''' https://doi.org/10.48670/moi-00036