French Research vessels have been collecting thermo-salinometer (TSG) data since the early 2000 in contribution to the GOSUD programme. The set of homogeneous instruments is permanently monitored and regularly calibrated. Water samples are taken on a daily basis by the crew and later analysed in the laboratory. We present here the delayed mode processing of the time series intiated in 2001 dataset and an overview of the resulting quality. The careful calibration and instrument maintenance, complemented with a rigorous adjustment on water samples lead to reach an accuracy of a few 10-² PSS in salinity or evenless. Global comparison with the ISAS13 ARGO gridded product shows an excellent agreement of the datasets. The SSS-Fresh dataset appears as highly valuable for the "calibration and validation" of the new satellite observations delivered by SMOS, Aquarius and SMAP.

This dataset comprises energy density and proximal composition (water, ash, lipid and protein contents) for anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus) from the Bay of Biscay, the English Channel and the southern North Sea between 2014 and 2017. Fish were sampled throughout various seasons thanks to the PELGAS (May, Bay of Biscay), EVHOE (October-November, Bay of Biscay), CGFS and CAMANOC (September-October, English Channel) surveys conducted by IFREMER on the RV “Thalassa”, to the JUVENA (September-October, Bay of Biscay) survey conducted by AZTI, and from commercial landings within the European Data Collection Framework (DCF) during the CAPTAIN project (France Filière Pêche). During the surveys, pelagic (PELGAS and JUVENA) or demersal (EVHOE and CGFS) trawl hauls are undertaken to identify species and measure individual fish traits. Professional sampling was performed from pelagic trawl or purse-seine catches. From the various surveys, a sub-sampling of the trawls was performed to cover as much as possible the spatial extent of the surveys along the french coast. From the various selected trawls, a sub-sampling of 5 fish per size class (when possible) was performed to cover the size range of each species, based on the following size classes : sardine (1 : <15 cm ; 2 : 15-20 cm ; 3 : >20cm), anchovy (1 : <10cm ; 2 : 10-14 cm ; 3 : >14cm). Each fish was individually measured to the nearest tenth of a centimeter and weighted to the nearest tenth of a gram. These measurements were taken either at sea or later in the laboratory. The collected fish were frozen individually at -20°C before laboratory processing. In the laboratory, maturity stages were determined following ICES guidelines (ICES, 2008) based on macroscopic gonads observation and using a six-stage key as follows: stages 1 & 2 indicate immature and developing individuals, stages 3–5 indicate three steps of increasing gonad development and the spawning period (stage 3: partial pre-spawning; stage 4: spawning (hydrated); stage 5: partial post-spawning), and stage 6 features the final post-spawning period. Fish characterised by maturity stages 3, 4 or 5 were considered as being in an active reproductive period as opposed to fish in stages 1, 2 or 6. Fish were then ground and freeze-dried during at least 48 hours. Water content of the entire fish was determined from dry mass and wet mass ratio. Then, fish were ground again to obtain fine homogeneous dry powder for subsequent analysis. Energy density measurements were performed following the protocols of Gatti et al. (2018). Two subsamples of fish powder were placed in an adiabatic bomb calorimeter (IKA C-4000 adiabatic bomb calorimeter, IKA-WerkeGmbh & co. KG) for energy measurements. The energy density (ED, kJ.g-1 dry mass) was determined by measuring the heat released through the combustion of a small subsample, approximately 200 mg. If the coefficient of variation between the two measurements exceeded 3%, a third measurement was made. Finally, ED subsamples measurements were averaged and assigned to each individual fish. Energy density analyses were conducted on 503 individuals for anchovy and 976 individuals for sardine. Ash content was determined gravimetrically by combusting dried tissue in a muffle furnace at 550°C for six hours. Lipids and proteins were analysed by a certified laboratory (Labocea, Plouzané, France). Protein content was estimated using the Kjeldahl method. It consists in first determining the quantity of nitrogen contained in the sample, and to convert it into protein content using a conversion factor (6.25 here). Lipid content was determined by hydrolysis, using petroleum ether as an organic solvent. Carbohydrates represent less than 1% of fish mass and were thus neglected. Protein, lipid and ash content did not exactly sum to 1 in DW (anchovy: mean = 0.91, sd = 0.04; sardine: mean = 0.90, sd = 0.04). This discrepancy may arise from residual water, measurement uncertainties, or to a lesser extent the exclusion of carbohydrates. Body component contents have been normalised by dividing each component by the sum of lipids, proteins and ash content, to sum to one, enabling comparisons between fishes, assuming proportional errors across the components. A total of 116 and 104 proximate composition analyses were performed for anchovy and sardine, respectively.

