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 potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Norwegian Sea, Barents Sea, Greenland Sea and Icelandic Waters. Data were harmonised and validated by the 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)' in Norway. The dataset contains water and sediment profiles. The temporal coverage is 1974–2011 for water measurements and 1974–2021 for sediment measurements. Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/. The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).

This gridded product visualizes 1960 - 2014 water body phosphate concentration (umol/l) in the North Sea domain, for each season (winter: December – February; spring: March – May; summer: June – August; autumn: September – November). It is produced as a Diva 4D analysis, version 4.6.9: a reference field of all seasonal data between 1960-2014 was used; results were logit transformed to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. Every step of the time dimension corresponds to a 10-year moving average for each season. The depth dimension allows visualizing the gridded field at various depths.

The Circumpolar Biodiversity Monitoring Program, a cornerstone programme of the Conservation of Arctic Flora and Fauna (CAFF), Arctic Council working Group is an international network of scientists, government agencies, Indigenous organizations and conservation groups working together to harmonize and integrate efforts to monitor the Arctic's living resources.CBMP experts are developing four coordinated and integrated Arctic Biodiversity Monitoring Plans to help guide circumpolar monitoring efforts. Results will be channeled into effective conservation, mitigation and adaptation policies supporting the Arctic. These plans represent the Arctic's major ecosystems(Marine, Freshwater, Coastal, Terrestrial).

<p>Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales.-nbsp;</p>

We defined the interfaces between the air/snow, snow/ice, and ice/ocean and calculated the ocean heat flux for two SIMBA recordings (SIMBA2015a and SIMBA_2015f) of repeated temperature profiles at 6h interval and 2cm vertical resolution, during N-ICE 2015 experiment floe1. The snow/ice interface is derived from the sharp contrast in the diffusivity proxy values between both media. The snow/ice interface does not change except for slush formation associated with flooding events. The air/snow interface is calculated using simultaneous information from the vertical gradient of the temperature and the standard deviation over 24, 48, and 72 h period. Snow accumulation of more than 10 centimeters happened at different time for the 2 SIMBA. The ice/ocean interface is estimated from temperature profiles alone since the winter sea-ice remains colder than the ocean. The ocean just below the ice is at or just above the freezing temperature (estimated from a near surface conductivity-temperature-depth (CTD) sensor see Koenig et al. [2016]). The method detects (1) the first sensor, downward of the snow/ice interface, with a temperature above the ocean freezing temperature and (2) the last sensor in the ice with a temperature below the mean ocean temperature by at least twice the ocean temperature standard deviation in that profile. The ice/ocean interface is then defined as half way between the last sensor in the ice and the first sensor in the ocean. Note it take 3-4 days for the deployment hole to refreeze. Then the ice thickness remains constant up to 20 February when floe1 breaks. Simba_2015f stops working and SIMBA_2015a features basal melt events corresponding to temperature changes in the ocean. The consistency of the 3 interfaces estimate is validated with the thermal diffusivity proxy and the vertical and temporal derivatives of temperature. The ocean heat flux is derived from the latent heat flux which is directly proportional to the change in time of the ice/ocean interface depth and the conductive heat flux in the lower portion of the ice estimated 6 cm above the ice/ocean interface. The ocean heat flux values for SIMBA_2015a and SIMBA2015f range from -50 to 350 W/m2, and -50 to 150 W/m2 respectively, while the basal melt events associated with ocean temperature increase stand out in SIMBA_2015a.   The SIMBA data are available through the Norwegian Polar Institute’s data center (https://data.npolar.no/dataset/6ed9a8ca-95b0-43be-bedf-8176bf56da80) and the method of interface detection is thoroughly described in Provost et al. (2017). Note that all time series have been smoothed with a 36-h running mean.   Provost, C., N. Sennechael, J. Miguet, P. Itkin, A. Rosel, Z. Koenig, N. Villacieros-Robineau, and M. A. Granskog (2017), Observations of flooding and snow-ice formation in a thinner Arctic sea-ice regime during the N-ICE2015 campaign: Influence of basal ice melt and storms, J. Geophys. Res. Oceans, 122, 7115–7134, doi:10.1002/2016JC012011. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

<p>Original provider: Happywhale Dataset credits: Happywhale and contributors Abstract: Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales.-nbsp;</p>

IAOOS14, IAOOS15 and IAOOS25 were deployed from the Korean Icebreaker R/V Araon during cruises in the northern Chukchi Sea. IAOOS14 and IAOOS15 were deployed 300 m apart on the same floe on 12 August 2015 in the Makarov Basin (80.8°N;173°E) and they drifted together remaining always less than 6 km apart. IAOOS25 was deployed on 15 August 2017 south-west Mendeleev Ridge (77.7°N;180°E) and drifted westward to the continental slope of the East Siberian Sea. IAOOS14 and IAOOS25 stopped transmitting on 9 October 2015 and 19 November 2017 respectively, likely due to the loss of their profilers while crossing relatively shallow bathymetry. IAOOS15 dataset ends in 15 October 2015. Ocean profilers were PROVOR SPI (from French manufacturer NKE) equipped with a Seabird SBE41 CTD (Conductivity, Temperature, Depth) and a dissolved oxygen (DO) Aandera 4330 optode. The profilers were set to perform two upward profiles a day from 800 m (IAOOS 14), 300 m (IAOOS 15) and 420 m (IAOOS 25), upward starting at approximately 6 am and 6 pm. The present dataset is composed of CTD-DO data from IAOOS 14 and 15, and CTD data from IAOOS 25 in the Makarov Basin, corrected from salinity errors and interpolated vertically every 0.5 m. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

<p>Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales.-nbsp;</p>

This visualization product displays the total abundance of marine macro-litter (> 2.5cm) per beach, per 100m & to 1 survey aggregated over the period 2001 to 2020 from Marine Strategy Framework Directive (MSFD) monitoring surveys. 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 processing 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 MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Some categories & some litter types like organic litter, small fragments (paraffin and wax; items > 2.5cm) and pollutants have been removed. The list of selected items is attached to this metadata (total abundance list). This list was created using EU Marine Beach Litter Baselines and EU Threshold Value for Macro Litter on Coastlines from JRC (these two documents are attached to this metadata); - Normalization of survey lengths to 100m & 1 survey / year: in some cases, the survey length was not exactly 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 items (normalized by 100 m) = Number of litter per items x (100 / survey length) Then, this normalized number of items is summed to obtain the total normalized number of litter for each survey. Finally, a median is calculated over the entire period among all these total numbers of litter per 100m calculated for each survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. The size of each circle on this map increases with the calculated median number of marine litter per beach, per 100m & to 1 survey. The median litter abundance values displayed in the legend correspond to the 50 and 99 percentiles and the maximum value. More information is available in the attached documents. Warning: - the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area. - This map was created to give an idea of the distribution of beach litter between 2001 and 2021 in a synthetic manner. NOT ALL BEACHES MAY HAVE DATA FOR THE ENTIRE PERIOD, SO IT IS NOT POSSIBLE TO MAKE A COMPARISON BETWEEN BEACHES.

This dataset was compiled to describe the intertidal meiobenthic community of Kongsfjorden and to better understand the relationship between the horizontal and vertical distribution of meiofauna with a special focus on nematodes and environmental features