This series includes maps of projected change in mean precipitation based on CMIP5 multi-model ensemble results for RCP2.6, RCP4.5 and RCP8.5, expressed as a percentage (%) of mean precipitation in the reference period. The median projected change across the ensemble of CMIP5 climate models is shown. Maps are provided for three time periods: 2016-2035, 2046-2065 and 2081-2100. For more maps on projected change, please visit the Canadian Climate Data and Scenarios (CCDS) site: https://climate-scenarios.canada.ca/?page=download-cmip5.

This interactive map commemorates Canada’s participation in armed conflicts at home and abroad by highlighting a sample of the many geographical features and places named for those that served our country. These commemorative geographical names help us remember war casualties, soldiers, sailors, airmen and airwomen, military leaders, and civilians recognized or decorated for outstanding acts of bravery and sacrifice in battle. These names also commemorate notable battles in which Canada participated, and Canadian military units, regiments, squadrons, and ships in which Canadians served. Federal, provincial and territorial members of the Geographical Names Board of Canada provided these commemorative names for the development of the map. Many more commemorative place names exist in Canada, and will be added in future releases of this evergreen interactive map. If you would like to contribute names to this project, please contact the Geographical Names Board of Canada Secretariat at Natural Resources Canada.

A Conservation Unit (CU) is a group of wild Pacific salmon sufficiently isolated from other groups that, if extirpated, is very unlikely to recolonize naturally within an acceptable timeframe, such as a human lifetime or a specified number of salmon generations. Holtby and Ciruna (2007) provided a framework for aggregating the five species of salmon (genus Oncorhynchus) found on Canada’s Pacific coast into species-specific CUs based on three primary characteristics: ecotypology, life history and genetics. The first stage in the description of the Conservation Units is based solely on ecology. The ecotypologies used in this framework include a combined characterization of both freshwater and near-shore marine environments, and is termed “joint adaptive zone”. The second stage of the description involves the use of life history, molecular genetics, and further ecological characterizations to group and partition the first stage units into the final Conservation Units. The result is CUs that are described through the joint application of all three axes. It is important to note that CUs are distinct from other aggregates of Pacific salmon, such as designatable units (DUs) under the Species at Risk Act or management units (MUs). CU Counting Sites: Salmon spawner enumeration data in the Pacific Region is stored and managed in the New Salmon Escapement Database (NuSEDS). The term “escapement” is used to refer to the group of mature salmon that have ‘escaped’ from various sources of exploitation, and returned to freshwater to spawn and reproduce. This data is assigned to a “Counting Site”, which may be a complete watercourse with a marine terminus, a tributary to a larger watercourse, or a defined reach within a watercourse that may or may not encompass the entire population but represents an index of the abundance of that population. CU Status: CUs form the basic unit for assessment under Canada’s Policy for the Conservation of Wild Salmon Policy (WSP) (DFO 2005). The biological status of a CU is evaluated using a number of metrics (Holt et al. 2009; Holt 2009), which indicate a WSP status zone: Red (poor status), Amber (marginal status), or Green (healthy status). A final step then incorporates all metric and status-related information into a final integrated status for each CU, along with expert commentary to support the final status determination (e.g., DFO 2012; DFO 2016). This information is used as inputs to fisheries management processes to help prioritize assessment activities and management actions. Note: CU boundaries were reviewed in 2020-2021 and have been updated from the BC Freshwater Atlas 1:50,000 scale to the BC Freshwater Atlas 1:20,000 scale. The CU boundaries were last updated in March 2023. Please be aware that CUs may be reviewed and are subject to change without notice. Please refer to Conservation Unit Review Requests-Form and Summary for a list of CU review requests that are ongoing or have been finalized.

