This visualization product displays the type of litter in percent per net per year from specific protocols different from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. To calculate percentages for each type, formula applied is: Type (%) = (∑number of particles of each type)*100 / (∑number of particles of all type) When the number of micro-litters was not filled or was equal to zero, it was not possible to calculate the percentage. Standard vocabularies for micro-litter types are taken from Seadatanet's H01 library (https://vocab.seadatanet.org/v_bodc_vocab_v2/search.asp?lib=H01). Some morphological types of micro-litters may have been sampled but were not defined by the protocole applied during the survey. They are represented as « undefined micro-litter items ». Warnings: - 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 National Oceanographic Data Centre (NODC) for this area. - since 03/07/2023, the preferred label « Undefined micro-litter items » has been integrated into the H01 library whereas the labels « microplastic items », « non-plastic man-made micro-particles (e.g. glass, metal, tar) » and «non-plastic filaments (natural fibres, rubber) » have been deprecated. When defined, the material or polymer type can be checked directly in the source data.

This visualization product displays the spatial distribution of the sampling effort (based on the start position of the sampling tow) over the six-years' period 2017-2022 from other specific protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter samplings carried out according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. The spatial distribution was then determined by calculating the number of times each cell was sampled during the period 2017-2022, only taking into account the start position of the tows. The corresponding total distance (kms) sampled in each cell is also provided in the attribute table. Information on data processing and calculation are 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 National Oceanographic Data Centre (NODC) for this area. This work is based on the work presented in the following scientific article: O. Gerigny, M. Brun, M.C. Fabri, C. Tomasino, M. Le Moigne, A. Jadaud, F. Galgani, Seafloor litter from the continental shelf and canyons in French Mediterranean Water: Distribution, typologies and trends, Marine Pollution Bulletin, Volume 146, 2019, Pages 653-666, ISSN 0025-326X, https://doi.org/10.1016/j.marpolbul.2019.07.030.

This visualization product displays the fishing & aquaculture related plastic items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter 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 and reference lists used on a European scale. Preliminary processings were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Selection of fishing and aquaculture related plastic items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata). The selection was adapted to the Joint list of litter categories fishing gears identification and therefore contains some differences with the selection made for previously published versions of this product; - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of fishing & aquaculture related plastic items of the survey (normalized by 100 m) = Number of fishing & aquaculture related items of the survey x (100 / survey length) Then, this normalized number of fishing & aquaculture related plastic items is summed to obtain the total normalized number of fishing & aquaculture related plastic items for each survey. Finally, the median abundance of fishing & aquaculture related plastic items for each beach and year is calculated from these normalized abundances of fishing & aquaculture related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account fishing & aquaculture related plastic items from other sources data for all years. More information is available in the attached documents. 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 COAST-HF/Arcachon-Ferret time series characterizes the hydrology of the interface between the Arcachon lagoon, located in the South-Western France, and the Atlantic Ocean. A buoy belonging to Phares et Balises is instrumented with a multi-parametric probe that records sub-surface temperature, conductivity, depth, turbidity and fluorescence every 10 minutes since February 2018. It is opérated by the OASU and EPOC teams (Univ. Bordeaux/CNRS). COAST-HF (Coastal OceAn observing SysTem - High Frequency; www.coast-hf.fr) is a national observation network accredited by the CNRS as a national Earth Science Observatory (Service National d’Observation: SNO). It aims to federate and coordinate a set of 14 fixed platforms instrumented with high-frequency in situ measurements for key parameters of coastal waters. The COAST-HF/Arcachon-Ferret buoy is one of them. COAST-HF is part of the French Research Infrastructure dedicated to coastal ocean observations (RI ILICO, https://www.ir-ilico.fr). Data are transmitted to the Coriolis Côtier database (https://data.coriolis-cotier.org/). Data are raw data.

