Moving 6-year analysis of Water body phosphate in the NorthEast Atlantic for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span from 1950/1955 until 2016/2021. Observation data span from 1950 to 2021. Depth levels (IODE standard depths): [0.0, 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 75.0, 100.0, 125.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1750.0, 2000.0]. Data sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Descrption of DIVAnd analysis: the computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.4, using GEBCO 30 sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps is 0.1 degrees. Horizontal correlation length varies from 250km in open sea regions to 50km at the coast. Vertical correlation length is defined as twice the vertical resolution. Signal-to-noise ratio was fixed to 1 for vertical profiles and 0.1 for time series to account for the redundancy in the time series observations. A logarithmic transformation (DIVAnd.Anam.loglin) was applied to the data prior to the analysis to avoid unrealistic negative values. Background field: a vertically-filtered profile of the seasonal data mean value (including all years) is substracted from the data. Detrending of data: no, advection constraint applied: no. Units: umol/l.

This dataset represents meat weight and shell height data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey collected from June to mid-August. Wet meat weights were recorded to a tenth of a gram and shell heights are measured in millimeters. Meat weights and shell heights are sampled from a subset of scallops caught on survey and this detailed sampling is conducted from approximately half of the tows conducted. Each row in the dataset represents an individual scallop and contains information such as tow number, tow date, cruise name, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025). References Glass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p. Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p. Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Meat Weight and Shell Height Data 2011 to 2023. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/65d32794-2d81-4682-b0ea-8d8bbe907a58

This visualization product displays plastic bags density 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 fishing bottom trawl surveys. In cases where the wingspread and/or number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using this formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities have been calculated on each trawl and year using the following computation: Density of plastic bags (number of items per km²) = ∑Number of plastic bags related items / Swept area (km²) Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. The list of selected items for this product is attached to this metadata. Information on data processing and calculation is detailed in the attached methodology document. 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.

The Regional Deterministic Wave Prediction System (RDWPS) produces wave forecasts out to 48 hours in the future using the third generation spectral wave forecast model WaveWatch III® (WW3). The model is forced by the 10 meters winds from the High Resolution Deterministic Prediction System (HRDPS). Over the Great Lakes, an ice forecast from the Water Cycle Prediction System of the Great Lakes (WCPS) is used by the model to attenuate or suppress wave growth in areas covered by 25% to 75% and more than 75% ice, respectively. Over the ocean, an ice forecast from the Regional Ice Ocean Prediction System (RIOPS) is used: in the Northeast Pacific, waves propagate freely for ice concentrations below 50%, above this threshold there is no propagation; in the Northwest Atlantic the same logic is used as in the Great Lakes. Forecast elements include significant wave height, peak period, partitioned parameters and others. This system includes several domains: Lake Superior, Lake Huron-Michigan, Lake Erie, Lake Ontario, Atlantic North-West and Pacific North-East.

Arctic Ecologically and Biologically Significant Areas (EBSAs) and Arctic Marine Areas of Heightened Ecological and Cultural Significance as identified in the Arctic Marine Shipping Assessment (AMSA) IIC report. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 1</a> - Page 16 - Box Figure 1.1

Trends in abundance of plankton Focal Ecosystem Components across each Arctic Marine Area. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - Chapter 4 - Page 178 - Figure 4.2

A novel, bay – scale (i.e. tens of km) survey method was employed to examine algal populations on the southwestern shore of Cape Breton, Canada, for the purposes of potential economic exploitation. Since traditional remote sensing methods were unlikely to be successful in these waters, underwater video and acoustic methods were applied. A transponder positioned towfish housing video camera and sidescan sonar was hauled along predetermined transects perpendicular to shore to provide information on bottom type and algal cover. The towfish data were used to ground truth echosounder data (bottom type and macrophyte canopy height) collected along 5, 10 and 20 m depth contours. The survey area was divided into six zones comprising a range of exposure, depth and bottom types. Destructive quadrat samples were collected at each depth plus shore stations to provide biomass estimates. Over thirty five taxa were enumerated, indicating depths and zones of common occurrence. Ascophyllum was abundant at some of the shore stations. The genera Chondrus, Cystoclonium, Desmarestia, Fucus, Phyllophora, Polysiphonia, and Saccharina were common at 5 m. Desmarestia and Saccharina dominated at 10 m with wet weights sometimes over 1 kg·m-2. Agarum dominated at 20 m. The towfish / echosounder grid sampling system was relatively coarse in order to cover the 140 km2 survey area within 12 days. As a result, the survey did not produce spatially detailed information. However, adequate information was gathered to describe the general characteristics of bottom type and algal cover by zone and for focusing further exploration--Abstract, p. vi. Cite this data as: Vandermeulen H. Data of: A Novel Video and Acoustic Survey of the Seaweeds of Isle Madame. Published: August 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ebdd8f91-9131-45f0-8aec-aba9f65e3fae

The Coastal Environmental Baseline Program is a multi-year Fisheries and Oceans Canada initiative designed to work with Indigenous and local communities and other key parties to collect coastal environmental data at six pilot sites across Canada (Port of Vancouver, Port of Prince Rupert, Lower St. Lawrence Estuary, Port of Saint John, Placentia Bay, and Iqaluit). The goal of the Program is to gather local information in these areas in effort to build a better understanding of marine ecological conditions. The Maritimes region has developed a habitat classification program to align with the oceanographic interests and data needs of local communities and stakeholders, with the goal of sharing this information via open data. In 2020, a habitat survey in the lower Musquash Marine Protected Area (MPA) was undertaken to further develop this project, using an Autonomous Underwater Vehicle (AUV) equipped with high-frequency (450 kHz) side scan sonar to build a habitat map of the MPA. This dataset includes mosaicked series of sonar images (raw & position-corrected versions), covering roughly 6 km2 of marine and intertidal areas in the Musquash MPA. Doppler Velocity logs and mission-specific files for each survey are also included, along with detailed methodological documentation. These data were generated from 17 separate survey missions that were completed in August, September and October 2020.

This visualization product displays beaches locations where non-MSFD monitoring surveys, research & cleaning operations have been applied to collate data on macrolitter (> 2.5 cm). Reference lists associated with these protocols have been indicated with different colors in the map. 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; - 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. 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). 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.

Commercial fishery impact on zoobenthos of the Barents Sea. Figure A) Intensity and duration of fishery efforts in standard commercial fishery areas in the Barents Sea. The darker the area the longer the fishery has been in operation. Figure B) Level of decline in macrobenthic biomass between 1926-1932 and 1968-1970 calculated as 1-b1968/b1930. The largest biomass decreases correspond to the darker colour, whereas lighter colour refers to no change (Denisenko 2013). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/benthos" target="_blank">Chapter 3</a> - Page 97 - Figure 3.3.4