The Arcachon Bay is a unique and ecologically important meso-tidal lagoon on the Atlantic coast of south-west France. The Arcachon Bay has the largest area of dwarf seagrass (Z. noltei) in Europe, the extent of which was stable in their extent between the 1950s and 1990s, but a decline in seagrass was observed in mid-2000. The decline of Zostera (seagrass) may have a significant impact on sedimentation in this coastal ecosystem rich in marine life. Interface cores were collected in September 2022 to determine sediment and mass accumulation rates (SAR, MAR) in the Arcachon Bay. Ten study areas were selected, distributed over most of the areas where seagrass meadows are actually observed. Two sites were visited each time, one with the presence of Zostera noltei in good condition (Healthy) and the other where the sediment was bare (Bare). Maximum water heights during spring tides range from 3.44 m for the deepest site (Garrèche) to 2.09 m for the shallowest site (Fontaines). A total of 20 sediment cores were sampled and carefully extruded every 1 cm from the top to the bottom of the core. The sediment layers were used to determine dry bulk density and selected radioisotope activities: DBD, 210Pb, 226Ra, 137Cs, 228Th and 40K expressed as %K). 

The ARCHYD dataset, which have been collected since 1988, represents the longest long-term hydrologic data sets in Arcachon Bay. The objectives of this monitoring programme are to assess the influence of oceanic and continental inputs on the water quality of the bay and their implications on biological processes. It also aims to estimate the effectiveness of management policies in the bay by providing information on trends and/or shifts in pressure, state, and impact variables. Sampling is carried on stations spread across the entire bay, but since 1988, the number and location of stations have changed slightly to better take into account the gradient of ocean and continental inputs. In 2005, the ARCHYD network was reduced to 8 stations that are still sampled by Ifremer to date. All the stations are sampled at a weekly frequency, at midday, alternately around the low spring tide and the high neap tide. Data are complementary to REPHY dataset. Physico-chemical measures include temperature, salinity, turbidity, suspended matters (organic, mineral), dissolved oxygen and dissolved inorganic nutrients (ammonium, nitrite+nitrate, phosphate, silicate). Biological measures include pigment proxies of phytoplankton biomass and state (chlorophyll a and phaeopigment).

This dataset contains maps of 13 anthropogenic pressures (one pressure per map), modeled according to the methodology used by Holon et al. (2015), and updated with the latest available data on human activities in 2021. This dataset is available for visualization on the Medtrix cartographic platform (http://www.medtrix.fr, free access after registration). More details can be found on the methodology and modeling approach on the medtrix website (https://medtrix.fr/en/portfolio_page/impact-2/) and on the 2018 IMPACT update report (only available in French at the moment). The modeling and mapping was performed using R software V 4.0. Table 1 lists the modeled anthropogenic pressures, the modeling approach and the data used. The spatial resolution of the raster layers is 500 m, the coordinate reference system (CRS) of the raster layers is RGF93 / Lambert-93 (EPSG 2154). The values of each layer range from 0 (no pressure) to 1 (max modeled pressure over the study area), and is unitless. All pressures are modeled over the spatial extent of the French mediterranean coastal habitat map (www.medtrix.fr, “DONIA expert” project), except for professional fishing and marine traffic, that are modeled over the entire French Mediterranean sea. The ZIP archive contains a tif raster composed of 13 layers corresponding to the 13 modeled pressures. All data acquired are publicly accessible without any restriction (under CC-BY licence).  

