Prises IPE présentes sur les territoires gérés par la SPL NATHD

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The BALTIC_OMI_TEMPSAL_sst_trend product includes the cumulative/net trend in sea surface temperature anomalies for the Baltic Sea from 1993-2021. The cumulative trend is the rate of change (°C/year) scaled by the number of years (29 years). The SST Level 4 analysis products that provide the input to the trend calculations are taken from the reprocessed product SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 with a recent update to include 2021. The product has a spatial resolution of 0.02 degrees in latitude and longitude. The OMI time series runs from Jan 1, 1993 to December 31, 2021 and is constructed by calculating monthly averages from the daily level 4 SST analysis fields of the SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 from 1993 to 2021. See the Copernicus Marine Service Ocean State Reports for more information on the OMI product (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018). The times series of monthly anomalies have been used to calculate the trend in SST using Sen’s method with confidence intervals from the Mann-Kendall test (section 3 in Von Schuckmann et al., 2018). '''CONTEXT''' SST is an essential climate variable that is an important input for initialising numerical weather prediction models and fundamental for understanding air-sea interactions and monitoring climate change. The Baltic Sea is a region that requires special attention regarding the use of satellite SST records and the assessment of climatic variability (Høyer and She 2007; Høyer and Karagali 2016). The Baltic Sea is a semi-enclosed basin with natural variability and it is influenced by large-scale atmospheric processes and by the vicinity of land. In addition, the Baltic Sea is one of the largest brackish seas in the world. When analysing regional-scale climate variability, all these effects have to be considered, which requires dedicated regional and validated SST products. Satellite observations have previously been used to analyse the climatic SST signals in the North Sea and Baltic Sea (BACC II Author Team 2015; Lehmann et al. 2011). Recently, Høyer and Karagali (2016) demonstrated that the Baltic Sea had warmed 1-2oC from 1982 to 2012 considering all months of the year and 3-5oC when only July- September months were considered. This was corroborated in the Ocean State Reports (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018). '''CMEMS KEY FINDINGS''' SST trends were calculated for the Baltic Sea area and the whole region including the North Sea, over the period January 1993 to December 2021. The average trend for the Baltic Sea domain (east of 9°E longitude) is 0.049 °C/year, which represents an average warming of 1.42 °C for the 1993-2021 period considered here. When the North Sea domain is included, the trend decreases to 0.03°C/year corresponding to an average warming of 0.87°C for the 1993-2021 period. Trends are highest for the Baltic Sea region and North Atlantic, especially offshore from Norway, compared to other regions. '''DOI (product):''' https://doi.org/10.48670/moi-00206

Zone arrière du point de mutualisation (ZAPM) des territoires gérés par la SPL NATHD déployées

The dataset presents the potential combined effects of land-based pressures on marine species and habitats estimated using the method for assessment of cumulative effects, for the entire suite of pressures and a selected set of marine species groups and habitats by an index (Halpern et al. 2008). The spatial assessment of combined effects of multiple pressures informs of the risks of human activities on the marine ecosystem health. The methodology builds on the spatial layers of pressures and ecosystem components and on an estimate of ecosystem sensitivity through an expert questionnaire. The raster dataset consists of a division of the Europe's seas in 10km and 100 km grid cells, which values represents the combined effects index values for pressures caused by land-based human activities. The relative values indicate areas where the pressures potentially affect the marine ecosystem. This dataset underpins the findings and cartographic representations published in the report "Marine Messages" (EEA, 2020).

Zone arrière du point de mutualisation (ZAPM) des territoires gérés par la SPL NATHD non déployées

This metadata corresponds to the EUNIS Littoral biogenic habitat types (salt marshes), distribution based on vegetation plot data dataset. Littoral biogenic habitats (commonly known as salt marshes) are formed by animals such as worms and mussels or plants. The verified saltmarsh habitat samples used are derived from the Braun-Blanquet database (http://www.sci.muni.cz/botany/vegsci/braun_blanquet.php?lang=en) which is a centralised database of vegetation plots and comprises copies of national and regional databases using a unified taxonomic reference database. The geographic extent of the distribution data are all European countries except Armenia and Azerbaijan. The dataset is provided both in Geodatabase and Geopackage formats.

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' Oligotrophic subtropical gyres are regions of the ocean with low levels of nutrients required for phytoplankton growth and low levels of surface chlorophyll-a whose concentration can be quantified through satellite observations. The gyre boundary has been defined using a threshold value of 0.15 mg m-3 chlorophyll for the Atlantic gyres (Aiken et al. 2016), and 0.07 mg m-3 for the Pacific gyres (Polovina et al. 2008). The area inside the gyres for each month is computed using monthly chlorophyll data from which the monthly climatology is subtracted to compute anomalies. A gap filling algorithm has been utilized to account for missing data. Trends in the area anomaly are then calculated for the entire study period (September 1997 to December 2020). '''CONTEXT''' Oligotrophic gyres of the oceans have been referred to as ocean deserts (Polovina et al. 2008). They are vast, covering approximately 50% of the Earth’s surface (Aiken et al. 2016). Despite low productivity, these regions contribute significantly to global productivity due to their immense size (McClain et al. 2004). Even modest changes in their size can have large impacts on a variety of global biogeochemical cycles and on trends in chlorophyll (Signorini et al. 2015). Based on satellite data, Polovina et al. (2008) showed that the areas of subtropical gyres were expanding. The Ocean State Report (Sathyendranath et al. 2018) showed that the trends had reversed in the Pacific for the time segment from January 2007 to December 2016. '''CMEMS KEY FINDINGS''' The trend in the North Atlantic gyre area for the 1997 Sept – 2020 December period was positive, with a 0.39% year-1 increase in area relative to 2000-01-01 values. This trend has decreased compared with the 1997-2019 trend of 0.45%, and is statistically significant (p<0.05). During the 1997 Sept – 2020 December period, the trend in chlorophyll concentration was positive (0.24% year-1) inside the North Atlantic gyre relative to 2000-01-01 values. This time series extension has resulted in a reversal in the rate of change, compared with the -0.18% trend for the 1997-209 period and is statistically significant (p<0.05). Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00226

remontée geocatalogue mtd tag spécifique "données ouvertes"

This metadata corresponds to the EUNIS Coastal habitat types, predicted distribution of habitat suitability dataset. Coastal habitats are those above spring high tide limit (or above mean water level in non-tidal waters) occupying coastal features and characterised by their proximity to the sea, including coastal dunes and wooded coastal dunes, beaches and cliffs. Includes free-draining supralittoral habitats adjacent to marine habitats which are normally only very rarely subject to any type of salt water, in as much as they may be inhabited predominantly by terrestrial species, strandlines characterised by terrestrial invertebrates and moist and wet coastal dune slacks and dune-slack pools. Supralittoral sands and wracks may be found also in marine habitats (M). Excludes supralittoral rock pools and habitats, the splash zone immediately above the the mean water line, as well the spray zone and zone subject to sporadic inundation with salt water in as much as it may be inhabited predominantly by marine species, which are included in marine (M). The modelled suitability for EUNIS coastal habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. Note however that it is not representing the actual distribution of the habitat type. As predictors for the suitability modelling not only climate and soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables, like land use, vegetation height, phenology, and LAI (Leaf Area Index). Because the EBV's are restricted by the extent of the remote sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats.

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