Dataset of species/gear type commercial fisheries from 2014 to 2023 in the Eastern Canada Regions. Only fish harvested from the NL, Maritimes, Gulf, Quebec and Eastern Arctic regions are included (Species Sought). The data was obtained from Statistical Services, Fisheries and Oceans Canada (DFO) and consists of commercial species/gear type landings data from 2014 to 2023 taken from Northwest Atlantic Fisheries Organization (NAFO) Subareas 0, 2, 3, 4 and 5 and fished in the NL, Maritimes, Gulf, Quebec and Eastern Arctic regions. The layer was created by overlaying a 2 minute hexagonal grid (approx. 10km2 cell) on species/gear type commercial fisheries point data and summing the total landings by weight reported for each cell over the ten year period. Therefore, the value of each grid cell is equal to the total species/gear type landings in kg from 2014 to 2023 for the area, and may represent many fishing events from several vessels over the ten year period. All landings are from Canadian vessels and does not include information pertaining to international fishing vessels (i.e., St. Pierre). Individuals should exercise caution when interpreting this data. Data has not been altered and is mapped from the original logbook entry for each record prior to amalgamation. Data may contain errors such as inaccurate or nonviable coordinates, landed weights and/or species identification. For example, cases of fishing events reported in a NAFO Division with corresponding coordinates falling outside that particular NAFO Division or fishing events which appear to be located on a land mass due to rounding errors in the original entries. Such cases were excluded from the dataset. Only one location is given for each fishing event; therefore, a fishing activity that would normally cover a large area (i.e., trawling) is only shown in a single location. Some species may not include all records or locations where activity is taking place due to regional differences in permissions for mapping, or because the fishery is only partially georeferenced (e.g. Lobster). The locations/areas shown should only be used as an estimation of fishing intensity and a general guide of where particular species/gear type fishing occurs. This dataset has been privacy screened to comply with the Government of Canada's privacy policy. Privacy assessments were conducted to identify NAFO unit areas containing data with less than five vessel IDs, license IDs and fisher IDs. If this threshold was not met, catch weight locations have been withheld from these statistical areas to protect the identity or activity of individual vessels or companies. In some instances, permissions were obtained to map species or gears with a limited number of vessels, licenses, or fisher ids. The withheld areas are indicated by the unit area that has been removed and given a weight of -9999.

Compiled by Alberta Data Partnerships Ltd. (ADP), on behalf of the Government of Alberta, the ATS v4.1 Polygons - Quarter Section with Road Allowance layer contains polygons that represent the location of Quarter Sections and adjacent Road Allowance Segment polygons, derived from the Master Alberta Township System points file published as ATS Version 4.1, dated March 31, 2005, and clipped to an updated Alberta Data Partnerships Ltd. (ADP) created version of the Alberta provincial boundary.

The data layer (.tif) presented are the results of using MaxEnt to produce a single species habitat map for Sea Scallop (Placopecten magellanicus) on German Bank (off South West Nova Scotia, Canada). Presence data derived from videos and still images were compared against environmental variables derived from multibeam bathymetry (Slope, Curvature, Aspect and Bathymetric Position Index (BPI)), and backscatter data (principal components: Q1, Q2, and Q3). Results represent a probability of habitat suitability for Sea Scallop on German Bank. Probability of suitability: The probability that a given habitat is suitable for a species based on presence data and underlying environmental variables (i.e. probability of species occurrence). 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.2012.04.009 Cite this data as: Brown, C. J., Sameoto, J. A., & Smith, S. J. Data of: Distribution of Sea Scallop on German Bank. Published: February 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/2bb98a09-5daf-42c4-94e8-e5de718b821d

Description: Seasonal sigma-t climatology of the Northeast Pacific Ocean was computed from historical observations including all available conductivity-temperature-depth (CTD), bottle, expendable bathy-thermograph (XBT), and Argo data in NOAA (http://www.argo.ucsd.edu/), Marine Environmental Data Service (MEDS), and Institute of Ocean Sciences archives over 1980 to 2010 period. Methods: Calculations, including smooth and interpolation, were carried out in sixty-five subregions and up to fifty-two vertical levels from surface to 5000m. Seasonal averages were computed as the median of yearly seasonal values. 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 sigma-t climatology for the Canadian Pacific Exclusive Economic Zone (EEZ), a subset of seasonal climatology of the Northeast Pacific Ocean, in high spatial resolution of 1/300 degree. References: Foreman, M. G. G., W. R. Crawford, J. Y. Cherniawsky, and J. Galbraith (2008). Dynamic ocean topography for the northeast Pacific and its continental margins, Geophys. Res. Lett., 35, L22606, doi: 10.1029/2008GL035152 Data Sources: NOAA, MEDS and IOS observational 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.

Province-wide SDE layer showing licensed water sources (streams and lakes), under the Water Act, (current and historical), not captured (displayed) on TRIM base mapping (or Freshwater Atlas base mapping). Includes an attribute for the internal Source Code number, which is associated with the (E-Licensing) stream name.

The Agriculture and Agri-Food Canada’s LiDAR Projects dataset was created from existing spatial data. It contains the footprints (outlines) of all the LiDAR data that is openly distributed by Agriculture and Agri-Food Canada. LiDAR (Light Detection And Ranging) is a method of acquiring survey points using optical remote sensing technology. The dataset indicates basic information about the location, source and properties of the data.