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The dataset includes age- and length-based catch per unit effort data for commercial fish species collected by the French trawl survey EVHOE.
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The Pélagiques Gascogne (PELGAS, Doray et al., 2000) integrated survey aims at assessing the biomass of small pelagic fish and monitoring and studying the dynamics and diversity of the Bay of Biscay pelagic ecosystem in springtime. PELGAS has been conducted within the EU Common Fisheries Policy Data Collection Framework and Ifremer’s Fisheries Information System. Details on survey protocols and data processing methodologies can be found in Doray et al., (2014, 2018). This dataset comprises the abundance (no. of individuals), biomass (metric tons), mean length (cm), mean weight (g) of marine organisms collected by midwater trawling to identify fish echoes detected during PELGAS surveys (2000-2018). All parameters have been raised to the trawl haul level. Trawl haul metadata and species reference list are also provided.
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This is the FAO Fishery and Aquaculture Reference Data repository: Codes and reference data for fishing gear, species, currencies, commodities, countries and others.
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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.
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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.
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Global Fishing Watch's AIS Apparent Fishing Effort dataset, version 3.0 (March 2025 release). Data is available for 2012 to 2024 and is based on positions of more than 190,000 unique automatic identification system (AIS) devices on fishing vessels, of which up to around 96,000 are active in a given year. Fishing vessels are identified via a machine learning model, vessel registry databases, and manual review by Global Fishing Watch and regional experts. Vessel time is measured in hours, calculated by assigning to each AIS position the amount of time elapsed since the previous AIS position of the vessel. The time is counted as apparent fishing hours if the Global Fishing Watch fishing detection model, a neural network machine learning model, determines the vessel is engaged in fishing behavior during that AIS position. Data are spatially binned into grid cells that measure 0.01 or 0.1 degrees on a side. The coordinates defining each cell are provided in WGS84 and correspond to the lower-left corner. Data are available in three formats: fishing hours by flag state and gear type at 100th degree resolution; monthly apparent fishing hours by flag state and gear type at 10th degree resolution; and fishing hours by MMSI at 10th degree resolution. The dataset is accompanied by a table of vessel information such as gear type, flag state and dimensions. Free for non-commercial use. This static dataset covers 2012 to 2024. For more recent data, or for a custom area, use the Global Fishing Watch APIs or the gfwr (R) and gfw-api-python-client (Python) packages, linked below. Read the data caveats before interpreting results.
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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).
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This folder contains two examples of PAGURE datasets, corresponding to three surveys: -CGFS conducted in 2018 in the English Channel (Northeast Atlantic) -EPIBENGOL conducted in 2019 in the Gulf of Lion (Western Mediterranean) -EVHOE conducted in 2020 in the Bay of Biscay and Celtic Shelf (Northeast Atlantic) Files include metadata for the sampling stations, annotation files. A readme tex file contains the links to the voyage metadata This folder is aimed at providing an example of documented underwater imagery dataset. These data are part of the data exchange conducted in the QuatreA collaboration between the French Research Institute for the Exploitation of the Sea (Ifremer), the Commonwealth Scientific and Industrial Research Organisation (CSIRO), and the University of Tasmania (UTAS).
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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/).
Catalogue PIGMA