Numerous reef-forming species have declined dramatically over the last century. Many of these declines have been insufficiently documented due to anecdotal or hard-to-access information. The Ross worm Sabellaria spinulosa (L.) is a tube-building polychaete that can form large mostly subtidal reefs, providing important ecosystem services such as coastal protection and habitat provision. It ranges from Scotland to Morocco and into the Mediterranean as far as the Adriatic, yet little is known about its distribution outside of the North & Wadden Seas, where it is protected under the OSPAR & HELCOM regional sea conventions respectively. As a result, online marine biodiversity information systems currently contain haphazardly distributed records of S. spinulosa. 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 the two Sabellaria species found in Europe, S. alveolata and S. spinulosa. Here we publish the result of the curation of 555 S. spinulosa sources, gathered from literature, targeted surveys, local conservation reports, museum specimens, personal communications by authors  their research teams, national biodiversity information systems (i.e. the UK National Biodiversity Network (NBN), www.nbn.org.uk) and validated citizen science observations (i.e. https://www.inaturalist.org). 56% of these records were not previously referenced in any online information system. Additionally, historic samples from Gustave Gilson were scanned for S. spinulosa information and manually entered.   The original taxonomic identification of the 40,261 S. spinulosa records has been kept. Some identification errors may however be present, particularly in the English Channel and Mediterranean where intertidal and shallow subtidal records can be mistaken for Sabellaria alveolata. A further 229 observations (16 sources) are recorded as ‘Sabellaria spp.’ as the available information did not provide an identification down to species level. Many sources reported abundances based on the semi-quantitative SACFOR scale whilst 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. spinulosa. Sabellaria spinulosa 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.

LOCEAN has been in charge of collecting sea water for the analysis of water isotopes on a series of cruises or ships of opportunity mostly in the equatorial Atlantic, in the North Atlantic, in the southern Indian Ocean, in the southern Seas, Nordic Seas, and in the Arctic. The LOCEAN data set of the oxygen and hydrogen isotope (δ18O and δD) of marine water covers the period 1998 to 2019, but the effort is ongoing. Most data prior to 2010 (only δ18O) were analyzed using isotope ratio mass spectrometry (Isoprime IRMS) coupled with a Multiprep system (dual inlet method), whereas most data since 2010 (and a few earlier data) were obtained by cavity ring down spectrometry (CRDS) on a Picarro CRDS L2130-I, or less commonly on a Picarro CRDS L2120-I. Occasionally, some data were also run by Marion Benetti on an Isoprime IRMS coupled to a GasBench (dual inlet method) at the university of Iceland (Reykjavik). On the LOCEAN Picarro CRDS, most samples were initially analyzed after distillation, but since 2016, they have often been analyzed using a wire mesh to limit the spreading of sea salt in the vaporizer. Some of the samples on the CRDS were analyzed more than once on different days, when repeatability for the same sample was not sufficient or the daily run presented a too large drift. Accuracy is best when samples are distilled, and for δD are better on the Picarro CRDS L2130-I than on the Picarro CRDS L2120-I. Usually, we found that the reproducibility of the δ18O measurements is within ± 0.05 ‰ and of the δD measurements within ± 0.30 ‰, which should be considered an upper estimate of the error on the measurement on a Picarro CRDS. The water samples were kept in darkened glass bottles (20 to 50 ml) with special caps, and were often (but not always) taped afterwards. Once brought back in Paris, the samples were often stored in a cold room (with temperature close to 4°C), in particular if they were not analyzed within the next three months. There is however the possibility that some samples have breathed during storage. We found it happening on a number of samples, more commonly when they were stored for more than 5 years before being analyzed. We also used during one cruise bottles with not well-sealed caps (M/V Nuka Arctica in April 2019), which were analyzed within 3 months, but for which close to one third of the samples had breathed. We have retained those analyses, but added a flag ‘3’ meaning probably bad, at least on d-excess (outside of regions where sea ice forms or melts, for the analyses done on the Picarro CRDS, excessive evaporation is usually found with a d-excess criterium (which tends to be too low); for the IRMS analyses, it is mostly based when excessive scatter is found in the S- δ18O scatter plots or between successive data, in which case some outliers were flagged at ‘3’). In some cases when breathing happened, we found that d-excess can be used to produce a corrected estimate of δ18O and δD (Benetti et al., 2016). When this method was used a flag ‘1’ is added, indicating ‘probably good’ data, and should be thought as not as accurate as the data with no ‘correction’, which are flagged ‘2’ or ‘0’. We have adjusted data to be on an absolute fresh-water scale based on the study of Benetti et al. (2017), and on further tests with the different wire meshes used more recently. We have also checked the consistency of the runs in time, as there could have been changes in the internal standards used. On the Isoprime IRMS, it was mostly done using different batches of ‘Eau de Paris’ (EDP), whereas on the Picarro CRDS, we used three internal standards kept in metal tanks with a slight overpressure of dry air). The internal standards have been calibrated using VSMOW and GISP, and were also sent to other laboratories to evaluate whether they had drifted since the date of creation (as individual sub-standards have typically stored for more than 5-years). These comparisons are still not fully statisfactory to evaluate possible drifts in the sub-standards. Version V5 contains only one global file (ALL-Wisotopes-V5). However, up to version V4, individual files corresponded to regional subsets : - SO: Southern Ocean including cruise station and surface data mostly from 2017 in the Weddell Sea (WAPITI Cruise JR160004, DOI:10.17882/54012), as well as in the southern Ocean south of 20°S - SI: OISO cruise station and surface data in the southern Indian Ocean (since 1998) (DOI:10.18142/228) - EA: 20°N-20°S cruise station and surface data (since 2005), in particular in the equatorial Atlantic from French PIRATA (DOI:10.18142/14) and EGEE cruises (DOI:10.18142/95) - NA: 20°N-72°N station and surface data, mostly in the North Atlantic from Oceanographic cruises as well as from ships of opportunity (this includes in particular OVIDE cruise data since 2002 (DOI:10.17882/46448),  CATARINA, BOCATS1 and BOCATS2 (PID2019-104279GB-C21/AEI/10.13039/501100011033) cruises funded by the Spanish Research Agency, RREX2017 2017 cruise data (DOI:10.17600/17001400), SURATLANT data set since 2011 (DOI:10.17882/54517), Nuka Arctica and Tukuma Arctica data since 2012, STRASSE (DOI:10.17600/12040060) and MIDAS cruise data in 2012-2013, as well as surface data from various ships of opportunity since 2012) - NS: Nordic Sea data from cruises in 2002-2018 - AS: Arctic Ocean north of 72°N, in particular from two Tara cruises (in 2006-2008 and 2013) and expeditions since 2020 - PM: miscellaneous data in tropical Pacific, Indian Ocean, Mediterranean Sea and Black Sea In some regions, such as in the Indian Ocean, it is valuable to combine different subsets to have the full data distribution. The files are in csv format reported, and starting with version V1, it is reported as: - Cruise name, station id, bottle number, day, month, year, hour, minute, latitude, longitude, pressure (db), temperature (°C), it, salinity (pss-78), is, dissolved oxygen (micromol/kg), io2, δ18O, iO, d D, iD, d-excess, id, method type - Temperature is an in situ temperature - Salinity is a practical salinity it, is, io2, iO, iD, id are quality indices equal to: - 0 no quality check (but presumably good data) - 1 probably good data - 2 good data - 3 probably bad data - 4 certainly bad data - 9 missing data (and the missing data are reported with an unlikely missing value) The method type is 1 for IRMS measurements, 2 for CRDS measurement of a saline water sample, 3 for CRDS measurement of a distilled water sample.

