LOCEAN has been in charge of analyzing the isotopic composition of the dissolved inorganic carbon (DIC) in sea water collected during a series of cruises or ships of opportunity mostly in the southern Indian Ocean , the North Atlantic, and the equatorial Atlantic, but also in the Mediterranean Sea and in the equatorial Pacific. The LOCEAN sea-water samples for δ13CDIC were collected in 125/25 ml glass bottles until 2022/since then and poisoned with HgCl2 (1 ml of saturated solution) before storage in a dark room à 4°C until their measurement. The DIC was extracted from the seawater by acidification with phosphoric acid (H3PO4 85%) and CO2 gas that was produced was collected in a vacuum system following the procedure described by Kroopnick (1974). The isotopic composition of CO2 was determined using a dual inlet-isotopic ratio mass spectrometer (SIRA9-VG) by comparing the 13C/12C ratio of the sample to the 13C/12C ratio of a reference material, the Vienna-Pee Dee Belemnite (V-PDB). The isotopic composition is expressed in the δ-unit defined by Craig (1957)(method type 2).  Experience showed that samples older than 3-4 years are likely to have experienced conservation issues and have been dismissed. The mass spectrometer has worked very well until 2014-2015. Afterwards, its aging as well as the aging of the preparation line resulted in more data loss, and often less accurate results. The preparation line was renovated in 2019, and analyses in 2020 were run manually, often repeating the measurement a second time for each sample. Up to 2007-2008, δ13CDIC values have a precision of±0.01 ‰ (Vangriesheim et al.,2009) and a reproducibility of±0.02 ‰. After an interlaboratory comparison exercise led by Claire Normandeau (Dalhousie  University),  results  suggest  that  recent  LOCEAN  samples have a slightly poorer reproducibility (±0.04 ‰ ) as well as an offset of -0.13‰ (details available in Reverdin et al., ESSD 2018) that is confirmed by Becker et al. 2016 work by comparison with other cruises after removing the anthropogenic signal. Recent comparisons in early May 2021 with Orsay GEOPS facility samples suggest that the current offset is much smaller and might be +0.03‰. LOCEAN has installed in 2021 a new measurement device by coupling a Picarro G2131-I cavity ring down spectrometer (CRDS) with a CO2 extractor (Apollo SciTech) that will measure at the same time DIC (method type 3) (Leseurre, 2022). Since then, all water samples have been analyzed on this device. Part of the data set, as well as a scientific context and publications are also presented on the WEB site https://www.locean-ipsl.upmc.fr/oceans13c. Individual files correspond to regional subsets of the whole dataset. The file names are based on two letters for the region followed by (-) the cruise or project name (see below) followed by –DICisotopes, followed by either -s (surface data) or -b (subsurface data), and a version number (-V0, …): example SI-OISO-DICisotopes-s-V0; the highest version number corresponds to the latest update of the cruise/project data set, and can be directly downloaded. Earlier versions can be obtained on request, but are not recommended. The region two letters are the followings:   - SI: station and surface data in the Southern Indian Ocean that include cruises : INDIGO I (1985 – stn) (https://doi.org/10.17600/85000111) CIVA I (1993 – stn & surf) (https://doi.org/10.17600/93000870) (Archambeau et al., JMS 1998) ANTARES (1993 – stn & surf) (https://doi.org/10.17600/93000600) OISO (*) (since 1998 – stn & surf) (https://doi.org/10.18142/228) (Racapé et al., Tellus 2010, Leseurre, 2022)   - EA: station and surface data in the Tropical Atlantic Ocean that include cruises : EQUALANT (1999 & 2000 – surf) (https://doi.org/10.18142/98) EGEE (2005 to 2007 – stn & surf) (https://doi.org/10.18142/95) PIRATA (since 2013 – stn & surf) (https://doi.org/10.18142/14) EUMELI 2 (1991 – stn) (https://doi.org/10.17600/91004011)  (Pierre et al., JMS 1994) BIOZAIRE 3 (2003 – stn & surf ) (https://doi.org/10.17600/3010120) (Vangriesheim et al., DSRII, 2009) TARA-Microbiomes (2021 - stn & surf)   - NA : station and surface data in the North Atlantic Subpolar gyre that include cruises : OVIDE (**) (since 2002 – stn & surf) (https://doi.org/10.17882/46448) (Racapé et al., 2013) RREX (2017 – stn & surf) (https://doi.org/10.17600/17001400) SURATLANT (since 2010 - surf) (https://doi.org/10.17882/54517) (Racapé et al., BG 2014 ; Reverdin et al., ESSD 2018, Leseurre, 2022) NUKATUKUMA (since 2017- surf)   - MS: station data in the Mediterranean sea that include cruises : ALMOFRONT 1 (1991 – stn) (https://doi.org/10.17600/91004211) VICOMED 3 (1990 – stn) (https://doi.org/10.17600/90000711)   - PO: tropical Pacific that include cruises : PANDORA (2012 – stn) (https://doi.org/10.17600/12010050) ALIZE2 (1991 – stn & surf) (https://doi.org/10.17600/91002711) (Laube-Lenfant and Pierre, Oceanologica Acta 1994)   - SO: station and surface data in the Southern Ocean (except OISO) that include cruises: TARA-Microbiomes (2021-2022, stn & surf) AGULHASII-072022 (2022, stn) CONFLUENCE (1993-1994, stn)   - AO: station and surface data in the Arctic Ocean and nearby seas that include cruises: GREENFEEDBACK (2024, stn&surf) TCA (2024, stn) REFUGE ARCTIC (2024, stn) (*) The values for cruises OISO19, 21 and 22 are doubtful (for some, too low) and will require further investigation to find whether adjusted values can be proposed. (**) Some of the OVIDE cruises are also referred to as or GEOVIDE (in 2014), and BOCATS (in 2016). CATARINA, BOCATS1 and BOCATS2 (PID2019-104279GB-C21/AEI/10.13039/501100011033) cruises were funded by the Spanish Research Agency  The values of the OVIDE 2010 stations are doubtful (too low), but no particular error was found, and they have been left in the files.   Data The files are in csv format reported as: - Cruise name, station id, (bottle number), day, month, year, hour, minute, longitude, latitude, pressure (db), depth (m), temperature (°C), temperature qc, salinity (pss-78), salinity qc, d13CDIC, d13CDIC qc, method type - Temperature is an in situ temperature - Salinity is a practical salinity - Method type (1) acid CO2 extraction from helium stripping technique coupled to mass spectrometer, (2) acid CO2 extraction in a vacuum system coupled to mass spectrometer,(3) CO2 extractor (Apollo SciTech) coupled to CRDS measurements. Temperature qc, salinity qc, d13CDIC qc 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 PHYTOBS-MARCOBOLO dataset comprises long-term time series on marine microphytoplankton, from 2003 to 2021, along the entire French metropolitan coastline. Microphytoplankton data cover microscopic taxonomic identifications and counts. The PHYTOBS-MARCOBOLO dataset corresponds to a dataset extracted from the PHYTOBS network (DOI:10.17882/85178). The PHYTOBS network provides the scientific community and stakeholders with validated and qualified data on the biomass, abundance and composition of marine microphytoplankton in coastal and lagoon waters, with the aim of supporting scientific research. PHYTOBS-MARCOBOLO is a dataset used as part of the Horizon Europe MARCO-BOLO project (https://marcobolo-project.eu/), in which we are currently working to understand and analyze multi-decadal trends in coastal and marine biodiversity on a European scale. The PHYTOBS-MARCOBOLO dataset gathers data from 18 sampling sites, selected from the PHYTOBS-Network dataset according to requirements of time series quality and geographical location of sampling sites established as part of the MARCO-COLO project. This dataset was also formatted according to a template imposed for the European project.

