'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The low resolution ocean physics analysis and forecast for the North-West European Shelf is produced using a forecasting ocean assimilation model, with tides, at 7 km horizontal resolution. The ocean model is NEMO (Nucleus for European Modelling of the Ocean), using the 3DVar NEMOVAR system to assimilate observations. These are surface temperature, vertical profiles of temperature and salinity, and along track satellite sea level anomaly data. The model is forced by lateral boundary conditions from the UK Met Office North Atlantic Ocean forecast model and by the CMEMS Baltic forecast product [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=BALTICSEA_ANALYSISFORECAST_PHY_003_006 BALTICSEA_ANALYSISFORECAST_PHY_003_006]. The atmospheric forcing is given by the operational UK Met Office Global Atmospheric model. The river discharge is from a daily climatology. Further details of the model, including the product validation are provided in the [http://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-NWS-QUID-004-001.pdf CMEMS-NWS-QUID-004-001]. Products are provided as hourly instantaneous and daily 25-hour, de-tided, averages. The datasets available are temperature, salinity, horizontal currents, sea level, mixed layer depth, and bottom temperature. Temperature, salinity and currents, as multi-level variables, are interpolated from the model 51 hybrid s-sigma terrain-following system to 24 standard geopotential depths (z-levels). Grid-points near to the model boundaries are masked. The product is updated daily, providing a 6-day forecast and the previous 2-day assimilative hindcast. See [http://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-NWS-PUM-004-001_002.pdf CMEMS-NWS-PUM-004-001_002] for further details. '''Associated products:''' This model is coupled with a biogeochemistry model (ERSEM) available as CMEMS product [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NWSHELF_ANALYSISFORECAST_BGC_004_002 NWSHELF_ANALYSISFORECAST_BGC_004_002] A reanalysis product is available from: [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NWSHELF_MULTIYEAR_PHY_004_009 NWSHELF_MULTIYEAR_PHY_004_009]. '''DOI (product) :''' https://doi.org/10.48670/moi-00057

Première utilisation du sol, devant l'agriculture et loin devant l'urbanisme, la forêt couvre 45 % du territoire aquitain. La région se caractérise par la domination d'une essence, le pin maritime. Celui-ci couvre plus de la moitié de la surface forestière régionale. Outre sa valeur patrimoniale, cette forêt génère une activité économique qui représente environ 3 milliards d'euros. Ce secteur forêt-bois est donc un formidable gisement d'emplois, principalement en milieu rural. Cet espace occupé par la forêt attise néanmoins des convoitises pour différents types d'usage: l'urbanisation, les installations photovoltaïques ou encore l'agriculture.

L’objectif de cette étude est d’illustrer à l’aide d’indicateurs les conséquences de choix de gestion imposés par cinq scénarios socioéconomiques prospectifs appliqués à une large zone forestière pour les 60 prochaines années. Le cas d’étude choisi est la zone centrée sur la commune de Pontenx-les-Forges dans le sud-ouest de la France et couvrant 101000 hectares. Cet article présente une description de la zone d’étude et des itinéraires sylvicoles mis en œuvre par les propriétaires forestiers selon des scénarios. À l’aide d’un simulateur pilotant deux modèles de croissance, l’évolution de la zone d’étude à l’échelle de chaque parcelle est synthétisée par 9 indicateurs sur une période de 60 ans : le volume sur pied, le carbone sur pied, le volume total exploité, la valeur commerciale sur pied, le volume de l’arbre moyen, la vulnérabilité au vent et au feu, et des indices de biodiversité. Un des principaux résultats de cette étude est de montrer l’amplitude des changements pour la production et le volume sur pied : selon les scénarios les récoltes annuelles peuvent varier de 50 % dès 2030. Par conséquent, d’autres indicateurs sont impactés comme la biodiversité, la vulnérabilité au vent ou au feu. Pourtant, l’espèce dominante est maintenue et le comportement partiellement conservateur des types de propriétaires est pris en compte. En conclusion, des améliorations pour de futures simulations sont envisagées ; dans ce but, des synergies avec la télédétection sont nécessaires pour la collecte des données d’initialisation sur de larges territoires, ce qui permettra d’améliorer la précision des résultats.