In October 2019 we chose 15 sites from the 2019 EVHOE survey for environmental DNA (eDNA) sampling. The French international EVHOE bottom trawl survey is carried out annually during autumn in the BoB to monitor demersal fish resources. At each site, we sampled seawater using Niskin bottles deployed with a circular rosette. There were nine bottles on the rosette, each of them able to hold ∼5 l of water. At each site, we first cleaned the circular rosette and bottles with freshwater, then lowered the rosette (with bottles open) to 5 m above the sea bottom, and finally closed the bottles remotely from the boat. The 45 l of sampled water was transferred to four disposable and sterilized plastic bags of 11.25 l each to perform the filtration on-board in a laboratory dedicated to the processing of eDNA samples. To speed up the filtration process, we used two identical filtration devices, each composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 l min–1 ), a VigiDNA 0.20 μm filtration capsule (SPYGEN, le Bourget du Lac, France), and disposable sterile tubing. Each filtration device filtered the water contained in two plastic bags (22.5 l), which represent two replicates per sampling site. We followed a rigorous protocol to avoid contamination during fieldwork, using disposable gloves and single-use filtration equipment and plastic bags to process each water sample. At the end of each filtration, we emptied the water inside the capsule that we replaced by 80 ml of CL1 conservation buffer and stored the samples at room temperature following the specifications of the manufacturer (SPYGEN, Le Bourget du Lac, France). We processed the eDNA capsules at SPYGEN, following the protocol proposed by Polanco-Fernández et al., (2020). Half of the extracted DNA was processed by Sinsoma using newly developped ddPCR assays for European seabass (Dicentrachus labrax), European hake (Merluccius merluccius) and blackspot seabream (Pagellus bogaraveo).  The other half of the extracted DNA was analysed using metabarcoding with teleo primer. The raw metabarcoding data set is available at https://www.doi.org/10.16904/envidat.442 Bottom trawling using a GOV trawl was carried out before or after water sampling. The catch was sorted by species and catches in numbers and weight were recorded. No blackspot seabream individuals were caught.   Data content: * ddPCR/: contains the ddPCR counts and DNA concentrations for each sample and species. * SampleInfo/: contains the filter volume for each eDNA sample. * StationInfo/: contains metadata related to the data collected in the field for each filter. * Metabarcoding/: contains metabarcoding results for teleoprimer. * Trawldata/: contains catch data in numbers and weight (kg).      

