This visualization product displays plastic bags density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys. In cases where the wingspread and/or number of items were/was unknown, it was not possible to use the data because these fields are needed to calculate the density. Data collected before 2011 are concerned by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using the following formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area was calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities were calculated on each trawl and year using the following computation: Density of plastic bags (number of items per km²) = ∑Number of plastic bags related items / Swept area (km²) Percentiles 50, 75, 95 & 99 were calculated taking into account data for all years. The list of selected items for this product is attached to this metadata. Information on data processing and calculation is detailed in the attached methodology document. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area.

The glider operations in the MOOSE network started to be deployed regularly in 2010 in the North Western Mediterranean Sea, thanks to the setup of national glider facilities at DT-INSU/Ifremer (http://www.dt.insu.cnrs.fr/gliders/gliders.php) and with the support of the European project FP7-PERSEUS. Two endurance lines are operated: MooseT00 (Nice-Calvi; Ligurian Sea) and MooseT02 (Marseille-Menorca; Gulf of Lion). The all dataset here corresponds to raw data in the EGO format.

The flat oyster Ostrea edulis is a European native species that once covered vast areas in the North Sea, on the Atlantic coast and in other European coastal waters including the Mediterranean region. All these populations have been heavily fished by dredging over the last three centuries. More recently, the emergence of parasites combined with the proliferation of various predators and many human-induced additional stressors have caused a dramatic decrease in the last remaining flat oyster populations. Today, this species has disappeared from many locations in Europe and is registered on the OSPAR (Oslo-Paris Convention for the Protection of the Marine environment of the North-East Atlantic) list of threatened and/or declining species (see https://www.ospar.org/work-areas/bdc/species-habitats/list-of-threatened-declining-species-habitats). In that context, since 2018, the Flat Oyster REcoVERy project (FOREVER) has been promoting the reestablishment of native oysters in Brittany (France). This multi-partner project, involving the CRC (Comité Régional de la Conchyliculture), IFREMER (Institut Français de Recherche pour l’Exploitation de la Mer), ESITC (École Supérieure d’Ingénieurs des Travaux de la Construction) Caen and Cochet Environnement, has consisted of (1) inventorying and evaluating the status of the main wild flat oyster populations across Brittany, (2) making detailed analysis of the two largest oyster beds in the bays of Brest and Quiberon to improve understanding of flat oyster ecology and recruitment variability and to suggest possible ways of improving recruitment, and (3) proposing practical measures for the management of wild beds in partnership with members of the shellfish industry and marine managers. the final report of this project is available on Archimer : https://doi.org/10.13155/79506. This survey is part of the task 1 of the FOREVER, which took place between 2017-2021. Some previous data, acquired with the same methodology and within the same geographic area have been also added to this dataset. These data were collected during 30 intertidal and diving surveys in various bays and inlets of the coast of Bretagne. The localization of these surveys has been guided by the help of historical maps. In the field, the methodology was simple enough to be easily implemented regardless of the configuration of the sampled site. The intertidal survey was conducted at very low tide (tidal range > 100) to sample the 0-1m level. Sampling was carried out randomly or systematically following the low water line. Where possible (in terms of visibility and accessibility), dive surveys were also carried out (0-10m depth), along 100m transects, using the same methodology of counting in a 1m2 quadrat. As often as possible, geo-referenced photographs were taken to show the appearance, density and habitat where Ostrea edulis was present. All these pictures are available in the image bank file. Overall, this dataset contains a total of 300 georeferenced records, where flat oysters have been observed. The dataset file contains also information concerning the surrounding habitat description and is organized according the OSPAR recommendations. This publication gives also a map, under a kml format showing each occurrence and its characteristics. This work was done in the framework of the following research project: " Inventaire, diagnostic écologique et restauration des principaux bancs d’huitres plates en Bretagne : le projet FOREVER. Contrat FEAMP 17/2215675".

