Understanding the dynamics of species interactions for food (prey-predator, competition for resources) and the functioning of trophic networks (dependence on trophic pathways, food chain flows, etc.) has become a thriving ecological research field in recent decades. This empirical knowledge is then used to develop population and ecosystem modelling approaches to support ecosystem-based management. The TrophicCS data set offers spatialized trophic information on a large spatial scale (the entire Celtic Sea continental shelf and upper slope) for a wide range of species. It combines ingested prey (gut content analysis) and a more integrated indicator of food sources (stable isotope analysis). A total of 1337 samples of large epifaunal invertebrates (bivalve mollusks and decapod crustaceans), zooplankton, fish and cephalopods, corresponding to 114 species, were collected and analyzed for stable isotope analysis of their carbon and nitrogen content. Sample size varied between taxa (from 1 to 52), with an average of 11.72 individuals sampled per species, and water depths ranged from 57 to 516 m. The gut contents of 1026 fish belonging to ten commercially important species: black anglerfish (Lophius budegassa), white anglerfish (Lophius piscatorius), blue whiting (Micromesistius poutassou), cod (Gadus morhua), haddock (Melanogrammus aeglefinus), hake (Merluccius merluccius), megrim (Lepidorhombus whiffiagonis), plaice (Pleuronectes platessa), sole (Solea solea) and whiting (Merlangius merlangus) were analyzed. The stomach content data set contains the occurrence of prey in stomach, identified to the lowest taxonomic level possible. To consider potential ontogenetic diet changes, a large size range was sampled. The TrophicCS data set was used to improve understanding of trophic relationships and ecosystem functioning in the Celtic Sea. When you use the data in your publication, we request that you cite this data paper. If you use the present data set (TrophicCS) for the majority of the data analyzed in your study, you may wish to consider inviting at least one author of the core team of this data paper to become a collaborator /coauthor of your paper.

210Pb, 226Ra and 137Cs were measured by non-destructive gamma spectrometry on marine sediment cores, collected during RIKEAU 2002 cruise on board r/v Thalia, on the shelf of the Bay of Biscay

Data collected by the Spindrift 2 Sails of Change vessel during its attempt at the round-the-world sailing record, the Jules Verne Trophy. More information at https://spindrift-racing.com/fr/.

The network was initiated by IFREMER from 1993 to 2009 (under the acronym REMORA) to study the rearing performance of the Pacific oyster Crassostrea gigas at a national scale. To do so, the network monitored annually the mortality and growth of standardized batches of 18-month-old oysters. Starting in 1995, the monitoring of the rearing performance of 6-month-old oyster spat was integrated into this network. These sentinel batches were distributed simultaneously each year on 43 sites and were monitored quarterly. These sites were distributed over the main French oyster farming areas and allowed a national coverage of the multiannual evolution of oyster farming performances. Most of the sites were located on the foreshore at comparable levels of immersion. Field studies were carried out by the "Laboratoires Environnement Ressources" (LER) for the sites included in their geographical area of investigation. Following the increase in spat mortality in 2008, the network evolved in 2009 (under the acronym RESCO). From this date, the network selected 13 sites among the 43 sites previously monitored in order to increase the frequency of visits (twice a month) and the number of sentinel batches. More precisely, sentinel batches of oysters corresponding to different origins (wild or hatchery, diploid or triploid) and to two rearing age classes (spat or 18-month-old adults) were selected. The monitoring of environmental variables (temperature, salinity) associated with the 13 sites was also implemented. The actions of the network have thus contributed to disentangle the biotic and abiotic parameters involved in mortality phenomena, taking into account the different compartments (environment / host / infectious agents) likely to interact with the evolution of oyster rearing performance. Finally, since 2015, the network has merged the RESCO and VELYGER networks to adopt the acronym ECOSCOPA. The general objective of this current network is to analyze the causes of spatio-temporal variability of the main life traits (Larval stage - Recruitment - Reproduction - Growth - Survival - Cytogenetic abnormalities) of the cupped oyster in France and to follow their evolution on the long term in the context of climate change. To do this, the network proposes a regular spatio-temporal monitoring of the major proxies of the life cycle of the oyster, organized in three major thematic groups: (1) proxies related to growth, physiological tolerance and survival of experimental sentinel populations over 3 age classes: (2) proxies related to reproduction, larval phase and recruitment of the species throughout its natural range in France, and: (3) proxies related to environmental parameters essential to the species (weather conditions, temperature, salinity, pH, turbidity, chlorophyll a and phytoplankton) at daily or sub-hourly frequencies. Working in a geographical network associating several laboratories, ECOSCOPA provide these monitoring within 8 sites selected among the previous ones to ensure the continuity of the data acquisition. Today, these 8 sites are considered as ecosystems of common interest, contrasted, namely : - The Thau lagoon - The Arcachon basin - The Marennes Oléron basin - The Bourgneuf Bay - The bay of Vilaine - The bay of Brest - The bay of Mont Saint Michel - The bay of Veys The ECOSCOPA network is therefore one of the relevant monitoring tools on a national scale, allowing to objectively measure through different proxies the general state of health of cultivated and wild oyster populations, and this for the different sensitive phases of their life cycle. This network aims at allowing a better evaluation, on the long term, of the biological risks incurred by the sector but also by the ecosystems, in particular under the increasing constraint of climatic and anthropic changes. Figure : Sites monitored by the ECOSCOPA network  

