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  • '''DEFINITION''' Ocean heat content (OHC) is defined here as the deviation from a reference period (1993-2014) and is closely proportional to the average temperature change from z1 = 0 m to z2 = 700 m depth: OHC=∫_(z_1)^(z_2)ρ_0 c_p (T_yr-T_clim )dz [1] with a reference density of = 1030 kgm-3 and a specific heat capacity of cp = 3980 J kg-1 °C-1 (e.g. von Schuckmann et al., 2009). Time series of annual mean values area averaged ocean heat content is provided for the Mediterranean Sea (30°N, 46°N; 6°W, 36°E) and is evaluated for topography deeper than 300m. '''CONTEXT''' Knowing how much and where heat energy is stored and released in the ocean is essential for understanding the contemporary Earth system state, variability and change, as the oceans shape our perspectives for the future. The quality evaluation of MEDSEA_OMI_OHC_area_averaged_anomalies is based on the “multi-product” approach as introduced in the second issue of the Ocean State Report (von Schuckmann et al., 2018), and following the MyOcean’s experience (Masina et al., 2017). Six global products and a regional (Mediterranean Sea) product have been used to build an ensemble mean, and its associated ensemble spread. The reference products are: • The Mediterranean Sea Reanalysis at 1/24 degree horizontal resolution (MEDSEA_MULTIYEAR_PHY_006_004, DOI: https://doi.org/10.25423/CMCC/MEDSEA_MULTIYEAR_PHY_006_004_E3R1, Escudier et al., 2020) • Four global reanalyses at 1/4 degree horizontal resolution (GLOBAL_MULTIYEAR_PHY_ENS_001_031): GLORYS, C-GLORS, ORAS5, FOAM • Two observation based products: CORA (INSITU_GLO_PHY_TS_OA_MY_013_052) and ARMOR3D (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012). Details on the products are delivered in the PUM and QUID of this OMI. '''CMEMS KEY FINDINGS''' The ensemble mean ocean heat content anomaly time series over the Mediterranean Sea shows a continuous increase in the period 1993-2022 at rate of 1.38±0.08 W/m2 in the upper 700m. After 2005 the rate has clearly increased with respect the previous decade, in agreement with Iona et al. (2018). '''DOI (product):''' https://doi.org/10.48670/moi-00261

  • This visualization product displays the marine litter material categories percentage per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys. Unlike other EMODnet seafloor litter products, all trawls surveyed since 2007 are included in this map even if the wingspread and/or the distance are/is unknown. Only surveys with an unknown number of items were excluded from this product. Harmonization of the material categories between ICES and MEDITS lists was performed and the following calculation was applied: Material % = (∑Number of items of each material category*100)/(∑Number of items of all material categories) More information on data processing and calculation are detailed in the attached document. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area.

  • As part of the marine water quality monitoring of the “Pertuis” and the “baie de l’Aiguillon” (France), commissioned by the OFB and carried out by setec énergie environnement, three monitoring stations were installed. Two of them were set up at the mouths of the Charente and Seudre rivers on February 6 and 27, 2019, respectively, while a third was deployed in the Bay of Aiguillon on March 24, 2021. The dataset presented here concerns the station installed in the Charente estuary. Measurements are organized into .csv files, with one file per year. Data is collected using a SAMBAT multiparameter probe, which records the following parameters: - Temperature (-5 to 35 °C) - Conductivity (0 to 10 mS/cm) - Pressure (0 to 10 m) - Turbidity (0 to 300 NTU) - Dissolved Oxygen (0 to 20 mg/L & 0 to 200 %) - Fluorescence (0 to 50 µg/l) - PH (0/14)

  • This visualization product displays the size of litter in percent per net per year from specific protocols different from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. To calculate percentages for each size, formula applied is: Size (%) = (∑number of particles of each size)*100 / (∑number of particles of all size) When the number of micro-litters was not filled or was equal to zero, it was not possible to calculate the percentage. Standard vocabularies for micro-litter size classes are taken from Seadatanet's H03 library (https://vocab.seadatanet.org/v_bodc_vocab_v2/search.asp?lib=H03 ). Different protocols with different degrees of precision were used to classify the sampled micro-litters. Consequently, on the map, the distribution of micro-litter in the size classes depends on the protocol applied during the survey. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area.

