Assessment of the confidence limits of the data base by means of evaluation of the two involved numerical models: The wave model WAM (Parameter: Significant wave height Hs) and the Atmospheric model SKIRON (Parameter: Wind Speed 10m)

The average annual sediment balance per stretch of coast bordering the North Atlantic for the past 50 years.

Whole genome pooled sequencing of individuals from 4 populations and 3 different color phenotype in order to uncover the genetic variants linked to color expression in the pearl oyster P. margaritifera.

The raster dataset represents the intensity of species disturbance due to human presence along European coastlines. The dataset was created by combining the coastal urbanisation layer derived from Corine Land Cover 2012 (with the percentage of urbanised coastline per EEA 10 km grid cell) and the population density layer based on EUROSTAT NUTS 2016 data (with the population density in the NUTS 3 region corresponding to the coastal EEA 10 km grid cell). The dataset does not cover southern and western Mediterranean Sea, northern Black Sea and northernmost Atlantic Ocean. The dataset was prepared for the combined effect index produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.

Annual time series of eel escapement, (2008-2011): • Time series of silver eel escapement biomass for rivers monitored by EU member state every 3 years since 2008, and as defined in their Eel Management Plans (EMPs) • Maps of silver eel escapement biomass per Eel Management Unit (EMU could be a river, basin district, a region or a whole

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.

Rapport final ONF

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 has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The trend map is derived from version 5 of the global climate-quality chlorophyll time series produced by the ESA Ocean Colour Climate Change Initiative (ESA OC-CCI, Sathyendranath et al. 2019; Jackson 2020) and distributed by CMEMS. The trend detection method is based on the Census-I algorithm as described by Vantrepotte et al. (2009), where the time series is decomposed as a fixed seasonal cycle plus a linear trend component plus a residual component. The linear trend is expressed in % year -1, and its level of significance (p) calculated using a t-test. Only significant trends (p < 0.05) are included. '''CONTEXT''' Phytoplankton are key actors in the carbon cycle and, as such, recognised as an Essential Climate Variable (ECV). Chlorophyll concentration is the most widely used measure of the concentration of phytoplankton present in the ocean. Drivers for chlorophyll variability range from small-scale seasonal cycles to long-term climate oscillations and, most importantly, anthropogenic climate change. Due to such diverse factors, the detection of climate signals requires a long-term time series of consistent, well-calibrated, climate-quality data record. Furthermore, chlorophyll analysis also demands the use of robust statistical temporal decomposition techniques, in order to separate the long-term signal from the seasonal component of the time series. '''CMEMS KEY FINDINGS''' The average global trend for the 1997-2020 period was 0.59% per year, with a maximum value of 25% per year and a minimum value of -6.1% per year. Positive trends are pronounced in the high latitudes of both northern and southern hemisphehres. The significant increases in chlorophyll reported in 2016-2017 (Sathyendranath et al., 2018b) for the Atlantic and Pacific oceans at high latitudes continued to be observed after the 2020 extension, as well as the negative trends over the equatorial Pacific and the Indian Ocean Gyre. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00230

The data set aims to contribute to a better biological characterization of European marine ecosystems. As such it represents probabilities of EUNIS (EUropean Nature Information System) habitat presence at Level 3 for marine habitats including information on sea ice coverage (this corresponds to EUNIS level 2 for terrestrial habitats). The map combines spatially explicit data on marine bathymetry and sea-bed with non-spatially referenced habitat information of the EUNIS classification. The objective of the data set produced by EEA and its Topic Centre ETC/ULS is to improve the biological description of marine based ecosystem types and their spatial distribution. The work supports Target 2 Action 5 of the implementation of the EU Biodiversity Strategy to 2020, established to achieve the Aichi targets of the Convention of Biological Diversity (CBD). It further addresses the MAES process (Mapping and Assessing of Ecosystems and their Services). The data set represents 2 classes of the MAES classification level 3, namely “Marine inlets and transitional waters” and “Marine”. The dataset comprises the following information: • Sea region (1 – Arctic, 2 – Atlantic, 3 – Baltic, 4 – Mediterranean, 5 – Black Sea) • Sea zone (1 – Littoral, 2 – Infralittoral, 3 – Circalittoral, 4 – Offshore circalittoral, 5 – Upper bathyal, 6 – Lower bathyal, 7 – Abyssal,8 - Coastal Lagoons, 9 - Coastal Lagoons) • Substrate (0 – undetermined substrate, 1 – rock and biogenic, 3 – coarse sediment, 4 – mixed sediment, 5 – sand, 6 – mud) • Sea ice coverage (0 – no sea ice presence, 1 – seasonal sea ice presence, 2 – perennial sea ice presence)