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/).

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 Commission for the Conservation Southern Bluefin Tuna collects a variety of data types from its Members and Cooperating Non-Members, including total catch, catch and effort data, and catch at size data. Catch, size and trade information is also collected through the Commission's Catch Documentation Scheme, Japanese import statistics, and other monitoring programs. Annual catches provided on this page are reported on a calendar year basis. CCSBT Members use quota years (not calendar years) for managing catching limits, but quota years differ between Members, so calendar years are used to provide catches on a common timescale. Relevant subsets and summaries of these data are provided below. All figures are subject to change as improved data or estimates become available. In particular, reviews of SBT data in 2006 indicated that southern bluefin tuna catches may have been substantially under-reported over the previous 10-20 years and the data presented here do not include estimates for this unreported catch. Also, data for the last reported year of catch (2020) are preliminary and are subject to revision. Any latitudes and longitudes presented in these summaries represent the north western corner of the relevant grid, which is a 5*5 grid unless otherwise specified. Other information on Members and Cooperating Non-Members fishing activities appears in the reports of the Extended Scientific Committee, Compliance Committee and Extended Commission.

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.

The Argo program provides an unprecedented volume of oceanographic data, yet the complexity of its dataset — involving multiple data modes, quality control flags, and metadata conventions — often hinders its direct usage. The EasyOneArgo initiative addresses this challenge by delivering simplified, high-quality subsets of Argo data, specifically designed to streamline user access and integration. The EasyOneArgo data product is comprised of 4 datasets: - EasyOneArgoTS – A curated selection of temperature-salinity profiles filtered by strict quality criteria and optimized across raw, real-time adjusted, and delayed-mode status. - EasyOneArgoTSLite – The vertically interpolated counterpart of EasyOneArgoTS, with standardized pressure levels between 2 and 6000 dbar. - EasyOneArgoBGC – A curated selection of biogeochemical profiles filtered by strict quality criteria. The BGC parameters include DOXY, NITRATE, PH, CHLA, BBP, and various radiometry parameters. All BGC data are adjusted either in real-time or in delayed-mode. Accompanying TS measurements are also included. - EasyOneArgoBGCLite – The vertically interpolated counterpart of EasyOneArgoBGC, with the same standardized pressure levels as EasyOneArgoTSLite. Note: The BGC vertical interpolation process involves pre-filtering the original data before interpolation. Hence the magnitudes of some of the features are modulated in the BGCLite dataset. Each profile in EasyOneArgo is packaged as a standalone CSV file, with metadata and indexes for seamless retrieval. This work represents a user-centric shift in Argo data delivery: no QC flags, no data modes, no data manuals — just good, clean, structured ocean data ready for immediate scientific application. The EasyOneArgo data product is publicly available through monthly FAIR-compliant releases. We invite community feedback for continued refinement. Please send any comments to Annie Wong (apsw.uw@gmail.com) or Thierry Carval (Thierry.Carval@ifremer.fr).