Numerous reef-forming species have declined dramatically in the last century, many of which have been insufficiently documented due to anecdotal or hard-to-access information. One of them, the honeycomb worm Sabellaria alveolata (L.) is a tube-building polychaete that can form large reefs, providing important ecosystem services such as coastal protection and habitat provision. It ranges from Scotland to Morocco, yet little is known about its distribution outside of the United Kingdom, where it is protected and where there is a strong heritage of natural history and sustained observations. As a result, online marine biodiversity information systems currently contain haphazardly distributed records of S. alveolata. One of the objectives of the REEHAB project (http://www.honeycombworms.org) was to combine historical records with contemporary data to document changes in the distribution and abundance of S. alveolata. Here we publish the result of the curation of 446 sources, gathered from literature, targeted surveys, local conservation reports, museum specimens, personal communications by authors and by their research teams, national biodiversity information systems (i.e. the UK National Biodiversity Network (NBN), https://nbn.org.uk/) and validated citizen science observations (i.e. https://www.inaturalist.org/). 80%[ar1]  of these records were not previously referenced in any online information system. Additionally, historic field notebooks from Edouard Fischer-Piette and Gustave Gilson were scanned for S. alveolata information and manually entered. The original taxonomic identification of the 23296 S. alveolata records has been kept. Some identification errors may however be present, particularly in the English Channel and the North Sea where incorrectly identified observations of intertidal Sabellaria spinulosa were recorded. A further 229 observations are recorded as ‘Sabellaria spp.’ as the available information does not allow a species-level identification. Many sources reported abundances based on the semi-quantitative SACFOR scale while others simply noted its presence, and others still verified both its absence and presence. The result is a curated and comprehensive dataset spanning over two centuries on the past and present global distribution and abundance of S. alveolata. Sabellaria alveolata records projected onto a 50km grid. When SACFOR scale abundance scores were given to occurrence records, the highest abundance value per grid cell was retained.

Ensemble simulations of the ecosystem model Apecosm (https://apecosm.org) forced by the IPSL-CM6-LR climate model with the climate change scenario SSP5-8.5. The output files contain yearly mean biomass density for 3 communities (epipelagic, mesopelagic migratory and mesopelagic redidents) and 100 size classes (ranging from 0.12cm to 1.96m) The model grid file is also provided. Units are in J/m2 and can be converted in kg/m2 by dividing by 4e6. These outputs are associated with the "Assessing the time of emergence of marine ecosystems from global to local scales using IPSL-CM6A-LR/APECOSM climate-to-fish ensemble simulations" paper from the Earth's Future "Past and Future of Marine Ecosystems" Special Collection.

Good Environmental Status assessment (GES) for descriptor 8 (contaminants, D8) of the Marine Strategy Framework Directive (MSFD) is reached when concentrations of contaminants are at levels not giving rise to pollution effects. It is described by 4 criteria among which the first one focus on the concentration of the contaminants in the environment (criteria 1 of the D8, D8C1). The environmental status for D8 in France includes assessment of contaminant concentrations in sediment, bivalves, fish, birds, mammals to cover the French marine area the continental shelf from the coast line). The 8 tables below present the assessment of the chemical contamination in sediment and bivalves on the coastal area of the 4 French marine subregions for D8 as part of the 2024 GES assessment. These tables report the status and temporal trends of each station x matrice x substance triplet in each of the 4 French marine subregions. Explanation on how to read the cells is given in the “read file”. The environmental assessment for D8 in France can be found in Mauffret al., 2023 (DOI:10.13155/97214). It includes 17 national indicator assessments, 4 OSPAR indicators and integrated assessment in selected assessment units at the level of the criteria 1 and 2. 

