Web Map Service for Emodnet Chemistry

Donnees publiques de la Directive Cadre Strategie pour le Milieu Marin (DCSMM)

This visualization product displays the cigarette related items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations without UNEP-MARLIN data. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter 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 and reference lists used on a European scale. Preliminary processings were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Selection of plastic bags related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata); - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of plastic bags related items of the survey (normalized by 100 m) = Number of plastic bags related items of the survey x (100 / survey length) Then, this normalized number of plastic bags related items is summed to obtain the total normalized number of plastic bags related items for each survey. Finally, the median abundance of plastic bags related items for each beach and year is calculated from these normalized abundances of plastic bags related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account plastic bags related items from other sources data for all years. More information is available in the attached documents. 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.

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/.

Serveur wms public de l'Ifremer, Accès aux données du Sismer

A world deep displacement dataset comprising more than 1600 000 Argo floats deep displacements, has been produced from the global Argo float database (GDAC). ANDRO dataset was completed over the period 2000-2009, then was partially but yearly updated since 2010. ANDRO actual contents and format is described in the user guide, which must be carefully read before using ANDRO (ANDRO format is also described in Ollitrault M. et al (2013)). One important feature of ANDRO is that the pressures measured during float drifts at depth, and suitably averaged are preserved in ANDRO (see Figure 2). To reach this goal, it was necessary to reprocess most of the Argo raw data, because of the many different decoding versions (roughly 100) not always applied by the DACs to the displacement data because they were mainly interested in the p,t,S profiles. The result of our work was the production of comprehensive files, named DEP (for déplacements in French), containing all the possibly retrievable float data. For detailed information and status of the last released ANDRO product, please visit the dedicated Argo France web page: https://www.umr-lops.fr/SNO-Argo/Products/ANDRO-Argo-floats-displacements-Atlas

The general objective of the PEACETIME cruise is to study the fundamental processes and their interactions at the ocean-atmosphere interface, occurring after atmospheric deposition (especially Saharan dust) in the Mediterranean Sea, and how these processes impact the functioning of the pelagic ecosystem. During the proposed 33 days cruise in the western and central Mediterranean Sea in May 2017, we will study the impact of atmospheric deposition on the cycles of chemical elements, on marine biogeochemical processes and fluxes, on marine aerosols emission and how ongoing changes will impact the functioning of Mediterranean Sea communities in the future. The cruise is designed to explore a variety of oligotrophic regimes. Combining in situ observations both in the atmosphere and the ocean, and in situ and minicosm-based on-board process studies, the 40 embarking scientists from atmosphere and ocean sciences will characterize the chemical, biological and physical/optical properties of both the atmosphere and the sea-surface microlayer, mixed layer and deeper waters. The PEACETIME strategy (season and cruise track) associated to a combination of dust transport forecasting tools and near real-time satellite remote sensing is designed to maximize the probability to catch a Saharan dust deposition event in a stratified water column in order to follow the associated processes in-situ. This coordinated multidisciplinary effort will allow us to fill the current weaknesses/lacks in our knowledge of atmospheric deposition impact in the ocean and feedbacks to the atmosphere in such oligotrophic systems. As a key joint-project between MERMEX and CHARMEX : The PEACETIME project comes in the scope of the regional multidisciplinaryprogramme MISTRALS (Mediterranean Integrated STudies at Regional And Local Scales ), which aims at predicting the evolution of this region following strong expected changes in climate and human pressures. In this framework, the PEACETIME project constitutes a key joint project between the ChArMEx (the Chemistry-Aerosol Mediterranean Experiment) and MERMEx (Marine Ecosystems Response in the Mediterranean Experiment) initiatives, enabling to gather communities of atmospheric chemists and marine biogeochemists around the common question of assessing the impact of atmospheric deposition on the marine biogeochemical processes and air-sea exchanges.

