The Canadian Hydrographic Service (CHS) High Water Mark Lines provide alongshore and across-shore geomorphological and biological attributes of the high water mark shoreline. The lines are used in the CHS nautical charts to represent the level reached by sea water at high tide.

A towfish containing sidescan and video hardware was used to map eelgrass in two shallow northern New Brunswick estuaries. The sidescan and video data were useful in documenting suspected impacts of oyster aquaculture gear and eutrophication on eelgrass. With one boat and a crew of three, the mapping was accomplished at a rate of almost 10 km2 per day. That rate far exceeds what could be accomplished by a SCUBA based survey with the same crew. Moreover, the towfish survey applied with a complementary echosounder survey is potentially a more cost effective mapping method than satellite based remote sensing. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Richibucto 2007. Published: October 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ca7af8ba-8810-4de5-aa91-473613b0b38d

The Oceans Act (1997) commits Canada to maintaining biological diversity and productivity in the marine environment. A key component of this is to identify areas that are considered ecologically or biologically significant. Fisheries and Oceans Canada (DFO) Science has developed guidance on the identification of Ecologically or Biologically Significant Areas (EBSAs) (DFO 2004) and has endorsed the scientific criteria of the Convention on Biological Diversity (CBD) for identifying ecologically or biologically significant marine areas as defined in Annex I of Decision IX/20 of its 9th Conference of Parties. These criteria were applied to the Newfoundland and Labrador (NL) Shelves Bioregion in two separate data-driven processes. The first process focused on the area north of the Placentia Bay-Grand Banks (PBGB) Large Ocean Management Area (LOMA) (DFO 2013). The second process focused on the PBGB area (DFO 2019), where EBSAs had previously been identified using a more Delphic approach (Templeman 2007). In both cases, an EBSA Steering Committee, comprised of experts in oceanography, ecosystem structure and function, taxa-specific life histories and Geographic Information Systems (GIS) guided the process by advising or aiding in the identification, collection, processing and analysis of data layers, as well as participating in the final selection of candidate EBSAs (Wells et al. 2017, Ollerhead et al. 2017, Wells et al. 2019). All information was compiled in a GIS and a hierarchical approach was used to review individual data layers and groupings of data layers. Peer review meetings were held for both processes, during which candidate EBSAs were reviewed and the final EBSAs were agreed upon and delineated. In the northern study area, a total of fifteen EBSAs were identified and described; three of these areas are primarily coastal areas; seven are in offshore areas; four EBSAs straddle coastal and offshore areas; and one is a transitory EBSA that follows the southern extent of pack ice. In the PBGB study area, fourteen EBSAs were identified in two different categories: seven based on coastal data and seven based on offshore data. In comparing the new PBGB EBSAs to those identified in 2007, nine of them overlap spatially and are based on similar features; however, there were some variations in the boundaries. Two of the EBSAs that were identified in 2007 were no longer considered EBSAs in 2017, but portions of both of these areas were captured in part by other EBSAs. Five new EBSAs were identified in areas not previously considered. References: DFO, 2004. Identification of Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Ecosystem Status Rep. 2004/006. DFO. 2013. Identification of additional Ecologically and Biologically Significant Areas (EBSAs) within the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2013/048. DFO. 2019. Re-evaluation of the Placentia Bay-Grand Banks Area to Identify Ecologically and Biologically Significant Areas . DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2019/040. Ollerhead, L.M.N., Gullage, M., Trip, N., and Wells, N. 2017. Development of Spatially Referenced Data Layers for Use in the Identification and Delineation of Candidate Ecologically and Biologically Significant Areas in the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/036. v + 38 p Templeman, N.D. 2007. Placentia Bay-Grand Banks Large Ocean Management Area Ecologically and Biologically Significant Areas. Can. Sci. Advis. Sec. Res. Doc. 2007/052: iii + 15 p. Wells, N.J., Stenson, G.B., Pepin, P., and Koen-Alonso, M. 2017. Identification and Descriptions of Ecologically and Biologically Significant Areas in the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/013. v + 87 p. Wells, N., K. Tucker, K. Allard, M. Warren, S. Olson, L. Gullage, C. Pretty, V. Sutton-Pande and K. Clarke. 2019. Re-evaluation of the Placentia Bay-Grand Banks Area of the Newfoundland and Labrador Shelves Bioregion to Identify and Describe Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Res. Doc. 2019/049. viii + 138 p.

This dataset represents abundance data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey. Data is binned into 5-mm shell height bins, is prorated to an 800 m tow length and 17.5 feet (5.334 m) drag width (i.e., representing an area swept of 4267 m2), and was collected using unlined dredge gear. Each row represents a tow and contains information such as tow date, cruise name, gear type, 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 Commercial Size Abundance Data. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ecc09d98-56ed-4a27-ad62-5c3714a1d9b4

The Global Deterministic Wave Prediction System (GDWPS) produces wave forecasts out to 120 hours in the future using the third generation spectral wave forecast model WaveWatch III® (WW3). The model is forced by the 10 meters winds and the ice concentration from the Global Deterministic Prediction System (GDPS). The ice concentration is used by the model to attenuate wave growth in areas covered by 25% to 75% ice and to suppress it for concentration above 75%. Forecast elements include significant wave height, peak period and primary swell height, direction and period.

