Map of seasonal averages of dissolved oxygen indicator (mg/l) for eutrophication for the past 10 years (2005-2014) in the Atlantic basin. It will be generated using in situ measurements of the different parameteres required to assess the dissolved oxygen indicator and the OSPAR Convention Common procedure methodology (OSPAR 2013, Common Procedure for the Identification of the Eutrophication Status of the OSPAR Maritime Area. Agreement 2013-08. 67 pp)

The Oil Platform Leaks challenge attempts to determine the likely trajectory of the slick and to release rapid information on the oil movement and environmental and coastal impacts in the form of a bulletin broadcast 72 hours after the event. This bulletin indicates what information can be provided, evidencing the fitness for use of the current available marine datasets, as well as pointing out gaps in the current Emodnet data collection framework. The exercise relies on two tools operated by CLS: The OSCAR model (Oil Spill Contingency and Response, operated at CLS under license) made available by SINTEF and used to simulate the oil spill fate and weathering at water surface, in the water column and along shorelines. A QGIS system to display and cross the oil spill forecast with coastal data (information on environment and human activities). The declarative data given for the OSCAR simulation are: Date and time of oil spill, Location and depth of oil spill, Oil API number or oil type name, Oil spill amount or oil spill rate

'''DEFINITION''' Volume transport across lines are obtained by integrating the volume fluxes along some selected sections and from top to bottom of the ocean. The values are computed from models’ daily output. The mean value over a reference period (1993-2014) and over the last full year are provided for the ensemble product and the individual reanalysis, as well as the standard deviation for the ensemble product over the reference period (1993-2014). The values are given in Sverdrup (Sv). '''CONTEXT''' The ocean transports heat and mass by vertical overturning and horizontal circulation, and is one of the fundamental dynamic components of the Earth’s energy budget (IPCC, 2013). There are spatial asymmetries in the energy budget resulting from the Earth’s orientation to the sun and the meridional variation in absorbed radiation which support a transfer of energy from the tropics towards the poles. However, there are spatial variations in the loss of heat by the ocean through sensible and latent heat fluxes, as well as differences in ocean basin geometry and current systems. These complexities support a pattern of oceanic heat transport that is not strictly from lower to high latitudes. Moreover, it is not stationary and we are only beginning to unravel its variability. '''CMEMS KEY FINDINGS''' The mean transports estimated by the ensemble global reanalysis are comparable to estimates based on observations; the uncertainties on these integrated quantities are still large in all the available products. At Drake Passage, the multi-product approach (product no. 2.4.1) is larger than the value (130 Sv) of Lumpkin and Speer (2007), but smaller than the new observational based results of Colin de Verdière and Ollitrault, (2016) (175 Sv) and Donohue (2017) (173.3 Sv). Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00247

Annual time series of salmon escapement (2009-2014): • Time series of atlantic salmon escapement • Location and Long Term Average (LTA) of atlantic salmon escapement per Management Unit, that could be a river, basin district, a region or a whole country.

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

Map at 1 degree resolution of 50-year linear trend in sea water temperature at 3 levels: surface, 500m, bottom.

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). ITS-90 water temperature and Water body salinity variables have been also included (as-is) to complete the Eutrophication and Acidity data. If you use these variables for calculations, please refer to SeaDataNet for having the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets . This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the Mediterranean Sea with 67271 CDI records (60876 Vertical profiles and 6395 Time series). Vertical profiles temporal range is from 1911-08-17 to 2017-10-25. Time series temporal range is from 1974-06-04 to 2015-12-22. Data were aggregated and quality controlled by 'Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)' from Greece. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/. Detailed documentation is available at: https://doi.org/10.6092/ec8207ef-ed81-4ee5-bf48-e26ff16bf02e The aggregated dataset can be downloaded as ODV spreadsheet, which is composed of metadata header followed by tab separated values. This worksheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ). The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search

Data from a number of different sources have been integrated to provide new perspectives on fishing activities. Vessel Monitoring Systems (VMS) record and transmit the position and speed of fishing vessels at intervals of two hours or less. Fishing time can be calculated from the VMS data and combining this parameter with vessel logbook data, maps of fishing effort and intensity at different spatial and temporal scales can be calculated. The statistical software package “R” is used to extract the required information then re-interrogated to produce maps of fishing effort or intensity per month and year. The use of Automatic Identification System (AIS) data was not considered as combining AIS data with fisheries logbook data would pose issues namely; the ability of the AIS system to be switched off, only mandatory on vessels > 15 meters in length, cost involved to purchase data, and confidentiality.

Map at 1 degree resolution of 10 year linear trend in sea water temperature at 3 levels: surface, 500m , bottom

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.