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 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 second of a series aiming to provide an oceanographic knowledge baseline of the Coast of Bays.This dataset includes temperature, salinity, and dissolved oxygen concentration profiles collected during CTD surveys, each survey containing a varying number of casts/profiles taken within the area of interest. In total, 760 profiles from 11 surveys, executed over 276 stations, were collected from June 2009 to November 2013. Data were processed and quality controlled using the instrumentation manufacturer guidelines, custom tools as well as visual inspection. Data are provided in tab-delimited text-based format compatible with most data processing language and tools (e.g. MS. Excel) as well as with the Ocean Data View software (https://odv.awi.de/) for rapid visualisation. A summary of the CTD profiles and stations surveyed is also provided as a comma separated values (CSV) file.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_077-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 layer details Important Areas (IAs) relevant to coral, sponge, and reef-building species in the Pacific North Coast Integrated Management Area (PNCIMA). 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 IAs 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, fish, geographic features, invertebrates, and other vertebrates.Though data collection is considered complete, the emergence of significant new data may merit revisiting of IAs on a case by case basis.

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.

This layer details Important Areas (IAs) relevant to coral, sponge, and reef-building species in the West Coast Vancouver Island (WCVI) 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).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.Though data collection is considered complete, the emergence of significant new data may merit revisiting of IA's on a case by case basis.Other datasets in this series detail IAs for birds, cetaceans, fish, geographic features, invertebrates, and other vertebrates.This package also includes project documentation and tech reports relevant to the IA process and its role within the selection of EBSAs.

This layer details Important Areas (IAs) relevant to important geographic features in the Pacific North Coast Integrated Management Area (PNCIMA). 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, invertebrates, 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.

The joint Natural Resources Canada/Department of Fisheries and Oceans Marine Spatial Planning Program requires the highest resolution marine based bathymetric elevation data and adjacent land based topographic elevation data that are available. This digital elevation model of Canada's west coast compiles the best data available from multiple government agencies to create a regional model gridded at 10 meter spacing. The transitions between the marine and terrestrial areas are seamless creating a continuous surface of elevations for scientific research and mapping.

The shallow, coastal regions of the world’s oceans are highly productive ecosystems providing important habitat for commercial, forage, endangered, and iconic species. Given the diversity of ecosystem services produced or supported by this ecosystem, a better understanding of its structure and function is central to developing an ecosystem-based approach to management. However this region termed the ‘white strip’ by marine geologists because of the general lack of high-resolution bathymetric data - is dynamic, highly variable, and difficult to access making data collection challenging and expensive. Since substrate is a key indicator of habitat in this important ecosystem, we created a continuous substrate map of Bottom Patches (BoPs) from the best available bottom type data using an approach that is simple, quantitative, and transparent making it amenable to iterative improvement as data quality and availability improve. To provide subsequent analyses (such as habitat models) with some confidence in the defined bottom type values, we developed a corresponding confidence surface based on the agreement of, and distance between observations. Such data are critical to assessments of species distributions and anthropogenic risk. Bottom patches (BoPs) have been created to represent bottom type for the entire Pacific Canadian coast from the high high water line to a depth of 50 metres (m). As a polygon representation, the BoPs describe patches of similar substrate prescribed by depth classes and the available field observations. In the areas where no observations are available, predicted bottom type values are used. The approach is described in Gregr et al. (2013), as a spatial framework for representing nearshore ecosystems. Accuracy of the bottom type depends on a multitude of factors but primarily the reliability and density of the bottom type observations. The horizontal accuracy of these data likely ranges from metres to 10s of metres because of the source data or data processing required. Areas with a higher data density, where the data show strong coherence, are understood to have higher accuracy. The BoPs use depth ribbons (polygons describing bathymetric ecozones) as an input. Depth ribbons for Pacific Canada were created from a high resolution (20 x 20 m2) bathymetry. Given the resolution of these data, processing was facilitated by dividing the Pacific Coast into 5 regions.The West Coast of Vancouver Island, extending from Cape Sutil in the North past Port San Juan to the South, includes a total of 110,313 BoP polygons. Bottom Patches for Queen Charlotte Strait and Strait of Georgia regions were combined for a total of 235,754 BoP polygons. The North Central Coast region, extending from the Alaskan border in the North to Cape Caution in the South, includes a total of 431,639 BoP polygons. The Haida Gwaii region includes a total of 86,825 BoP polygons.These data are intended for scientific research only. The developers (Fisheries and Oceans Canada, SciTech Environmental Consulting) are not responsible for damages resulting from any omissions or errors that may be contained in this dataset and expressly disclaims any warranty of fitness for any particular purpose. Developers shall not be liable for any losses, financial or otherwise, due to the use of these data. The user assumes the entire risk as to the suitability, results and performance of the dataset for their proposed use. Please credit SciTech and Fisheries and Oceans Canada as the source of the data in any maps, reports, or articles that are printed or published on paper or the Internet.

High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

The dataset includes timeseries of horizontal current speed and direction, vertical current speed, water depth, and temperature at instrument depth from Acoustic Doppler Current Profiler (ADCP) moorings. Data were collected 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. This dataset is the third of a series aiming to provide an oceanographic knowledge baseline of the Coast of Bays, Newfoundland. It consists of 73 ADCP timeseries varying in length from about 26 days to 235 days collected between 2009 and 2014. 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), Proceedings (http://www.dfo-mpo.gc.ca/csas-sccs/Publications/Pro-Cr/2017/2017_043-eng.html) and several research documents were published.