The eleven collected wild strains of T. lutea were compared phenotypically, in particular with regard to their pigment and lipid profiles. The genome of each T. lutea strain was also sequenced to investigate the genetic structure and genome organisation of this species. Collected data were summarized in a genome browser to provide easy-to-use support for the scientific community (https://genomes-catalog.ifremer.fr). This provides an important resource- to understand, exploit and predict the biodiversity of this species.

Potentialités agronomiques par culture (blé, haricot, maïs, orge, tabac et tournesol).

Maps of seasonal p90 (percentile 90) of Chla on the North Atlantic basin for the past ten years (2005-2014) using the Global Copernicus chla level 4 (L4) products (resolution of 4 km). Method as Gohin Francis, Saulquin Bertrand, Bryere Philippe (2010) Atlas de la Température, de la concentration en Chlorophylle et de la Turbidité de surface du plateau continental français et de ses abords de l’Ouest européen. Ifremer. http://archimer.ifremer.fr/doc/00057/16840/

Temporal series (annual mean values) of temperature for each river mouth.Temporal series (annual mean values) of temperature for each river mouth.

Calculation of the average annual sediment balance per stretch of coast for the past 50 years for all coastal zones bordering the North Atlantic Ocean. For this scale of study, this has been interpreted in terms of shoreline advance / retreat in mm/year. Required data sources are therefore national or international datasets giving this parameter directly. It is also possible to utilise more aggregated data sources, but annual values would then be approximated from them. The main challenge in producing this product lies with obtaining datasets which include this data from multiple countries and potentially multiple languages, since this data is usually produced as a result of comparatively small scale studies.

The in-situ TAC integrates and quality control in a homogeneous manner in situ data from outside Copernicus Marine Environment Monitoring Service (CMEMS) data providers to fit the needs of internal and external users. It provides access to integrated datasets of core parameters for initialization, forcing, assimilation and validation of ocean numerical models which are used for forecasting, analysis and re-analysis of ocean physical and biogeochemical conditions. The in-situ TAC comprises a global in-situ centre and 6 regional in-situ centres (one for each EuroGOOS ROOSs). The focus of the CMEMS in-situ TAC is on parameters that are presently necessary for Copernicus Monitoring and Forecasting Centres namely temperature, salinity, sea level, current, waves, chlorophyll / fluorescence, oxygen and nutrients. The initial focus has been on observations from autonomous observatories at sea (e.g. floats, buoys, gliders, ferrybox, drifters, and ships of opportunity). The second objective was to integrate products over the past 25 to 50 years for re-analysis purposes... Gathering data from outsider organisations requires strong mutual agreements. Integrating data into ONE data base requires strong format standard definition and quality control procedures. The complexity of handling in situ observation depends not only on the wide range of sensors that have been used to acquire them but, in addition to that, the different operational behaviour of the platforms (i.e vessels allow on board human supervision, while the supervision of others should be put off until recovering or message/ping reception)°

Temporal series (annual mean values) and long term average (LTA) of temperature for each river mouth.

Temporal series (annual mean values) with error of estimation and Long Term Average (LTA) with error of estimation of total phosphate load for each river mouth where in situ data is available. Different sources can be mixed if any.

The EEA coastline dataset is created for detailed analysis with a Minimum Mapping Unit of e.g. 1:100000, for geographical Europe. The coastline is a hybrid product obtained from satellite imagery from two projects: 1) EUHYDRO (Pan-European hydrographic and drainage database) [https://land.copernicus.eu/pan-european/satellite-derived-products/eu-hydro/view] and 2) GSHHG (A Global Self-consistent, Hierarchical, High-resolution Geography Database) [http://www.soest.hawaii.edu/pwessel/gshhg/]. The defining criteria was altitude level = 0 from EUDEM [https://land.copernicus.eu/pan-european/satellite-derived-products/eu-dem/view]. Outside the coverage of the EUDEM, the coastline from GSHHG was used without modifications. A few manual amendments to the dataset were necessary to meet requirements from EU Nature Directives, Water Framework Directive and Marine Strategy Framework Directive. In 2015, several corrections were made in the Kalogeroi Islands (coordinates 38.169, 25.287) and two other Greek little islets (coordinates 36.766264, 23.604318), as well as in the peninsula of Porkkala (around coordinates 59.99, 24.42). In this revision (v3, 2017), 2 big lagoons have been removed from Baltic region, because, according to HELCOM, are freshwater lagoons. This dataset is a polygon usable as a water-land mask.

Combined product of Water body silicate based on DIVA 4D 10-year analysis on five regions : Northeast Atlantic Ocean, North Sea, Baltic Sea, Black Sea, Mediterranean Sea. The boundaries and overlapping zones between these five regions were filtered to avoid any unrealistic spatial discontinuities. This combined water body silicate product is masked using the relative error threshold 0.5. Units: umol/l