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.

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

'''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

RESOMAR is a national network whose main objective is to bring together studies and monitoring programmes conducted at the network’s stations and observatories (Wimereux, Luc/Mer, Dinard, Roscoff, Brest, Concarneau, Ile d'Yeu, La Rochelle, Arcachon, Anglet, Banyuls, Perpignan, Sète, Marseille, Villefranche / Mer). Based on benthic and plankton community monitoring programmes implemented by the stations, one of RESOMAR’s objectives is to use this biological information in order to answer scientific questions, for example concerning the factors which control the distribution and abundance of organisms on different spatial and temporal scales. This monitoring information, the characteristics of which vary depending on the station (number of sites, frequency, continuous monitoring or not, communities observed, taxonomic resolution, observation methods, etc.) is brought together in two databases (RESOMAR/BENTHOS and RESOMAR/PELAGOS), which are currently being developed. The RESOMAR-PELAGOS database hosts biological data obtained by the pelagic aspects of RESOMAR (around fifteen programmes as of September 2012): http://abims.sb- roscoff.fr/pelagos/ This database in particular brings together observation data (long-term series, inventories, spatial studies, etc.).

Zooplankton monitoring (essentially metazoal) – mesozooplankton in the Gironde estuary (3 stations) since 1997 Locations : 3 Stations pK86 : 45°31’N, 01°57’W, pK52 : 45°14’80’’N, 0°43’50’’W pK30 : 45°04’10’’N, 0°38’30’’W

The Pelagos database is the result of collaborative work by the Réseau des Stations et Observatoires Marins (RESOMAR), now part of the ILICO research infrastructure. It brings together biodiversity data from the coastal pelagic ecosystem (including time series). One of the goals is to exploit the biological information acquired, to answer scientific questions concerning, for example, the factors controlling the distribution and abundance of pelagic organisms at different spatial and time scales.

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.

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 1,433,278 resulting objects were sorted by a limited number of operators, following a common taxonomic guide, into 93 taxa, using the web application EcoTaxa (http://ecotaxa.obs-vlfr.fr). The archive 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: taxonomic name. Ambiguous names are made unique by including the name of the parent taxon in parentheses, after the name of the taxon. - lineage: full taxonomic lineage corresponding to this taxon. features_native.csv.gz Table of morphological features computed 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: same as above - area: area - mean: mean grey - stddev: standard deviation of greys - mode: modal grey - min: minimum grey - max: maximum grey - perim.: perimeter - width,height dimensions - major,minor: length of major,minor axis of the best fitting ellipse - circ.: circularity: 4pi(area/perim.^2) - feret: maximal feret diameter - intden: integrated density: mean*area - median: median grey - skew,kurt: skewness,kurtosis of the histogram of greys - %area: proportion of the image corresponding to the object - area_exc: area excluding holes - fractal: fractal dimension of the perimeter - skelarea: area of the one-pixel wide skeleton of the image - slope: slope of the cumulated histogram of greys - histcum1,2,3: grey level at quantiles 0.25, 0.5, 0.75 of the histogram of greys - nb1,2,3: number of objects after thresholding at the grey levels above - symetrieh,symetriev: index of horizontal,vertical symmetry - symetriehc,symetrievc: same but after thresholding at level histcum1 - convperim,convarea: perimeter,area of the convex hull of the object - fcons: contrast - thickr: thickness ratio: maximum thickness/mean thickness - elongation: elongation index: major/minor - range: range of greys: max-min - meanpos: relative position of the mean grey: (max-mean)/range - cv: coefficient of variation of greys: 100*(stddev/mean) - sr: index of variation of greys: 100*(stddev/range) - perimferet: index of the relative complexity of the perimeter: perim/feret - perimmajor: index of the relative complexity of the perimeter: perim/major 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.txt Tree view of the taxonomy and number of images in each taxon, displayed as text. map.png Map of the sampling locations, to give an idea of the diversity sampled in this dataset. imgs Directory containing images of each object, named according to the object id objid and sorted in subdirectories according to their taxon.

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.

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.