Description ot the spatial layers attributes of sea level trend for the last 50 and 100 years for the Mediterranean basin and for each NUTS3 region along the coast.

Description ot the spatial layers attributes of sea level trend for the last 10 years for the Mediterranean basin and for each NUTS3 region along the coast.

Description of de desirable and recomended attributes for generating time-series of sea surface annual average temperature for the last 10, 50 and 100 yrs for the Mediterranean basin and for each NUTS region along the coast.

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.

Specification of the desirable and recommended product attributes for sediment mass budget at the coast for the last 10, 50 and 100 years for the Mediterranean basin and for each NUTS3 region along the coast.

Description of the attributes for the time-series of sea surface annual average temperature for the last 10, 50 and 100 yrs for the Mediterranean basin and for each NUTS region along the coast.

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.

Global Fishing Watch is working across the globe to provide governments and authorities with actionable reports and capacity building to help strengthen fisheries monitoring and compliance. Our global team of experts produce analyses to inform monitoring, control and surveillance of fisheries in five key areas: - Illegal, unreported and unregulated fishing - Transshipment - Port controls - Marine protected areas - Operation support Collaboration and information sharing are integral to achieving well-managed fisheries. By working with stakeholders and making analyses available to national, regional and intergovernmental partners, Global Fishing Watch is enabling fisheries agencies to make more informed and cost-efficient decisions. Topics: - Commercial fishing, Global Fishing Watch is harnessing innovative technology to turn transparent data into actionable information and drive tangible change in the way that fisheries are governed. - Transshipment, Through publicly sharing map visualisations and creating data and analysis tools, we seek to inform management and policy efforts and provide a more complete picture of transshipment at sea. - Marine protected areas, Global Fishing Watch is harnessing the data and technology revolution to support the effective design, management and monitoring of marine protected areas.

The main aim of this product was to define the suitability of offshore sites in the area between the borders of France-Spain-Italy for wind farm development. The adopted approach classifies wind speed data by their level of suitability, ranging from a grade 5 for exclusion zones, to a grade 1 for areas deemed appropriate for wind farm development. The quality indexes adopted were based on mean and variation statistical measures taking into consideration both the expected energy potential and the corresponding variability.

The main aim of this product was to define the suitability of offshore sites in the area between the borders of France-Spain-Italy for wind farm development. The adopted approach classifies wind speed data by their level of suitability, ranging from a grade 5 for exclusion zones, to a grade 1 for areas deemed appropriate for wind farm development. The quality indexes adopted were based on mean and variation statistical measures taking into consideration both the expected energy potential and the corresponding variability.