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  • 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). 

  • 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).      

  • 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/).

  • SOMLIT (Service d'Observation en Milieur Littoral) : a French Coastal Monitoring Network Coastal zones are where land, ocean and atmosphere interact. They are important for the exchange of matter and energy, and play a key role in (biogeo)chemical cycles at global scale. These environments are characterised by significant spatial and temporal variability of their physico-chemical and biological parameters due to local and seasonal meteorological drivers which are exacerbated by large-scale climate drivers (e.g. global warming, modification of the wind regime) and local-scale anthropogenic drivers (e.g. nutrient cycle changes linked to the use of fertilisers or the construction of large installations such as dams). These driving mechanisms are often interconnected. In the context of global warming (due to­­ climate and human-induced changes), the identification and understanding of their impact on coastal marine and littoral ecosystems is essential. The scientific objective of SOMLIT is to 1) characterise the multi-decadal evolution of coastal marine and littoral ecosystems, and 2) determine the climatic and anthropogenic drivers. In order to meet this objective, a nationally coordinated multi-site monitoring system was set up in the mid-1990s. The observation strategy is the same for each of the 12 monitored ecosystems with fortnightly sampling and/or measurements, at high tide (for sites subject to tides): 1) in surface-water for a range of 15 parameters (temperature, salinity, dissolved oxygen, pH, nitrate, nitrite, ammonium, phosphate, silicate, suspended particulate matter, chlorophyll a, particulate organic carbon and nitrogen and stable isotopes of particulate organic carbon and nitrogen), 2) in surface-water for a range of 26 parameters of numbering and optical characteristics of pico- and nanoplankton), and 3) along the water column for temperature, salinity, fluorescence and PAR (vertical profiles of multi-parameter probes). SOMLIT’s activities are carried out under a quality assurance / quality control process based on the ISO 17025 standard. SOMLIT’s service provision objectives are to provide data and logistical support for research and other observation activities. SOMLIT has been officially accredited since 1996 as one of the CNRS (French National Centre for Scientific Research) National Observation Services (SNO). SOMLIT’s coordination is hosted by the Observatoire Aquitain des Sciences de l'Univers (University of Bordeaux / CNRS) and the service relies on strong partnerships with nine other institutions (University of Lille, University of the Littoral Opal Coast, University of Caen Normandy, Sorbonne University, University of Western Brittany, La Rochelle University, University of Montpellier, Aix Marseille University, National Museum of Natural History). SOMLIT is one of the nine networks that compose France’s Coastal Research Infrastructure (ILICO).  SOMLIT has strong ties with ILICO’s other networks such as the SNOs MOOSE (Mediterranean Ocean Observing System on Environment), PHYTOBS (microphytoplankton monitoring) and COAST-HF (Coastal Ocean Observing System - High Frequency).

  • This database contains hauls collated from 1965 to 2019, from fisheries dependent and independent data, from across eastern Atlantic waters and French Mediterranean waters. From this data diadromous fish spatio-temporal data was cleaned and standardised.

  • Gironde estuary environmental parameters and SPM maps generated from 41 Landsat-8/OLI and Sentinel-2/MSI images acquired over the period 2013-2018. Except bathymetry and daily river discharge data, that are accessible on public platforms, the dataset includes all of the time seris used in the publication: Analysis of suspended sediment variability in a large highly-turbid estuary using a 5-year-long remotely-sensed data archive at high resolution, Journal of Geophysical Research: Oceans, DOI:10.1029/2019JC015417.

  • This dataset contains bio-optical measurements and environmental parameters associated with  Deep Chlorophyll Maxima acquired by BGC-Argo profiling floats and matched with mesoscale eddies location from the Ocean Eddy Detection and Tracking Algorithms (TOEeddies) Atlas. For each BGC-Argo profile the data files includes the World Meteorological Organistion (WMO) and profile numbers, geographical position (LON and LAT), the date of the profile in Julian Day (JULD); the qualification of the vertical profile (CARAC_BIO) as Deep Biomass Maximum (DBM), Deep photoAcclimation Maximum (DAM), or presenting no DCM (NO); at the depth of the maximum (DCM_DEPTH), the chlorophyll a concentration (CHLA_DCM, mg chla m-3 ) and the backscattering coefficient (BBP_DCM, m-1); the Mixed Layer Depth (MLD, m), the nitracline depth (NCLINE, m), the mean daily Available PAR in the Mixed Layer Depth (MIPAR_MLD, E m -1 d -1), the daily Available PAR at the nitracline depth (IPAR_NCLINE, E m-2 d-1); the location of the profile (CARAC_EDDY) as being inside the core/periphery (IN/_EN) of a cyclonic/anticyclonic eddy (DEP_/P_), or outside eddy influence (OUT); the processing level (MODE) of the ADT maps used for the TOEddies detection, either Near Real Time (-1), or Delayed Mode (1). The qualification and processing of the BGC-Argo profiles, as well as the DCM detection (DAM/DBM/NO) 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.  (2021). Deep chlorophyll maxima in the global ocean: Occurrences, drivers and characteristics. Global Biogeochem Cycles 35. https://doi.org/10.1029/2020GB006759 Data relative to mesoscale eddies were produced by processing daily 0.25°x0.25° AVISO Absolute Dynamical Topography (maps produced by Ssalto/Duacs and distributed by Copernicus-Marine Environment Services) with the TOEddies algorithm (Laxenaire, R., Speich, S., Blanke, B., Chaigneau, A., Pegliasco, C., & Stegner, A. (2018). Anticyclonic Eddies Connecting the Western Boundaries of Indian and Atlantic Oceans. Journal of Geophysical Research: Oceans, 123(11), 7651–7677. https://doi.org/10.1029/2018JC014270)

  • An observation network was initiated in 2021 in the framework of the CocoriCO2 project to monitore carbonate parameters along the French coastal systems. Six sites were selected along the French Atlantic and Mediterranean coastlines based on their importance in terms of shellfish production and the presence of high- and low-frequency monitoring activities. At each site, autonomous pH sensors were deployed both inside and outside shellfish production areas, next to high-frequency CTD (conductivity-temperature-depth) probes operated through two operating monitoring networks (SNO COAST-HF and Ifremer ECOSCOPA). pH sensors were set to an acquisition rate of 15 min and discrete seawater samples were collected biweekly in order to control the quality of pH data (laboratory spectrophotometric measurements) as well as to measure total alkalinity and dissolved inorganic carbon concentrations for full characterization of the carbonate system. While this network has been up and running for more than two years, the acquired dataset has already revealed important differences in terms of pH variations between monitored sites related to the influence of diverse processes (freshwater inputs, tides, temperature, biological processes).    

  • These data are outputs of a spatio-temporal model inferring fish distribution. The maps are based on high-resolution catch data (VMS-logbook). They have a montly time resolution and a 0.05° spatial resolution. Four demersal species of the Bay of Biscay are available in the dataset: common sole (Solea solea), megrim (Lepidorhombus whiffiagonis), anglerfish (Lophius spp) and thornback ray (Raja clavata). Maps are provided for year 2008 to 2018 ; they were produced in the context of the MACCO project (https://www.macco.fr/en/accueil-english/), an Ifremer project that aims at proposing alternative management strategies for the mixed demersal fisheries of the Bay of Biscay.

  • 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.