Développement d'une méthode pour inventorier les airiaux, afin de les cartographier à différentes échelles prédéfinies.

Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of Solitary Scleractinian fields assemblage in the Celtic Sea. This community is considered ecologically coherent according to the cluster analysis conducted by Parry et al. (2015) on image sample. Modelling its distribution complements existing work on their definition and offers a representation of the extent of the areas of the north-east Atlantic where they can occur based on the best available knowledge. This work was performed at the University of Plymouth in 2021.

This product displays the stations where benzo[A]pyrene has been measured and the values present in EMODnet Chemistry infrastructure are always above the limit of detection or quantification (LOD/LOQ), i.e quality value equal to 1. It is necessary to take into account that LOD/LOQ can change with time. These products aggregate data by station, producing only one final value for each station (above, below or above/below). EMODnet Chemistry has included the gathering of contaminants data since the beginning of the project in 2009. For the maps for EMODnet Chemistry Phase III, it was requested to plot data per matrix (water,sediment, biota), per biological entity and per chemical substance. The series of relevant map products have been developed according to the criteria D8C1 of the MSFD Directive, specifically focusing on the requirements under the new Commission Decision 2017/848 (17th May 2017). The Commission Decision points to relevant threshold values that are specified in the WFD, as well as relating how these contaminants should be expressed (units and matrix etc.) through the related Directives i.e. Priority substances for Water. EU EQS Directive does not fix any threshold values in sediments. On the contrary Regional Sea Conventions provide some of them, and these values have been taken into account for the development of the visualization products. To produce the maps the following process has been followed: 1. Data collection through SeaDataNet standards (CDI+ODV) 2. Harvesting, harmonization, validation and P01 code decomposition of data 3. SQL query on data sets from point 2 4. Production of map with each point representing at least one record that match the criteria The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols. Preliminary processing were necessary to harmonize all the data : • For water: contaminants in the dissolved phase; • For sediment: data on total sediment (regardless of size class) or size class < 2000 μm • For biota: contaminant data will focus on molluscs, on fish (only in the muscle), and on crustaceans • Exclusion of data values equal to 0

EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Mediterranean Sea. Data were aggregated and quality controlled by the 'Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)' in Greece. ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets. Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions (https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/. When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.025 kg/L. The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV).

The Coastal Zones (CZ) LC/LU product for 2018 is providing a detailed Land Cover / Land Use (LC/ LU) dataset for areas along the coastline of the EEA38 countries and the United Kingdom, with reference year 2018 for the classification. This product monitors landscape dynamics in European coastal territory to an inland depth of 10 km with a total area of approximately 730,000 km², with all the relevant areas (estuaries, coastal lowlands, nature reserves). The production of the coastal zone layers was coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme, as part of the Copernicus Land Monitoring Service (CLMS) Local Component. The Coastal Zones product covers a buffer zone of coastline derived from EU-Hydro v1.1. Land Cover/Land Use (LC/LU) layer is extracted from Very High Resolution (VHR) satellite data and other available data. The class definitions follow the pre-defined nomenclature on the basis of Mapping and Assessment of Ecosystems and their Services (MAES) typology of ecosystems (Level 1 to Level 4) and CORINE Land Cover adapted to the specific characteristics of coastal zones. The classification provides 71 distinct thematic classes with a Minimum Mapping Unit (MMU) of 0.5 ha and a Minimum Mapping Width (MMW) of 10 m. The product is available for the 2012 and 2018 reference year including change mapping. This CZ dataset is distributed in vector format, in a single OGC GeoPackage SQLite file covering the area of interest.