  • As part of the marine water quality monitoring of the “Pertuis” and the “baie de l’Aiguillon” (France), commissioned by the OFB and carried out by setec énergie environnement, three monitoring stations were installed. Two of them were set up at the mouths of the Charente and Seudre rivers on February 6 and 27, 2019, respectively, while a third was deployed in the Bay of Aiguillon on March 24, 2021. The dataset presented here concerns the station installed in the Bay of Aiguillon. Measurements are organized into .csv files, with one file per year. Data is collected using a WiMO multiparameter probe, which records the following parameters: •    Temperature (-2 to 35 °C) •    Conductivity (0 to 100 mS/cm) •    Pressure (0 to 30 m) •    Turbidity (0 to 4000 NTU) •    Dissolved Oxygen (0 to 23 mg/L & 0 to 250 %) •    Fluorescence (0 to 500 ppb)  

  • This visualization product displays the spatial distribution of the sampling effort (based on the start position of the sampling tow) over the six-years' period 2017-2022 from other specific protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter samplings carried out according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. The spatial distribution was then determined by calculating the number of times each cell was sampled during the period 2017-2022, only taking into account the start position of the tows. The corresponding total distance (kms) sampled in each cell is also provided in the attribute table. Information on data processing and calculation are detailed in the attached methodology document. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area. This work is based on the work presented in the following scientific article: O. Gerigny, M. Brun, M.C. Fabri, C. Tomasino, M. Le Moigne, A. Jadaud, F. Galgani, Seafloor litter from the continental shelf and canyons in French Mediterranean Water: Distribution, typologies and trends, Marine Pollution Bulletin, Volume 146, 2019, Pages 653-666, ISSN 0025-326X, https://doi.org/10.1016/j.marpolbul.2019.07.030.

  • EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification, contaminants and litter. The chosen parameters are relevant for the Marine Strategy Framework Directive (MSFD), in particular for descriptors 5, 8, 9 and 10. The dataset contains standardized, harmonized and validated data collections from beach litter (monitoring and other sources). Datasets concerning beach and seafloor litter data are loaded in a central database after a semi-automated validation phase. Once loaded, a data assessment is performed in order to check data consistency and potential errors are corrected thanks to a feedback loop with data originators. For beach litter, the harmonized datasets contain all unrestricted EMODnet Chemistry data on beach litter, including monitoring data, data from cleaning surveys and data from research. A relevant part of the monitoring data has been considered for assessment purposes by the European institutions and therefore is tagged as MSFD_monitoring. EMODnet beach litter data and databases are hosted and maintained by 'Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Division of Oceanography (OGS/NODC)' from Italy. Data are formatted following Guidelines and forms for gathering marine litter data, which can be found at: https://doi.org/10.6092/15c0d34c-a01a-4091-91ac-7c4f561ab508 The updated vocabularies of admitted values are available at: https://nodc.ogs.it/marinelitter/vocab The European harmonized dataset is provided as csv format in two files, one containing the survey data and one containing the survey metadata. The dataset is available through direct download or through ERDDAP.