Dataset summary Plankton and detritus are essential components of the Earth’s oceans influencing biogeochemical cycles and carbon sequestration. Climate change impacts their composition and marine ecosystems as a whole. To improve our understanding of these changes, standardized observation methods and integrated global datasets are needed to enhance the accuracy of ecological and climate models. Here, we present a global dataset for plankton and detritus obtained by two versions of the Underwater Vision Profiler 5 (UVP5). This release contains the images classified in 33 homogenized categories, as well as the metadata associated with them, reaching 3,114 profiles and ca. 8 million objects acquired between 2008-2018 at global scale. The geographical distribution of the dataset is unbalanced, with the Equatorial region (30° S - 30° N) being the most represented, followed by the high latitudes in the northern hemisphere and lastly the high latitudes in the Southern Hemisphere. Detritus is the most abundant category in terms of concentration (90%) and biovolume (95%), although its classification in different morphotypes is still not well established. Copepoda was the most abundant taxa within the plankton, with Trichodesmium colonies being the second most abundant. The two versions of UVP5 (SD and HD) have different imagers, resulting in a different effective size range to analyse plankton and detritus from the images (HD objects >600 µm, SD objects >1 mm) and morphological properties (grey levels, etc.) presenting similar patterns, although the ranges may differ. A large number of images of plankton and detritus will be collected in the future by the UVP5, and the public availability of this dataset will help it being utilized as a training set for machine learning and being improved by the scientific community. This will reduce uncertainty by classifying previously unclassified objects and expand the classification categories, ultimately enhancing biodiversity quantification. Data tables The data set is organised according to: - samples : Underwater Vision Profiler 5 profiles, taken at a given point in space and time. - objects : individual UVP images, taken at a given depth along the each profile, on which various morphological features were measured and that where then classified taxonomically in EcoTaxa. samples and objects have unique identifiers. The sample_id is used to link the different tables of the data set together. All files are Tab separated values, UTF8 encoded, gzip compressed. samples.tsv.gz - sample_id    <int>    unique sample identifier - sample_name    <text>    original sample identifier - project    <text>    EcoPart project title - lat, lon    <float>    location [decimal degrees] - datetime    <text>    date and time of start of profile [ISO 8601: YYYY-MM-DDTHH:MM:SSZ] - pixel_size    <float>    size of one pixel [mm] - uvp_model    <text>    version of the UVP: SD: standard definition, ZD: zoomed, HD: high definition samples_volume.tsv.gz Along a profile, the UVP takes many images, each of a fixed volume. The profiles are cut into 5 m depth bins in which the number of images taken is recorded and hence the imaged volume is known. This is necessary to compute concentrations. - sample_id    <int>    unique sample identifier - mid_depth_bin    <float>    middle of the depth bin (2.5 = from 0 to 5 m depth) [m] - water_volume_imaged    <float>    volume imaged = number of full images × unit volume [L] objects.tsv.gz - object_id    <int>     unique object identifier - object_name    <text>     original object identifier - sample_id    <int>     unique sample identifier - depth    <float>    depth at which the image was taken [m] - mid_depth_bin    <float>    corresponding depth bin [m]; to match with samples_volumes - taxon    <text>     original taxonomic name as in EcoTaxa; is not consistent across projects - lineage    <text>     taxonomic lineage corresponding to that name - classif_author    <text>     unique, anonymised identifier of the user who performed this classification - classif_datetime    <text>     date and time at which the classification was - group    <text>     broader taxonomic name, for which the identification is consistent over the whole dataset - group_lineage    <text>     taxonomic lineage corresponding to this broader group - area_mm2    <float>    measurements on the object, in real worl units (i.e. comparable across the whole dataset) … - major_mm    <float> - area    <float>    measurements on the objet, in [pixels] and therefore not directly comparable among the different UVP models and units - mean    <float> … - skeleton_area    <float> properties_per_bin.tsv.gz The information above allows to compute concentrations, biovolumes, and average grey level within a given depth bin. The code to do so is in `summarise_objects_properties.R`. - sample_id    <int>     unique sample identifier - depth_range    <text>     range of depth over which the concentration/biovolume are computed: (start,end], in [m] where `(` means not including, `]` means including - group    <text>     broad taxonomic group - concentration    <float>    concentration [ind/L] - biovolume    <float>    biovolume [mm3/L] - avg_grey    <float>    average grey level of particles [no unit; 0 is black, 255 is white] ODV_biovolumes.txt, ODV_concentrations.txt, ODV_grey_levels.txt This is the same information as above, formatted in a way that Ocean Data View https://odv.awi.de can read. In ODV, go to Import > ODV Spreadsheet and accept all default choices. Images The images are provided in a separate, much larger, zip file. They are stored with the format `sample_id/object_id.jpg`, where `sample_id` and `object_id` are the integer identifiers used in the data tables above.

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 Greater North Sea and Celtic Seas. Data were aggregated and quality controlled by 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' in Denmark. 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 Southern Ocean plays a fundamental role in regulating the global climate. This ocean also contains a rich and highly productive ecosystem, potentially vulnerable to climate change. Very large national and international efforts are directed towards the modeling of physical oceanographic processes to predict the response of the Southern Ocean to global climate change and the role played by the large-scale ocean climate processes. However, these modeling efforts are greatly limited by the lack of in situ measurements, especially at high latitudes and during winter months. The standard data that are needed to study ocean circulation are vertical profiles of temperature and salinity, from which we can deduce the density of seawater. These are collected with CTD (Conductivity-Temperature-Depth) sensors that are usually deployed on research vessels or, more recently, on autonomous Argo profilers. The use of conventional research vessels to collect these data is very expensive, and does not guarantee access to areas where sea ice is found at the surface of the ocean during the winter months. A recent alternative is the use of autonomous Argo floats. However, this technology is not easy to use in glaciated areas. In this context, the collection of hydrographic profiles from CTDs mounted on marine mammals is very advantageous. The choice of species, gender or age can be done to selectively obtain data in particularly under-sampled areas such as under the sea ice or on continental shelves. Among marine mammals, elephant seals are particularly interesting. Indeed, they have the particularity to continuously dive to great depths (590 ± 200 m, with maxima around 2000 m) for long durations (average length of a dive 25 ± 15 min, maximum 80 min). A Conductivity-Temperature-Depth Satellite Relay Data Logger (CTD-SRDLs) has been developed in the early 2000s to sample temperature and salinity vertical profiles during marine mammal dives (Boehme et al. 2009, Fedak 2013). The CTD-SRDL is attached to the seal on land, then it records hydrographic profiles during its foraging trips, sending the data by satellite ARGOS whenever the seal goes back to the surface.While the principle intent of seal instrumentation was to improve understanding of seal foraging strategies (Biuw et al., 2007), it has also provided as a by-product a viable and cost-effective method of sampling hydrographic properties in many regions of the Southern Ocean (Charrassin et al., 2008; Roquet et al., 2013).