This dataset provides 1/36-degree monthly-mean ocean current climatology (April - September) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).

The GEBCO_2020 Grid was released in May 2020 and is the second global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid provides global coverage of elevation data in meters on a 15 arc-second grid of 43200 rows x 86400 columns, giving 3,732,480,000 data points. Grid Development The GEBCO_2020 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds. The grid uses as a ‘base’ Version 2 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with the gridded bathymetric data sets developed by the four Seabed 2030 Regional Centers. The Regional Centers have compiled gridded bathymetric data sets, largely based on multibeam data, for their areas of responsibility. These regional grids were then provided to the Global Center. For areas outside of the polar regions (primarily south of 60°N and north of 50°S), these data sets are in the form of 'sparse grids', i.e. only grid cells that contain data were populated. For the polar regions, complete grids were provided due to the complexities of incorporating data held in polar coordinates. The compilation of the GEBCO_2020 Grid from these regional data grids was carried out at the Global Center, with the aim of producing a seamless global terrain model. In contrast to the development of the previous GEBCO grid, GEBCO_2019, the data sets provided as sparse grids by the Regional Centers were included on to the base grid without any blending, i.e. grid cells in the base grid were replaced with data from the sparse grids. This was with aim of avoiding creating edge effects, 'ridges and ripples', at the boundaries between the sparse grids and base grid during the blending process used previously. In addition, this allows a clear identification of the data source within the grid, with no cells being 'blended' values. Routines from Generic Mapping Tools (GMT) system were used to do the merging of the data sets. For the polar data sets, and the adjoining North Sea area, supplied in the form of complete grids these data sets were included using feather blending techniques from GlobalMapper software version 11.0, made available by Blue Marble Geographic. The GEBCO_2020 Grid includes data sets from a number of international and national data repositories and regional mapping initiatives. For information on the data sets included in the GEBCO_2020 Grid, please see the list of contributions included in this release of the grid (https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2020/#compilations).

In 2012 and 2013, Fisheries and Oceans Canada conducted benthic imagery surveys in the Davis Strait and Baffin Basin in two areas then closed to bottom fishing, the Hatton Basin Voluntary Closure (now the Hatton Basin Conservation Area) and the Narwhal Closure (now partially in the Disko Fan Conservation Area). The photo transects were established as long-term biodiversity monitoring sites to monitor the impact of human activity, including climate change, on the region’s benthic marine biota in accordance with the protocols of the Circumpolar Biodiversity Monitoring Program established by the Council of Arctic Flora and Fauna. These images were analyzed in a techncial report that summarises the epibenthic megafauna found in seven image transects from the Disko Fan Conservation Area. A total of 480 taxa were found, 280 of which were identified as belonging to one of the following phyla: Annelida, Arthropoda, Brachiopoda, Bryozoa, Chordata, Cnidaria, Echinodermata, Mollusca, Nemertea, and Porifera. The remaining 200 taxa could not be assigned to a phylum and were categorised as Unidentified. Each taxon was identified to the lowest possible taxonomic level, typically class, order, or family. The summaries for each of the taxa include their identification numbers in the World Register of Marine Species and Integrated Taxonomic Information System’s databases, taxonomic hierarchies, images, and written descriptions. The report is intended to provide baseline documentation of the epibenthic megafauna in the Disko Fan Conservation Area, and serve as a taxonomic resource for future image analyses in the Arctic. Baker, E., Beazley, L., McMillan, A., Rowsell, J. and Kenchington, E. 2018. Epibenthic Megafauna of the Disko Fan Conservation Area in the Davis Strait (Eastern Arctic) Identified from In Situ Benthic Image Transects. Can. Tech. Rep. Fish. Aquat. Sci. 3272: vi + 388 p.

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.

This dataset is part of Environment and Climate Change Canada’s Shoreline Classification and Pre-Spill database. Shoreline classification data has been developed for use by the Environmental Emergencies Program of Environment and Climate Change Canada for environmental protection purposes. Marine and freshwater shorelines are classified according to the character (substrate and form) of the upper intertidal (foreshore) or upper swash zone (Sergy, 2008). This is the area where oil from a spill usually becomes stranded and where treatment or cleanup activities take place. The basic parameter that defines the shoreline type is the material that is present in the intertidal zone. The presence or absence of sediments is a key factor in determining whether oil is stranded on the surface of a substrate or can penetrate and/or be buried. This dataset contains thousands of linear shoreline segments ranging in length from 200 m and 2 km long. The entities represent the location of the segments and their geomorphological description. There exist further fields in the attribute table for this dataset. We are currently working on standardizing our shoreline segmentation datasets and the updated data will soon be uploaded to the catalog. Sergy, G. (2008). The Shoreline Classification Scheme for SCAT and Oil Spill Response in Canada. Proceedings of the 31stArctic and Marine Oil Spill Program Technical Seminar.Environment Canada, Ottawa, ON, Pp. 811-819.