Three saltmarshes, Aiguillon, Brouage, Fier d'Ars, located in the Pertuis-Charentais Sea along the south-west coast of France, were studied to evaluate their sediment and mass accumulation rates (SAR; MAR) based on 210Pb and 137Cs profiles in sediments. Coastal saltmarshes play indeed an essential role in providing services such as coastal protection and supporting biodiversity. Saltmarshes are also critical environments for the accumulation of sedimentary organic carbon (blue carbon). However, the number of studies on saltmarshes remains underrepresented compared to studies on mangroves and seagrass. This work is a contribution to the effort to document sediment and mass accumulation rates of saltmarshes.A total of 16 1m sediment cores were collected in the three saltmarshes (Aiguillon, Brouage, Fier d'Ars) in 2021 and 2022 using an Eijkelkamp stainless steel peat sampler. Each sediment core was sampled 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 (210Pb, 226Ra, 137Cs, 228Th, 137Cs). Combining excess 210Pb and 137Cs has allowed to establish a reliable chronology of sediment deposition on a multidecadal timescale.

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 dataset contains standardized, harmonized and validated data collections from beach litter (monitoring and other sources). Datasets concerning beach and 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. For beach litter, the harmonized datasets contain all unrestricted EMODnet Chemistry data on beach litter, including monitoring data, data from cleaning surveys and data from research. A relevant part of the monitoring data has been considered for assessment purposes by the European institutions and therefore is tagged as MSFD_monitoring. EMODnet beach litter data and databases are hosted and maintained by 'Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Division of Oceanography (OGS/NODC)' from Italy. Data are formatted following Guidelines and forms for gathering marine litter data, which can be found at: https://doi.org/10.6092/15c0d34c-a01a-4091-91ac-7c4f561ab508 The updated vocabularies of admitted values are available at: https://nodc.ogs.it/marinelitter/vocab The European harmonized dataset is provided as csv format in two files, one containing the survey data and one containing the survey metadata. The dataset is available through direct download or through ERDDAP.

The willingness to pay (WTP) of people to protect animal populations can be used as a tool for these populations’ conservation. The WTP reflects the non-use value of animals, which can be significant for charismatic species. This value can be used as an economic criterion for decision-makers in order to recommend protective measures. The definition of the WTP to protect a species is challenging, as valuation methods are time-consuming and expensive. To overcome these limitations, we built a benefit transfer function based on 112 valuation studies and apply it to 440 Mediterranean marine species. We extracted these species from the IUCN database and retrieved some required parameters from, amongst others, the FishBase database. Marine mammals appear to have the highest WTP value followed in order by sea turtles, sharks and rays, and ray-finned fishes. Commercial fish species appear to have the highest values amongst the fish class.

