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oceans

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  • EMODnet bathymetry is composed of a multitude of datasets from a multitude of data providers. Users of the resulting grid and associated datasets need to be able to evaluate at the grid node level the quality of the bathymetric data and product they will be using. For this EMODnet Bathymetry has introduced a Quality index (QI). The QI is available as a WFS service providing vector data and as WMS providing the QI as an image service. The aim of the quality index is to: • help data users to evaluate quickly the dataset they are about to request, • indicate to the EMODnet Basin coordinators what are the limitations of the dataset they are about to merge while building the EMODnet DTM and to • be used as the basis of the evaluation of the quality of the EMODnet DTM. Service URL: https://ows.emodnet-bathymetry.eu/wfs

  • Moving 10-years analysis of phosphates at Mediterranean Sea 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 centered average of each season. Decades span from 1960-1969 until 2004-2013. Observational data span from 1960 to 2013. Depth range (IODE standard depths): -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, -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. Profiles were interpolated at standard depths using weighted parabolic interpolation algorithm (Reiniger and Ross, 1968). GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5. DIVA settings: A constant value for signal-to-noise ratio was used equal to 3. Correlation length was 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 constraint applied: no. Originators of Italian data sets-List of contributors • Brunetti Fabio (OGS) • Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306 • Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987 • Cataletto Bruno (OGS) • Cinzia Comici Cinzia (OGS) • Civitarese Giuseppe (OGS) • DeVittor Cinzia (OGS) • Giani Michele (OGS) • Kovacevic Vedrana (OGS) • Mosetti Renzo (OGS) • Solidoro C.,Beran A.,Cataletto B.,Celussi M.,Cibic T.,Comici C.,Del Negro P.,De Vittor C.,Minocci M.,Monti M.,Fabbro C.,Falconi C.,Franzo A.,Libralato S.,Lipizer M.,Negussanti J.S.,Russel H.,Valli G., doi:10.6092/e5518899-b914-43b0-8139-023718aa63f5 • Celio Massimo (ARPA FVG) • Malaguti Antonella (ENEA) • Fonda Umani Serena (UNITS) • Bignami Francesco (ISAC/CNR) • Boldrini Alfredo (ISMAR/CNR) • Marini Mauro (ISMAR/CNR) • Miserocchi Stefano (ISMAR/CNR) • Zaccone Renata (IAMC/CNR) • Lavezza, R., Dubroca, L. F. C., Ludicone, D., Kress, N., Herut, B., Civitarese, G., Cruzado, A., Lefèvre, D., Souvermezoglou, E., Yilmaz, A., Tugrul, S., and Ribera d’Alcala, M.: Compilation of quality controlled nutrient profiles from the Mediterranean Sea, doi:10.1594/PANGAEA.771907, 2011. Units: umol/l

  • Distribution of catch from deep-sea impacting fishing on the North Atlantic (18°N to 76°N and 36°E to 98°W), for the period 2010-2015. The average of yearly fishing catch for the period 2010-2015 is displayed as an index on the ATLAS grid of 25km * 25km resolution. Source data originated from the Global Fisheries Landings V4.0 database. The dataset was filtered to select only the fishing gears that have an impact on large areas of the seafloor (dredges, bottom trawls, and Danish seines). Within each cell, all remaining catch records were summed to get the total catch rate of the considered year. This dataset was built to feed a basin-wide spatial conservation planning exercise, targeting the deep sea of the North Atlantic. The goal of this approach was to identify conservation priority areas for Vulnerable Marine Ecosystems (VMEs) and deep fish species, based on the distribution of species and habitats, human activities and current spatial management.

  • The objective of this tender is to examine the current data collection, observation and data assembly programmes in the Meditterranean Sea, identify gaps and to evaluate how they can be optimised.

  • ERA‐40 is a re‐analysis of meteorological observations from September 1957 to August 2002 produced by the European Centre for Medium‐Range Weather Forecasts (ECMWF)

  • The project’s purpose is to introduce new low trophic species, products and processes in marine aquaculture value chains across the Atlantic. Low trophic species are those organisms low on the food chain as sea urchins or mussels. The five chosen value chains of AquaVitaeinclude macroalgae, Integrated Multi-Trophic Aquaculture (IMTA), echinoderm species (e.g. sea urchins), shellfish and finfish. IMTA is a process that farms several species together using waste from one species as feed for another. One of the main expected results of the project would be the creation of real and meaningful collaborative links between researchers, industry and other aquaculture stakeholders in the Atlantic area. AquaVitae will contribute to the Belém Statement, the joint Declaration on Atlantic Ocean Research and Innovation Cooperation between the European Union, Brazil, and South Africa through: - Setting up a network for knowledge and research exchange through the Atlantic. - Sustainable use of marine resources with a circular economy approach. - Better monitoring of aquaculture activities through new and emerging technologies. - Contributing to the well-being of aquaculture communities. - Enhancing citizen engagement through training and outreach activities. - Setting up student exchanges and industrial apprenticeships.