  • Worldwide, shellfish aquaculture and fisheries in coastal ecosystems represent crucial activities for human feeding. But these biological productions are under the pressure of climate variability and global change. Anticipating the biological processes affected by climate hazards remains a vital objective for species conservation strategies and human activities that rely on. Within marine species, filter feeders like oysters are real key species in coastal ecosystems due to their economic and societal value (fishing and aquaculture) but also due to their ecological importance. Indeed oysters populations in good health play the role of ecosystem engineers that can give many ecosystem services at several scales: building reef habitats that contribute to biodiversity, benthic-pelagic coupling and phytoplankton bloom control through water filtration, living shorelines against coastal erosion… The Pacific oyster, Crassostrea gigas (Thunberg, 1793), which is currently widespread worldwide, was introduced into the Atlantic European coasts at the end of the 19th century for shellfish culture purposes and becomes the main marine species farmed in France (around 100 000 tons) despite severe mortalities crisis. But in the same time and because of warming, natural oysters beds has spread significantly along the French coast and are supposed to have reach approximately 500 000 tons. In that context, Pacific oyster populations (natural and cultivated) in France are the subjects of many scientific projects. Among them, a specific long-term biological monitoring focuses on the reproduction of these populations at a national scale: the VELYGER national program. With more than 8 years of weekly data at many stations in France, this field-monitoring program offers a valuable dataset for studying processes underpinning reproduction cycle of this key-species in relation to environmental parameters, water quality and climate change.   Database content: Larval concentration (number of individuals per 1.5 m3) monitored, since 2008, at several stations in six bays of the French coast (from south to north): Thau Lagoon and bays of Arcachon, Marennes Oléron, Bourgneuf, Vilaine and Brest (see map below).   Methods used to monitor larval concentration: An important volume of seawater (1.5 m3) is pumped twice a week throughout the spawning season (june-september), at one meter below the surface at high tide (+/- 2h) in several sites within each VELYGER ecosystem. Water is filtered trough plankton net fitted with 40 µm mesh. After a proper rinsing of the net, the retained material is transferred into a polyethylene bottle (1 liter) and fixed with alcohol. At laboratory, sample is then gently filtered and rinse again and transferred into eprouvette. Two sub-samples of 1 mL are then taken using a pipette and examined on a graticule slide for microscope. The microscopic examination is made with a conventional binocular optical microscope with micrometer stage at a magnification of 10 X (or above). During the counting, a special care is necessary as larvae of other bivalves are also collected and confusion is possible. Larvae of C. gigas are also classified into four stage of development: - Stage I = D-shaped straight hinge larvae (shell length <105 µm) - Stage II = Early umbo evolved larvae (shell length between 105 and 150 µm) - Stage III = Medium umbo larvae (shell length between 150 and 235 µm) - Stage IV*= Large umbo eyed pediveliger larvae (shell length > 235 µm) * Larvae that are very closed to settle are sometimes identified into a separated 5th stage, but generally this stage is included in stage IV.   Illustrations: Location of the different Velyger sites along the French coast. From south to north: Thau Lagoon and bays of Arcachon, Marennes Oléron, Bourgneuf, Vilaine and Brest.   Legend: Pacific Oyster Larvae (left side) and Natural oyster bed (right side). Photos : © S. Pouvreau/Ifremer

  • The SOMLIT-SOGIR time-series data characterize the hydrology of the Gironde Estuary ecosystem, located in the South-western France and flowing into the Bay of Biscay. Monthly-like measurements have been undertaken since 1997 by the OASU and EPOC teams (Univ. Bordeaux/CNRS). The SOMLIT-SOGIR time series is a part of the French monitoring network SOMLIT (https://www.somlit.fr/), labelled by the CNRS as a national Earth Science Observatory (Service National d’Observation : SNO). It aims to detect the long-term evolution of monitored ecosystems including both natural and anthropogenic forcings. Implemented at three sites (PK 30: 45.06833°N, 0.63833°W; PK 52: 45.24667°N, 0.725°W; PK 86:  45.5167°N, 0.95°W), the SOMLIT-SOGIR time series is among the oldest long-term coastal observation time series of the French Research Infrastructure dedicated to coastal ocean observations (RI ILICO, https://www.ir-ilico.fr). SOMLIT-SOGIR samples are collected at 1m below the water surface and 1m above the floor, at high and low tide, during slack water. Samples collected are analysed for 15 core parameters: water temperature and salinity, dissolved oxygen, pH, ammonia, nitrate, nitrite, phosphate, silicic acid, suspended particulate matter, particulate organic carbone, particulate nitrogen, chlorophyll a, delta15N and delta13C. CTD-PAR-profile is also performed at site PK86 during high tide. The SOMLIT network quality management system is in line with the ISO/IEC 17025:2017 standard: “General requirements for the competence of testing and calibration laboratories”. Further information on standard operating procedures for sample collection and data acquisition are available at: https://www.somlit.fr/parametres-et-protocoles. For more information on the quality flagging scheme: https://www.somlit.fr/codes-qualite/.

  • The Delmoges project aims to generate new ecological and fisheries knowledge to reduce dolphin bycatch in the Bay of Biscay (GoG). This dataset presents maps produced by a hierarchical model of the seasonal and interannual distribution of dolphins' main prey, small pelagic fish. The model integrates 3 types of data: presence-absence and biomass of fish from scientific campaigns and presence of fish from fishing data. For the first time, the model has provided a quantitative description of the seasonal spatial dynamics of sardines and associated fisheries. The main sardine distribution areas were coastal, from the mouth of the Gironde to south-west Brittany. On average, sardines were distributed over a wider area in small aggregations in spring. They seemed to concentrate in their main distribution areas in summer, and to disperse offshore in autumn, but to a lesser extent than in spring. Fishing was concentrated in the sardine's main coastal distribution areas, and was more intense in summer, then autumn, and less intense in spring.