The dataset dcm_dtb.txt contains bio-optical measurements and environmental parameters associated with  Deep Chlorophyll Maxima (DCM) acquired by BGC-Argo profiling floats. For each BGC-Argo profile the data files includes the World Meteorological Organization (WMO) and profile numbers, the Data Assembly Center (DAC), the geographical position (LON and LAT), the date of the profile in Julian Day (JULD) and in YYYY-MM-DD format; the region of the profile (REGION, acronyms detailed in the region.txt file), the DCM zonal attribution (ZONE, acronyms detailed in the zone.txt file), the vertical resolution of measurements of the concentration of the chlorophyll a [Chla] and of the backscattering coefficient (bbp) within the 250 first meters, the Mixed Layer Depth (MLD, m), the qualification of the vertical profile (DCM_TYPE) as Deep Biomass Maximum (3), Deep photoAcclimation Maximum (2), or presenting no DCM (1); the depth of the DCM (DCM_DEPTH); the chlorophyll a concentration (CHLA_DCM, mg chla m-3 ) the backscattering coefficient (BBP_DCM, m-1), and the Brunt-Vaisala frequency (N2_DCM) at the DCM depth; the nitracline depth (NCLINE_DEPTH, m) and steepness (NCLINE_STEEP, µmol NO3 m-3 m-1), the mean nitrate concentration within the Mixed Layer (NO3_MEAN_MLD, µmol NO3 m-3), the mean daily Photosynthetically Available Radiation in the Mixed Layer (MEAN_IPAR_MLD, E m -1 d -1), the daily Photosynthetically Available Radiation at the nitracline depth (IPAR_NCLINE, E m-2 d-1);  and the [Chla] measured by satellite (CHLA_SAT, mg chla m-3). The dataset shape_NASTG_ASEW.txt contains the seasonal median, the first and third quartiles of the [Chla] and of the bbp profiles for the North Atlantic Subtropical Gyre and Atlantic SubEquatorial Waters regions. The dataset climato_NASTG_ASEW.txt contains the monthly mean and standard deviations of the DCM depth (DCM_depth), the isolume depth of daily Photosynthetically Available Radiation of 20 E m-2 d-1 (iPAR_20), the nitracline depth, and the Mixed Layer Depth (MLD) for the profiles within the North Atlantic Subtropical Gyre and Atlantic SubEquatorial Waters regions.  The qualification and processing of the BGC-Argo profiles, as well as the DCM detection (DCM_TYPE) and the estimation of the environmental parameters, were applied as described from Cornec, M., Claustre, H., Mignot, A., Guidi, L., Lacour, L., Poteau, A., D’Ortenzio, F.,Gentili, B., Schmechtig, C., (to be updated.) Deep Chlorophyll Maxima in the global ocean: occurrences, drivers and characteristics. Global Biogeochemical Cycles, to be updated The [Chla] satellite variable was obtained by the match of each BGC-Argo profile with a L3S [Chla] product from the Ocean Colour-Climate Change Initiative v4.0 database merging observations from MERIS, MODIS, VIIRS and SeaWiFs, at a monthly and 4x4-km-pixel resolution, up to December 31, 2019 (ftp://oc-cci-data:ELaiWai8ae@oceancolour.org/occci-v4.2/).

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)

Particularly suited to the purpose of measuring the sensitivity of benthic communities to trawling, a trawl disturbance indicator (de Juan and Demestre, 2012, de Juan et al. 2009) was proposed based on benthic species life history traits to evaluate the sensibility of mega- and epifaunal community to fishing pressure known to have a physical impact on the seafloor (such as dredging and bottom trawling). The selected biological traits were chosen as they determine vulnerability to trawling: mobility, fragility, position on substrata, average size and feeding mode that can easily be related to the fragility, recoverability and vulnerability ecological concepts. Life history traits of species have been defined from the BIOTIC database (MARLIN, 2014) and from information given by Le Pape et al. (2007), Brindamour et al. (2009) and Garcia (2010). For missing life history traits, additional information from literature has been considered. The five categories retained are life history functional traits that were selected based on the knowledge of the response of benthic taxa to trawling disturbance (de Juan and Demestre, 2012). They reflect respectively the possibility to avoid direct gear impact, to benefit from trawling for feeding, to escape gear, to get caught by the net and to resist trawling/dredging action, each of these characteristics being either advantageous or sensitive to trawling. Then, to allow quantitative analysis, a score was assigned to each category: from low vulnerability (0) to high vulnerability (3). The five categories scores were then summed for each taxon (the highly vulnerable taxon could reach the maximum score is 15) and this value may be considered as a species index of sensitivity to trawling disturbance. The scores of 773 taxa commonly found in bottom trawl by-catch in the southern North Sea, English Channel and north-western Mediterranean were described.

The diet and stable isotopic (i.e. δ15N and δ13C values) compositions of eels have been studied during each season of 2019 with a fyke net in six estuaries located along the French coast of the eastern English Channel (Slack, Wimereux, Liane, Canche, Authie and Somme estuaries) (10.1371/journal.pone.0270348).