This dataset contains the modelled and observed data used in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). An application of the Finite Volume Community Ocean Model (FVCOM v4.1) was run from May 24 to June 27, 2019 in the Discovery Islands region of British Columbia, Canada. Observed temperature and salinity profiles available in this area during this time period are included in the dataset, along with the modelled values at the same times and locations.

The shallow substrate bottom type model was created to support near shore habitat modelling. Data sources include both available observations of bottom type and environmental predictor layers including oceanographic layers, fetch, and bathymetry and its derivatives. Using weighted random forest classification from the ranger R package, the relationship between observed bottom type and predictor layers can be determined, allowing bottom type to be classified across the study areas. The predicted raster files are classified as follows: 1) Rock, 2) Mixed, 3) Sand, 4) Mud The categorical substrate model domains are restricted to the extent of the input bathymetry layers (see data sources) which is 5 km from the 50 m depth contour.

This product displays for Hexachlorobenzene, positions with values counts that have been measured per matrix for each year and are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for every available year.

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 2023 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 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 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, 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); - 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 does not necessarily mean that they do not 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 2023 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 includes fifteen GeoTIFFs of Sea Surface Temperature (SST) organized into five distinct marine regions along Canada's Pacific coast, derived from Sentinel 3 satellite data for the period of April-September 2017. For each region, three GeoTIFFs are provided which represent the mean, maximum, and standard deviation values of SST (degrees Celcius). Jupyter notebooks with Python code used for data downloading and processing are also included for reference. The primary objective of this dataset is to provide detailed, regional spatial information on SST for key areas of Canada's Pacific coast, including the nearshore environment. The data can be used for various applications including species distribution modelling. This dataset is intended to fill the knowledge gap by providing high-resolution, spatially explicit regional SST data for Canada's Pacific coast. Existing datasets may not provide sufficient spatial resolution or may not include comprehensive statistical measures (mean, max, standard deviation) of SST for these specific areas. The dataset is structured by region. For each of the five regions, a set of three related GeoTIFFs is provided, representing the mean, max, and standard deviation of SST. Within each regional set, the three layers share the same spatial reference system, resolution, and extent, making them suitable for direct use in analytical stacks (e.g., for species distribution models). The Sentinel-3 satellites, part of the European Union's Copernicus Programme, are equipped with the Sea and Land Surface Temperature Radiometer (SLSTR) which measures SST among other parameters. The SST data products in this dataset are derived from Sentinel-3 satellite data. The intent of the data is to represent the marine environment and so a mask that excludes land was applied during data download and extraction. The SST data products have been resampled using a bilinear interpolation from their native resolution to a 20 m resolution to provide more detailed spatial information.

The locations of coastal British Columbia marine navigation hazards. The Coastal BC datasets are circa 2004 and legacy in nature. Caution should be exercised when using this data, as it may not be accurate or complete. There are currently no plans to update.

This layer details Important Areas (IAs) relevant to key invertebrate species (which are not corals or sponges) in the Strait of Georgia (SOG) ecoregion. This data was mapped to inform the selection of marine Ecologically and Biologically Significant Areas (EBSA). Experts have indicated that these areas are relevant based upon their high ranking in one or more of three criteria (Uniqueness, Aggregation, and Fitness Consequences). The distribution of IAs within ecoregions is used in the designation of EBSAs. Canada’s Oceans Act provides the legislative framework for an integrated ecosystem approach to management in Canadian oceans, particularly in areas considered ecologically or biologically significant. DFO has developed general guidance for the identification of ecologically or biologically significant areas. The criteria for defining such areas include uniqueness, aggregation, fitness consequences, resilience, and naturalness. This science advisory process identifies proposed EBSAs in Canadian Pacific marine waters, specifically in the Strait of Georgia (SOG), along the west coast of Vancouver Island (WCVI, southern shelf ecoregion), and in the Pacific North Coast Integrated Management Area (PNCIMA, northern shelf ecoregion). Initial assessment of IA's in PNCIMA was carried out in September 2004 to March 2005 with spatial data collection coordinated by Cathryn Clarke. Subsequent efforts in WCVI and SOG were conducted in 2009, and may have used different scientific advisors, temporal extents, data, and assessment methods. WCVI and SOG IA assessment in some cases revisits data collected for PNCIMA, but should be treated as a separate effort. Other datasets in this series detail IAs for birds, cetaceans, coral and sponges, fish, geographic features, and other vertebrates. Though data collection is considered complete, the emergence of significant new data may merit revisiting of IA's on a case by case basis.

This dataset was compiled as part of a multiyear effort lead by Fisheries and Oceans Canada (DFO) to support sustainable aquaculture regulation in the Coast of Bays, an area of the south coast of Newfoundland. It is the first of a series aiming to provide an oceanographic knowledge baseline of the Coast of Bays. This dataset consists of GIS products and analyses summarized in a spreadsheet. The GIS data include vector shapefiles and raster TIFF images, providing information on the area of interest physical dimensions (e.g. bays area, volume, perimeter, length and width) and other physical characteristics (e.g. tidal volume and freshwater input). A full description of the data and of its use in the context of the motivating project can be found in http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2017/2017_076-eng.html. Analyses from this dataset were presented during a Canadian Science Advisory Secretariat (CSAS) meeting which took place in St John’s in March 2015 (http://www.dfo-mpo.gc.ca/csas-sccs/schedule-horraire/2015/03_25-26b-eng.html) and from which a Science Advisory Report (http://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2016/2016_039-eng.html) and Proceedings (http://www.dfo-mpo.gc.ca/csas-sccs/Publications/Pro-Cr/2017/2017_043-eng.html) were published.

This product displays for Lead, positions with values counts that have been measured per matrix and are present in EMODnet regional contaminants aggregated datasets, v2022. The product displays positions for all available years.

This dataset contains the outputs for Bute Inlet from two simulations shown in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). The Finite Volume Community Ocean Model (FVCOM v4.1) was run with two different sets of initial conditions for the Discovery Islands region of British Columbia, Canada, from May 24 to June 27, 2019. The "Baseline" simulation used observed initial conditions, while the "Sensitivity" simulation removed the observed cold subsurface water mass from the initial profiles. Here in this dataset, we provide 29-day averages of the following variables in a transect along Bute Inlet: potential temperature, density, along-inlet velocity, and Brunt-Väisälä frequency (N^2). The averaging properly removes the tidal effects.