Coal Exploration Licences

This dataset displays the geographic areas within which critical habitat (CH) for terrestrial species at risk, listed on Schedule 1 of the federal Species at Risk Act (SARA), occurs in Canada. Note that this includes only terrestrial species and species for which Environment and Climate Change Canada (ECCC) and Parks Canada Agency (PCA) lead. Under SARA, critical habitat is “the habitat that is necessary for the survival or recovery of a listed wildlife species and that is identified as the species’ critical habitat in the recovery strategy or action plan for the species.” To precisely define what constitutes critical habitat for a particular species it is essential that this geospatial information be considered in conjunction with complementary information provided in a species’ recovery document. Recovery documents are available from the Species at Risk (SAR) Public Registry (https://www.canada.ca/en/environment-climate-change/services/species-risk-public-registry.html) for two posting stages (proposed and final posting). The recovery documents contain important information about the interpretation of the geospatial information, especially regarding the biological and environmental features (“biophysical attributes”) that complete the definition of a species’ critical habitat. Within any defined critical habitat geospatial boundary, not all of the area is necessarily critical habitat. It is important to note that recovery planning documents (and, therefore, critical habitat) may be amended from time to time as new information becomes available, which may occur after a document has been posted as proposed or final on the SAR Public Registry. The SAR Public Registry should always be considered as the main source for critical habitat information. In cases where the data are sensitive, the geographic area within which critical habitat occurs may be represented as grids. These are coarse grids (1, 10, 50 or 100 square kilometres) that serve as indicators to locate critical habitat in the recovery planning document. More detailed information on critical habitat may be made available on a need-to-know basis by contacting Environment and Climate Change Canada – Canadian Wildlife Service at ec.planificationduretablissement-recoveryplanning.ec@canada.ca. The data is current as of the date of the most recent revision.

Mineral Claims

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). ITS-90 water temperature and Water body salinity variables have been also included (as-is) to complete the Eutrophication and Acidity data. If you use these variables for calculations, please refer to SeaDataNet for having the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets. This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (18 parameters with quality flag indicators), and covers the Northeast Atlantic Ocean (40W) with 381639 CDI records (381085 Vertical profiles and 554 Time series). Vertical profiles temporal range is from 1921-10-15 to 2020-10-16. Time series temporal range is from 1974-06-14 to 2019-04-24. Data were aggregated and quality controlled by 'IFREMER / IDM / SISMER - Scientific Information Systems for the SEA' from France. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/. Detailed documentation is available at: https://dx.doi.org/10.6092/4e85717a-a2c9-454d-ba0d-30b89f742713 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/eutrophication%3EAtlantic The aggregated dataset can also be downloaded as ODV collection and spreadsheet, which is composed of metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ). The original datasets can be searched and downloaded from EMODnet Chemistry Chemistry CDI Data and Discovery Access Service: https://emodnet-chemistry.maris.nl/search

NWT Species at Risk Data

Ts’udé Nilįné Tuyeta Established Protected Area

Ecologically Based Landscape Classification Data

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the Norwegian Sea, Barents Sea, Greenland Sea and Icelandic Waters with 114721 CDI stations. Data were aggregated and quality controlled by 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)'. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12 ). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/ Detailed documentation is available at: https://dx.doi.org/10.6092/4e85717a-a2c9-454d-ba0d-30b89f742713 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/eutrophication>Arctic The aggregated dataset can also be downloaded as ODV collection and spreadsheet, which is composed of metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ) The original datasets can be searched and downloaded from EMODnet Chemistry Chemistry CDI Data and Discovery Access Service: https://emodnet-chemistry.maris.nl/search

Canadian Homogenized Surface Air Temperature – Version 3.1 (CanHomT V3.1) This dataset is an update of the Third Generation Homogenized Temperature dataset (Vincent et al. (2020), extended through 2023. It was developed for climate trend analysis and includes long-term daily maximum, minimum, and mean temperature series for 780 stations (776 locations) in Canada. The key enhancement in V3.1 is the inclusion of both Original and Adjusted data, together with their associated data flags and the source station climate ID, providing improved traceability, reproducibility, and transparency. Key processing steps include: • Merging observations from nearby sites to create long records • Quality control of data • Adjusting daily minimum temperatures since July 1961 for the observing-time (climatological day definition) change at 96 principal stations (Vincent et al., 2009) • Detecting non-climatic shifts in annual and seasonal average temperature data series using homogeneity tests with reference and station metadata. • Applying Quantile-Matching (QM) adjustments with reference data (including parallel observations) to correct non-climatic changes (Vincent et al., 2018; Wang et al., 2010). Parallel observations —simultaneous measurements from old and new instruments or locations—were used whenever available because they provide the most reliable basis for data homogenization. Adjustments made without suitable reference data carry greater uncertainty, and this increased uncertainty should be quantified and clearly communicated (WMO, 2020). The QM method adjusts the entire distribution of data in one segment to match another (Wang et al., 2026; Vincent et al., 2018; Wang & Feng, 2013; Wang et al. 2010), ensuring that distribution changes—including variance shifts—at identified changepoints are homogenized. The gridded version of monthly CanHomT V3.1, called CanGridT mlyV3.1 [https://open.canada.ca/data/en/dataset/781e02cc-6c1b-462e-b61b-f96c607b23bd], was found to represent Canada’s warming trend reasonably well since 1900, despite changes in data availability over time (Wang et al., 2026, see their Figure S3). References Vincent, L.A., M.M. Hartwell and X.L. Wang, 2020: A Third Generation of Homogenized Temperature for Trend Analysis and Monitoring Changes in Canada’s Climate. Atmosphere-Ocean, 58(3), 173–191. https://doi.org/10.1080/07055900.2020.1765728. Vincent, L.A., E.J. Milewska, R. Hopkinson and L. Malone, 2009: Bias in minimum temperature introduced by a redefinition of the climatological day at the Canadian synoptic stations. J. Appl. Meteor. Climatol, 48, 2160-2168. DOI: 10.1175/2009JAMC2191.1. Vincent, L.A., E.J. Milewska, X. L. Wang, and M. M. Hartwell, 2018. Uncertainty in homogenized daily temperatures and derived indices of extremes illustrated using parallel observations in Canada, Intl. J. Climatol., 38:2, 692-707. DOI: 10.1002/JOC.5203. Wang, X. L. and Y. Feng, published online July 2013: RHtestsV4 User Manual. Climate Research Division, Atmospheric Science and Technology Directorate, Science and Technology Branch, Environment Canada. 28 pp. [Available online at https://github.com/ECCC-CDAS] DOI: 10.13140/RG.2.2.17309.17125. Wang, X. L., H. Chen, Y. Wu, Y. Feng, and Q. Pu, 2010: New techniques for detection and adjustment of shifts in daily precipitation data series. J. Appl. Meteor. Climatol., 49, 2416-2436. DOI: 10.1175/2010JAMC2376.1. WMO. (2020). Guidelines on Homogenization (2020 edition). World Meteorological Organization. WMO-No. 1245. https://library.wmo.int/records/item/57130-guidelines-on-homogenization?offset=1. Wang, X. L., Feng, Y., Zwiers, F. W., & Cheng, V. Y. S. (2026). Precipitation trends in version 2 of the Canadian homogenized monthly precipitation dataset. Atmosphere-Ocean, 1–16, https://doi.org/10.1080/07055900.2026.2617861.