Plankton was sampled with a Continuous Underway Fish Egg Sampler (CUFES, 315µm mesh size) at 4 m below the surface, and a WP2 net (200µm mesh size) from 100m to the surface, or 5 m above the sea floor to the surface when the depth was < 100 m, in the Bay of Biscay. The full images were processed with the ZooCAM software and the embedded Matrox Imaging Library (Colas et a., 2018) which generated regions of interest (ROIs) around each individual object and a set of features measured on the object. The same objects were re-processed to compute features with the scikit-image library http://scikit-image.org. The 1, 286, 590 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. 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 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_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 morphological features computed by ZooCAM. 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 : - area : object's surface - area_exc : object surface excluding white pixels - area_based_diameter : object's Area Based Diameter: 2 * (object_area/pi)^(1/2) - meangreyobjet : mean image grey level - modegreyobjet : modal object grey level - sigmagrey : object grey level standard deviation - mingrey : minimum object grey level - maxgrey : maximum object grey level - sumgrey : object grey level integrated density: object_mean*object_area - breadth : breadth of the object along the best fitting ellipsoid minor axis - length : breadth of the object along the best fitting ellipsoid majorr axis - elongation : elongation index: object_length/object_breadth - perim : object's perimeter - minferetdiam : minimum object's feret diameter - maxferetdiam : maximum object's feret diameter - meanferetdiam : average object's feret diameter - feretelongation : elongation index: object_maxferetdiam/object_minferetdiam - compactness : Isoperimetric quotient: the ration of the object's area to the area of a circle having the same perimeter - intercept0, intercept45 , intercept90, intercept135 : the number of times that a transition from background to foreground occurs a the angle 0ø, 45ø, 90ø and 135ø for the entire object - convexhullarea : area of the convex hull of the object - convexhullfillratio : ratio object_area/convexhullarea - convexperimeter : perimeter of the convex hull of the object - n_number_of_runs : number of horizontal strings of consecutive foreground pixels in the object - n_chained_pixels : number of chained pixels in the object - n_convex_hull_points : number of summits of the object's convex hull polygon - n_number_of_holes : number of holes (as closed white pixel area) in the object - roughness : measure of small scale variations of amplitude in the object's grey levels - rectangularity : ratio of the object's area over its best bounding rectangle's area - skewness : skewness of the object's grey level distribution - kurtosis : kurtosis of the object's grey level distribution - fractal_box : fractal dimension of the object's perimeter - hist25, hist50, hist75 : grey level value at quantile 0.25, 0.5 and 0.75 of the object's grey levels normalized cumulative histogram - valhist25, valhist50, valhist75 : sum of grey levels at quantile 0.25, 0.5 and 0.75 of the object's grey levels normalized cumulative histogram - nobj25, nobj50, nobj75 : number of objects after thresholding at the object_valhist25, object_valhist50 and object_valhist75 grey level - symetrieh :index of horizontal symmetry - symetriev : index of vertical symmetry - skelarea : area of the object skeleton - thick_r : maximum object's thickness/mean object's thickness - cdist : distance between the mass and the grey level object's centroids features_skimage.csv.gz Table of morphological features recomputed with skimage.measure.regionprops on the ROIs produced by ZooCAM. 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 group 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.

The PROSOPE (PROductivity of Oceanic PElagic Systems) cruise took place from the 4th of September (Agadir, Morocco) to the 4th of October (Toulon, France) 1999 aboard the RV Thalassa. There were four main scientific objectives: 1, carry out classical process studies, typical of the Joint Global Ocean Flux Study (JGOFS), 2, focus on small scale biogeochemical processes, in particular at a daily scale, 3, study the influence of nitrogen, phosphorus and iron on oceanic fertility and 4, conduct a calibration/validation operation for the SeaWIFS (Sea-viewing Wide Field-of-View Sensor) color sensor. To reach these objectives, the studied areas, as well as the cruise plan, were designed : To investigate different trophic regimes, to investigate systems characterized by different degrees of limitation in nitrogen and phosphorus and to study stable ("steady state") systems for a sufficiently long period. The cruise track encompassed a variety of trophic systems ranging from eutrophic conditions associated to the Moroccan upwelling to the typical ultra-oligotrophic conditions of the eastern Mediterranean sea during summer stratification. Two main types of stations were occupied : - 9 short (4-hour) stations. These sites were occupied around the solar noon and were essentially designed to conduct objectives 1 (JGOFS process studies) and 4 (SeaWIFS validation/calibration) - 3 "long" (5-day) stations, where all four objectives were investigated with a particular emphasis on objectives 2 (processes at a daily scale) and 3 (nutrient resources and oceanic fertility). Between each station, continuous multiparametric (hydrological, optical, biological and chemical) surface acquisitions were performed.