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2016

526 record(s)
 
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  • A total number of 277 water samples were collected during distinct oceanographic cruises or at fixed stations across coastal systems of France and Senegal. The seawater samples were progressively filtered onto size-fractionated filters (representing micro, nano and pico-plankton). Metabarcoding of the V4 domain of the Eukaryotic 18S rDNA region was carried out to characterize the genetic diversity of the sampled communities. Genomic DNA was extracted following the DNA extraction kit Nucleospin Plant II (Macherey-Nagel) and the V4 markers were amplified with a taq polymerase (Phusion High-Fidelity PCR Master Mix with GC Buffer). Sequencing was performed by the Genotoul sequencing platform (get.genotoul.fr) with the Illumina MISeq method (2x250 bp). The present dataset gathers the different results issued from sequencing. This dataset was submitted to sequence cleaning, filtering, taxonomic assignment and OTU clustering, which resulted in a final dataset also presented.

  • Confidence in the full output of the 2016 EUSeaMap broad-scale predictive model, produced by EMODnet Seabed Habitats. Values are on a range from 1 (low confidence) to 3 (high confidence). Confidence is calculated by amalgamating the confidence values of the underlying applicable habitat descriptors used to generate the habitat value in the area in question. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed Substrate Riverine input Confidence in habitat descriptors are driven by the confidence in the source data used to determine the descriptor, and the confidence in the threshold/margin (areas closer to a boundary between two classes will have lower confidence). Confidence values are also available for each habitat descriptor and input data layer.

  • Auteur(s): Cha Lucie , Analyse des paysages de méga évènements sur des sites internationaux. Historique de l'évolution de expositions géantes. Projet d'aménagement de la ville de Bordeaux qui a posé sa candidature pour l'Exposition universelle de 2025

  • The Drifting Buoys GDAC -Global Data Assembly Centre- is the repository of surface drifters data. Both NRT -Near Real Time- and DM -Delayed Mode- data are available on the GDAC. Drifters report generally trajectories, sea-surface temperatures, atmospheric pressures at sea-level, as well as sea-surface salinity or sub-surface temperature in the ocean top layer.

  • Cette donnée représente l'ensemble des ERP géolocalisés du Lot-et-Garonne. Le périmètre de production concerne les ERP de catégories 1, 2, 3, 4, et 5 avec local à sommeil soit 1069 ERP. Seuls les ERP de catégorie 5 sans local à sommeil ne sont pas classés. Tous les types d'ERP sont représentés sauf les ERP type CTS. Etant donné les changements fréquents dont les ERP sont sujets, la mise à jour de ces données ne peut être permanente.

  • Moving 10-years analysis of Silicate at Northeast Atlantic Ocean for each season. - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December Every year of the time dimension corresponds to the 10-year centred average of each season. Decades span - from 1963-1972 until 2005-2014 (winter) - from 1979-1988 until 2005-2014 (spring) - from 1990-1999 until 2005-2014 (summer) - from 1964-1973 until 2005-2014 (autumn) Observational data span from 1962 to 2014. Depth range (IODE standard depths): -3000.0, -2500.0, -2000.0, -1750, -1500.0, -1400.0, -1300.0, -1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -20.0, -10.0, -5.0, -0.0 Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5 DIVA settings. Signal to noise ratio and correlation length were optimized and filtered vertically and a seasonally-averaged profile was used. Logarithmic transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. Detrending of data: no, Advection consraint applied: no. Units: umol/l

  • Specification of the desirable and recommended product attributes for generating time series of sea level trend for the last 10 years for the Mediterranean basin for each NUTS3 region along the coast.

  • Suitability index of a wind farm in the NWMed concerning the environmental resources, the natural barriers, human activities, MPA and fisheries.

  • Data from FerryBoxes on ships of opportunity going on permanent routes are stored inside this database (ferrydata.hzg.de). Parameters are temperature, salinity, chlorophyll-a fluorescence, oxygen and different others. The data model is transect oriented. A data portal to access and visualise the data is also provided.

  • Specification of the desirable and recommended product attributes for generating time series of average annual sea-level rise for the last 50 and 100 yrs.