This visualization product displays the total abundance of marine macro-litter (> 2.5cm) per beach per year from Marine Strategy Framework Directive (MSFD) monitoring surveys. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter 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 and reference lists used on a European scale. Preliminary processings were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Some categories & some litter types like organic litter, small fragments (paraffin and wax; items > 2.5cm) and pollutants have been removed. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata); - Normalization of survey lengths to 100m & 1 survey / year: in some cases, the survey length was not exactly 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of items (normalized by 100 m) = Number of litter per items x (100 / survey length) Then, this normalized number of items is summed to obtain the total normalized number of litter for each survey. Finally, the median abundance for each beach and year is calculated from these normalized abundances per survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. Percentiles 50, 75, 95 & 99 have been calculated taking into account MSFD data for all years. More information is available in the attached documents. Warning: the absence of data on the map does not necessarily mean that it does not exist, but that no information has been entered in the Marine Litter Database for this area.

The present repository makes available the model, material and outputs of the ISIS-Fish modeling work showcased in the peer-reviewed scientific article by Bastardie et al. 2025. As part of the SEAwise research project (seawiseproject.org), we used an ISIS-Fish database (Mahevas et al 2003, Pelletier et al. 2009, isis-fish.org) previously developed within the MACCO project which describes the mixed demersal fishery in the Bay of Biscay. For this application, the spatial extent of the fishery is the Bay of Biscay, defined here by ICES divisions 8a, 8b and 8d and the resolution chosen is 1/16 ICES statistical rectangle. The biological module (Vajas et al. 2024) includes 7 species of economic interest in the mixed demersal fishery: European hake (Merluccius merluccius), common sole (Solea solea), Norway lobster (Nephrops norvegicus), megrim (Lepidorhombus whiffiagonis), anglerfish (Lophius piscatorius) and two ray species (Raja clavata, Leucoraja naevus). The fishing activities module (Mahevas et al. 2024) is made up of 41 demersal fleets (including all French vessels < 12 meters and > 12 meters fishing in this area, Spanich, UK and Belgium fleets) and 431 métiers (combination of a gear, location and mix of target species) catching these 7 species, as target or bycatch. Monthly effort of a fleet distributes among the possible métiers (those historically practiced). The biological and fishing activity modules are identical to the published version. The original model used here has been calibrated on historical catch data 2015-2018 by tuning accessibility and catchability parameters. In the present application the Bay of Biscay model is used to investigate the spatial- and effort- based fisheries management strategies. Consistently with for a task of the SEAwise project (Bastardie et al. 2024) simulations were conducted from 2021 onwards, projecting the effect of an implementation of 3 different closures from 2022 to 2050, under current fishing effort conditions or in a context of fishing effort reduction. Outcomes of these simulations are averaged over short/medium (10 year horizon) and long-term period (20 year horizon). The data project includes: 1) the database including the biological module and fishing activity module; 2) 8 .properties files, each corresponding to one combination of management measure and closure, to restore the simulations parameters in the ISIS-Fish interface and reproduce the simulation runs; 3) the .java scripts to force effort dynamics and simulate spatio-temporal closures, as well as generate the main output files - they will be called by the ISIS-Fish software once the simulations restored 4) the .rds containing the main outputs of the simulations and the associated .html document displaying the R code to compute the indices of interest at different levels of aggregation and reproduce the figures in Bastardie et al. 2025. All files are provided in the Zip. Associated with this material, a study summary and a readme .docx are provided. The first one provides context on the present work and describes the model and simulations' design. The second provides guidelines to reproduce the simulations and their derived outcomes from the data project material made available in this repository. They are both directly downloadable from this repository and are also copied to the zipped folder containing the data project. All the data are reproducible using isis-fish-4.4.8.1 (isis-fish.org; available at forge.codelutin.com) and R 4.2.0.

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.