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

The hydrographic 1991 to 2020 climatology for the Maritimes region Atlantic Zone Monitoring Program core transects, Cabot Strait, Louisbourg, Halifax, Browns Bank, and Northeast Channel, are calculated to support annual reporting on seasonal variability. Details on data coverage for these transects and ancillary transects occupied since the inception of the program are provided. Comparisons with the previous climatology period, years 1981 to 2010, are summarized when possible.Cite this data as: Layton, C. Data of:Maritimes Region Atlantic Zone Monitoring Program 1991 to 2020 Hydrographic Transect Climatology.Published: August 2025. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.https://open.canada.ca/data/en/dataset/5f9c5d65-3ce1-4bdd-8b43-34086620d1e3

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).

Description:Seasonal climatologies for salinity of the Northeast Pacific Ocean were computed to cover the period 2001 to 2020. Historibal observations included all available conductivity-temperature_depth (CTD), bottle and profiling floats in the NODC World Ocean Database, Marine Environmental Data Services (MEDS), Institute of Ocean Sciences Water Properties website and the Canadian Integrated Ocean Observing System (CIOOS Pacific).Methods:Interpolation was carried out in up to fifty-two vertical levels from surface to 5000m. Data-Interpolating Variational Analysis (DIVA) was used for spatial interpolation for all years within each season and estimates projected onto a consistent grid. The average of the grid nodes was calculated to obtain the seasonal climatology. DIVA was used again on the final climatology followed by a median filter and a 5-point smoother. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal salinity climatology for the Canadian Pacific Exclusive Economic Zone (EEZ), a subset of seasonal climatology of the Northeast Pacific Ocean, with high spatial resolution of 1/300 degree.Data Sources:NODC, MEDS, IOS and CIOOS Pacific Data.Uncertainties:Uncertainties are introduced when quality controlled observational data are spatially interpolated to varying distances from the observation point. Climatological averages are calculated from these interpolated values.

Climatological monthly-mean temperature and salinity data were computed for each of the 27 Line P stations (https://www.dfo-mpo.gc.ca/science/data-donnees/line-p/index-eng.html). For any particular station, data were accepted as belonging to that station if the location was within 10 km of the intended station (or 24km at Ocean Station Papa, P26). Data were binned by month/year over all available data for each station up to and including 2012. Hence the time interval that the mean state was computed from starts between 1956 and 1960 and ends at the end of 2012. Standard deviations were computed for each month independently and at each 5-m depth bin and were estimated as the variability between different years for the month in question.

The data layer (.shp) presented is the result of an unsupervised classification method for classifying seafloor habitat on German Bank (off South West Nova Scotia, Canada). This method involves separating environmental variables derived from multibeam bathymetry (Slope, Curvature) and backscatter (principal components: Q1, Q2, and Q3) into spatial units (i.e. pixels) and classifying the acoustically separated units into 5 habitat classes (Reef, Glacial Till, Silt, Silt with Bedforms, and Sand with Bedforms) using in situ data (imagery). Benthoscape classes (synonymous to landscape classifications in terrestrial ecology) describe the geomorphology and biology of the seafloor and are derived from elements of the seafloor that were acoustically distinguishable.Unsupervised classifications (acoustic classifications) optimized at 15 classes using Idrisi CLUSTER method (pixel based)Number representing the benthoscape classes (CLASS) derived from in situ imagery and video (See Brown et al., 2012, Figure 3, Table 1).Benthoscape classes (See Brown et al., 2012, Figure 3).Reference:Brown, C. J., Sameoto, J. A., & Smith, S. J. (2012). Multiple methods, maps, and management applications: Purpose made seafloor maps in support of ocean management. Journal of Sea Research, 72, 1–13. https://doi.org/10.1016/j.seares.2012.04.009Cite this data as: Brown, C. J., Sameoto, J. A., & Smith, S. J. Data of: Benthoscape Map of German Bank. Published: February 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b7f81d4a-2cb6-4393-b35b-e536ec63e834

A derivative of DFO's benthic imagery surveys for the Marine Conservation Targets Program in the St. Anns Bank Marine Protected Area (https://open.canada.ca/data/en/dataset/2a55e2b4-cbb6-4fea-b17e-a16f5e99e68f), occurrence records in this analysis represent presence/absence and density of a biogenic habitat-forming species in five drift-camera transects in the southeast corner of the MPA, off the coast of Cape Breton, Nova Scotia, Canada. Presence/absence and count data of the unstalked crinoid (Heliometra glacialis) were derived from the use of high-resolution Nikon D850 still images (n=428, see link to parent record for more descriptive survey information and complete imagery dataset) and continuous high-definition video observations (approximately one observation every second using a 1Cam Mk6, SubC Imaging camera; n=8522). Densities were estimated by dividing the crinoid counts by the field of view (calculated from lasers with 10-cm spacing). Substrates were reported for each video observation, documenting the dominant substrate (>50% cover) according to a modified Wentworth scale (i.e., sand, gravel, pebble, cobble, boulder, bedrock; Wentworth 1922). Crinoids were observed in ~44% of the area of the five transects (~4811 m2), forming dense beds along sloped features from 77-119-m depths, predominantly on cobble and pebble substrates, reaching densities of up to 59 ind. m-2 and 139 ind. m-2 in the digital still images and video observations, respectively.Cite this data as: Lawton P, Teed L. Fine-scale observations of high density Heliometra glacialis (Crinoidea) beds from five near-seafloor imagery transects from a two-year survey in the St. Anns Bank Marine Protected Area, Atlantic Canada. Published March 2026. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B.References:- Wentworth, C.K. 1922. A scale of grade and class terms for clastic sediments. The Journal of Geology 30(5): 377-392.

This dataset contains observations of species occurrences from seafloor imagery collected by the autonomous underwater vehicle (AUV) during the 2012 Expedition to Cobb Seamount. The National Oceanographic and Atmospheric Administration-operated SeaBED-class AUV which collected photographic images from 4 transects ranging from 436 m to 1154 m in depth.

IBL - Imagery, basemaps, and land cover (imageryBaseMapsEarthCover) Basemaps. For example, resources describing land cover, topographic maps, and classified and unclassified images

The data layer (.shp) presented is the result of an unsupervised classification method for classifying seafloor habitat in the Bay of Fundy (Northwest Atlantic, Canada). This method involves separating environmental variables derived from multibeam bathymetry (slope, bathymetric position index), backscatter, and oceanographic information (wave-shear current velocity) into spatial units (i.e. image objects) and classifying the acoustically and oceanographically separated units into 7 habitat classes (Bedrock and Boulders, Mixed Sediments, Gravelly Sand, Sand, Silty Gravel with Anemones, Silt, and Tidal Scoured Mixed Sediments) using in-situ data (imagery). Benthoscape classes (synonymous to landscape classifications in terrestrial ecology) describe the geomorphology and biology of the seafloor and are derived from elements of the seafloor that were acoustically and oceanographically distinguishable. Reference:Wilson, B.R., Brown, C.J., Sameoto, J.A., Lacharite, M., Redden, A. (2021). Mapping seafloor habitats in the Bay of Fundy to assess macrofaunal assemblages associated with Modiolus modiolus beds. Estuarine, Coastal and Shelf Science, 252. https://doi.org/10.1016/j.ecss.2021.107294Cite this data as: Wilson, B.R., Brown, C.J., Sameoto, J.A., Lacharite, M., Redden, A. Bay of Fundy Benthoscape. Published May 2023. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/dbabd17a-a2c7-4b3f-9bd8-a77a9c7f9c1c