As part of the marine water quality monitoring of the “Pertuis” and the “baie de l’Aiguillon” (France), commissioned by the OFB and carried out by setec énergie environnement, three monitoring stations were installed. Two of them were set up at the mouths of the Charente and Seudre rivers on February 6 and 27, 2019, respectively, while a third was deployed in the Bay of Aiguillon on March 24, 2021. The dataset presented here concerns the station installed in the Charente estuary. Measurements are organized into .csv files, with one file per year. Data is collected using a SAMBAT multiparameter probe, which records the following parameters: - Temperature (-5 to 35 °C) - Conductivity (0 to 10 mS/cm) - Pressure (0 to 10 m) - Turbidity (0 to 300 NTU) - Dissolved Oxygen (0 to 20 mg/L & 0 to 200 %) - Fluorescence (0 to 50 µg/l) - PH (0/14)

Data were collected by the Laboratoire de Ressources Halieutiques d'Aquitaine (Ifremer). The observations were carried out between April 1992 and July 2006. Observations and measures were made on board commercial vessels, practicing on Adour River generally in springtime and in summer. Sampling of catches took place on the river between March and July; The researchers took scales, a blood sample, took measurements of length and weight on the fish caught by the fishermen during the observed fishing trips. Sampling was of sampling-by-opportunity type. The driftnet is an emblematic and very old métier in this area, targeting different species as atlantic salmon (Salmo salar), sea trout (Salmo trutta), sea Lamprey (Pétromyzon marinus) and also allis shad (Alosa alosa). This activity is framed by particular regulation as quota of fishing days and licenses. Between 15 and 20 costal boats practice this métier during the year and the fleet characteristics are homogenous. The boats put the net in the water (around 100 m long) and let it drift with the surface current (downstream) while the tide is rising; the fish swimming upstream the river are then trapped in the water column. Different meshes can be used.

'''DEFINITION''' Ocean heat content (OHC) is defined here as the deviation from a reference period (1993-2014) and is closely proportional to the average temperature change from z1 = 0 m to z2 = 700 m depth: OHC=∫_(z_1)^(z_2)ρ_0 c_p (T_yr-T_clim )dz [1] with a reference density of = 1030 kgm-3 and a specific heat capacity of cp = 3980 J kg-1 °C-1 (e.g. von Schuckmann et al., 2009). Time series of annual mean values area averaged ocean heat content is provided for the Mediterranean Sea (30°N, 46°N; 6°W, 36°E) and is evaluated for topography deeper than 300m. '''CONTEXT''' Knowing how much and where heat energy is stored and released in the ocean is essential for understanding the contemporary Earth system state, variability and change, as the oceans shape our perspectives for the future. The quality evaluation of MEDSEA_OMI_OHC_area_averaged_anomalies is based on the “multi-product” approach as introduced in the second issue of the Ocean State Report (von Schuckmann et al., 2018), and following the MyOcean’s experience (Masina et al., 2017). Six global products and a regional (Mediterranean Sea) product have been used to build an ensemble mean, and its associated ensemble spread. The reference products are: • The Mediterranean Sea Reanalysis at 1/24 degree horizontal resolution (MEDSEA_MULTIYEAR_PHY_006_004, DOI: https://doi.org/10.25423/CMCC/MEDSEA_MULTIYEAR_PHY_006_004_E3R1, Escudier et al., 2020) • Four global reanalyses at 1/4 degree horizontal resolution (GLOBAL_MULTIYEAR_PHY_ENS_001_031): GLORYS, C-GLORS, ORAS5, FOAM • Two observation based products: CORA (INSITU_GLO_PHY_TS_OA_MY_013_052) and ARMOR3D (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012). Details on the products are delivered in the PUM and QUID of this OMI. '''CMEMS KEY FINDINGS''' The ensemble mean ocean heat content anomaly time series over the Mediterranean Sea shows a continuous increase in the period 1993-2022 at rate of 1.38±0.08 W/m2 in the upper 700m. After 2005 the rate has clearly increased with respect the previous decade, in agreement with Iona et al. (2018). '''DOI (product):''' https://doi.org/10.48670/moi-00261

EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity, contaminants and marine litter. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on floating micro-litter. This dataset is the result of a validation and harmonisation process of the datasets concerning floating micro-litter present in EMODnet Chemistry. The datasets concerning micro-litter are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions. Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/ This process was performed by ‘Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Division of Oceanography (OGS/NODC)’ from Italy. Harmonisation means that: (1) unit conversion is carried out to express variables with a limited set of measurement units and (2) merging of variables described by different “local names”, but corresponding exactly to the same concepts in BODC P01 vocabulary. The harmonised dataset can be downloaded as ODV collection that can be opened with ODV software for visualization (More information can be found at: https://www.seadatanet.org/Software/ODV ). The same dataset is offered as spreadsheet (txt format, tab separated values) where the values of the categories for the following reported parameters (type, shape, size, color, transparency and material) have been uniformed as labelled in the SeaDataNet H01, H02, H03, H04, H05, H06 vocabularies (https://vocab.seadatanet.org/search ). This format is more adapted to worksheet applications (e.g. LibreOffice Calc).

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification, contaminants and litter. The chosen parameters are relevant for the Marine Strategy Framework Directive (MSFD), in particular for descriptors 5, 8, 9 and 10. The datasets contain standardized, harmonized and validated data collections from seafloor litter. Datasets concerning seafloor litter data are loaded in a central database after a semi-automated validation phase. Once loaded, a data assessment is performed in order to check data consistency and potential errors are corrected thanks to a feedback loop with data originators. EMODnet seafloor litter data and database are hosted and maintained by ‘Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Division of Oceanography (OGS/NODC)’ from Italy. For seafloor litter, the harmonized datasets contain all unrestricted EMODnet Chemistry data on seafloor litter data. Data are formatted following Guidelines and forms for gathering marine litter data, which can be found at: https://dx.doi.org/10.6092/15c0d34c-a01a-4091-91ac-7c4f561ab508 The updated vocabularies of admitted values are available at: https://vocab.seadatanet.org/search https://vocab.ices.dk/ The harmonized datasets can be downloaded as EMODnet Sea-floor litter data format version 1.0, which is a csv file, tab separated values.

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.

The Southern Ocean plays a fundamental role in regulating the global climate. This ocean also contains a rich and highly productive ecosystem, potentially vulnerable to climate change. Very large national and international efforts are directed towards the modeling of physical oceanographic processes to predict the response of the Southern Ocean to global climate change and the role played by the large-scale ocean climate processes. However, these modeling efforts are greatly limited by the lack of in situ measurements, especially at high latitudes and during winter months. The standard data that are needed to study ocean circulation are vertical profiles of temperature and salinity, from which we can deduce the density of seawater. These are collected with CTD (Conductivity-Temperature-Depth) sensors that are usually deployed on research vessels or, more recently, on autonomous Argo profilers. The use of conventional research vessels to collect these data is very expensive, and does not guarantee access to areas where sea ice is found at the surface of the ocean during the winter months. A recent alternative is the use of autonomous Argo floats. However, this technology is not easy to use in glaciated areas. In this context, the collection of hydrographic profiles from CTDs mounted on marine mammals is very advantageous. The choice of species, gender or age can be done to selectively obtain data in particularly under-sampled areas such as under the sea ice or on continental shelves. Among marine mammals, elephant seals are particularly interesting. Indeed, they have the particularity to continuously dive to great depths (590 ± 200 m, with maxima around 2000 m) for long durations (average length of a dive 25 ± 15 min, maximum 80 min). A Conductivity-Temperature-Depth Satellite Relay Data Logger (CTD-SRDLs) has been developed in the early 2000s to sample temperature and salinity vertical profiles during marine mammal dives (Boehme et al. 2009, Fedak 2013). The CTD-SRDL is attached to the seal on land, then it records hydrographic profiles during its foraging trips, sending the data by satellite ARGOS whenever the seal goes back to the surface.While the principle intent of seal instrumentation was to improve understanding of seal foraging strategies (Biuw et al., 2007), it has also provided as a by-product a viable and cost-effective method of sampling hydrographic properties in many regions of the Southern Ocean (Charrassin et al., 2008; Roquet et al., 2013).