Assess whether the MPA network constitutes a representative and coherent network as described in article 13 of the Marine Strategy Framework Directive 3 products were specified to achieve the second objectif of the challenge: ATLANTIC_CH02_Product_2 / Quantitative analyse of MPA coherency The product comprises 4 components: Distribution of vulnerable marine habitats : Shape represent the distribution of different vulnérable habitats Distribution biologically or ecologically significant areas (EBSAs) Critical areas of vulnerable species Distribution of indicator species The method used computes the percentage coverage between : Vulnerable habitats like carbon sinks, reef, kelp... Ecologically or biologically significant area Life critical area (feeding , breeding, migratory routes, spawning, dispersal larvea, nursery…) for indicator species Distribution of indicator species in the study area and MPA network location.

North Atlantic basin average at Pentadal (5-year) resolution time-series of the ocean heat storage (upper 700m) and kinetic energy. Use gridded information to calculate the local heat storage and average kinetic energy as a 5 year average and then calculate the basin average.

Identified areas across the north Atlantic which have been flagged as priority locations for quality bathymetry data, in the context of expanded shipping traffic and port expansions. The reference to determine the priority survey areas in combination with shiping routes and port locations are the bathymetric data sources used for product 2( GEBCO, EMODnet bathymetry, USGS and CHS) and the depth uncertainty derived of Product 2. The adequacy assessment of the input characteristics of Product 3 is limited to the shiping routes and port locations.

This product attempt to follow up on the sea level rise per stretch of coast of the North Atlantic, over past 100 years as follows: • Characterization of absolute sea level trend at annual resolution, along the coasts of EU Member States (including Outermost Regions), Canada, Faroes, Greenland, Iceland, Mexico, Morocco, Norway and USA; The stretchs or coast are defined by the administrative regions of the Atlantic Coast: • from NUTS3** administrative division for EU countries (see Eurostat), and • from GADM*** administrative divisions for non-EU countries. ** Third level of Nomenclature of Territorial Units for Statistics *** Global Administrative Areas For absolute sea level trend for 100 years we extract the information from grided sea level reconstruction datasets (using a combination of satellite and tide gauges) and extrapolate it to the nearest strecth of coast. The product is Provided in tabular form and as a map layer.

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The time series are derived from the regional chlorophyll reprocessed (REP) product as distributed by CMEMS. This dataset, derived from multi-sensor (SeaStar-SeaWiFS, AQUA-MODIS, NOAA20-VIIRS, NPP-VIIRS, Envisat-MERIS and Sentinel3A-OLCI) Rrs spectra produced by CNR using an in-house processing chain, is obtained by means of the Mediterranean Ocean Colour regional algorithms: an updated version of the MedOC4 (Case 1 (off-shore) waters, Volpe et al., 2019, with new coefficients) and AD4 (Case 2 (coastal) waters, Berthon and Zibordi, 2004). The processing chain and the techniques used for algorithms merging are detailed in Colella et al. (2021). Monthly regional mean values are calculated by performing the average of 2D monthly mean (weighted by pixel area) over the region of interest. The deseasonalized time series is obtained by applying the X-11 seasonal adjustment methodology on the original time series as described in Colella et al. (2016), and then the Mann-Kendall test (Mann, 1945; Kendall, 1975) and Sens’s method (Sen, 1968) are subsequently applied to obtain the magnitude of trend. '''CONTEXT''' Phytoplankton and chlorophyll concentration as a proxy for phytoplankton respond rapidly to changes in environmental conditions, such as light, temperature, nutrients and mixing (Colella et al. 2016). The character of the response depends on the nature of the change drivers, and ranges from seasonal cycles to decadal oscillations (Basterretxea et al. 2018). Therefore, it is of critical importance to monitor chlorophyll concentration at multiple temporal and spatial scales, in order to be able to separate potential long-term climate signals from natural variability in the short term. In particular, phytoplankton in the Mediterranean Sea is known to respond to climate variability associated with the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) (Basterretxea et al. 2018, Colella et al. 2016). '''CMEMS KEY FINDINGS''' In the Mediterranean Sea, the trend average for the 1997-2020 period is slightly negative (-0.580.62% per year). Due to the change in processing techniques and chlorophyll retrieval, this trend estimate cannot be compared directly to those previously reported. The observations time series (in grey) shows minima values have been quite constant until 2015 and then there is a little decrease up to 2020, when an absolute minimum occurs with values lower than 0.04 mg m-3. Throughout the time series, maxima are variable year by year (with absolute maximum in 2015, >0.14 mg m-3), showing an evident reduction since 2016. In the last years of the series, the decrease of chlorophyll concentrations is also observed in the deseasonalized timeseries (in green) with a marked step in 2020. This attenuation of chlorophyll values in the last years results in an overall negative trend for the Mediterranean Sea. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00259

PPRIF

List of fish stocks referenced for the year 2018. The repository includes 477 stocks. Each stock is identified by a unique key in accordance with the ICES codification in use. Each record contains a stock identifier, a species or group of species identifier according to the ASFIS/FAO classification, the English stock name, the Latin name of the species, the assessment area according to the FAO codification of fishing sectors. When the stock assessment area groups a series of sectors, the first and last sectors in the series are separated by a dash.

Particuliers bénéficiant du portage de repas à domicile

Annual time series of eel recruitement, (2005-2014) • Time series of glass and yellow eel for those rivers used in the annual ICES advice to the EU • Location, data availability and long term annual (LTA) eel recruiment per river mouth

The three digital maps provided in this product aim to assess the degree of Offshore windfarm siting suitability existing over a geographical area with a focal point where waters of France and Spain meet in Biscay Bay on 500 m depth. The maps display respectively the spatial distribution of the average and lowest windfarm siting suitability scores along with the average wind speed distribution over a time period of 10 years. They are part of a process set up to assess the fit for use quality of the currently available datasets to support a preliminary selection of potential offshore sites for wind energy development. To build these maps, GIS tools were applied to several key spatial datasets from the 5 data type domains considered in the project: Air, Marine Water, Riverbed/Seabed, Biota/Biology and Human Activities, collated during the initial stages of the project. Initially, each selected dataset was formatted and clipped to the study area extent and spatially classified according to suitability scores, to define raster layers with the variables depicting levels of current anthropogenic and environmental spatial occupation of activities, seabed depth and slope, distances to shoreline, shipping intensity, mean significant wave height, and substrate type. These pre-processed layers were employed as inputs for applying a spatial multi-criteria model using a wind farming suitability classification based on a discrete 5 grades index, ranging from Very Low up to Very High suitability. In adition to suitability maps, an average wind speed spatial distribution map for a 10 years period, at 10 m height, was obtained over the study area from the raster processing of a wind speed time series of monthly means available from daily wind analysis data. The characteristics of the datasets used in this exercise underwent an appropriateness evaluation procedure based on a comparison between their measured quality and those specified for the product. All the spatial information made available in these maps and from the subsequent appropriateness analysis of the datasets, contributes to a clearer overview of the amount of public-access baseline knowledge currently existing for the North Atlantic basin area.