The dataset is a compilation of the boundaries of the 19 NWT Electoral Districts based upon the 2012 Electoral Boundary Commission and the legal descriptions found in Bill 18 of Fifth Session, Seventeenth Legislative Assembly plus any Polling Divisions within each Electoral District as determined by Elections NWT.

The Thaidene Nëné (thy-Den-ay nen-ay) area is a celebrated cultural landscape with rich wildlife populations and unique geography located at the eastern end of Great Slave Lake in the Northwest Territories. The initial Thaidene Nëné study area was approximately 33,690 km2. Thaidene Nëné means ‘Land of the Ancestors’ in the Dënesųłı̨né language.

Mining Leases

Coal Exploration Licences

Canadian Homogenized Precipitation – Version 2 (CanHomP V2) The CanHomP V2 datasets were developed for climate trend analysis and include long-term monthly and daily precipitation series for 425 stations across Canada (Wang et al., 2026; Wang & Feng, 2026). Key improvements in Version 2 over its predecessor, CanHomPmlyV1 (Wang et al., 2023), include: • Expanded and improved source datasets, incorporating adjusted data from automated gauge stations and the Collaborative Rain, Hail and Snow (CoCoRaHS) network (https://www.cocorahs.org/canada.aspx) for recent decades. • Additional quality control procedures to remove false zeros in station data records for data-sparse regions or periods. • Enhanced changepoint detection, including tests on both untransformed and log-transformed data, and improved methods for identifying station-joining and variance inhomogeneities. • Use of more complete metadata for better accuracy. • Improved adjustment procedures to eliminate inhomogeneity by adjusting untransformed data series. • Development of homogenized daily precipitation series consistent with corresponding monthly totals (Wang & Feng, 2026). Key processing steps for both V1 and V2 include: • Merging observations from nearby sites to create long records, primarily using updated Adjusted Daily Rainfall and Snowfall data corrected for known issues such as unrealistic snow-water equivalent conversion, gauge wetting loss, and wind-induced undercatch (Wang et al., 2017). • Infilling data gaps using advanced spatial modeling of available data for the gap period. • Comprehensive quality control of data (Cheng et al., 2024). • Detecting non-climatic shifts using homogeneity tests with reference and station metadata. • Using up to four best neighbor stations as references, along with data derived from advanced spatial modeling of adjusted precipitation (MacDonald et al., 2021) and the Twentieth Century Reanalysis (20CRv3) ensemble-mean series of monthly precipitation (Slivinski et al., 2019). • Applying Quantile-Matching (QM) adjustments without reference data to correct non-climatic changes (Wang et al., 2026; Wang et al., 2023; Wang et al., 2010). Wang et al. (2023) also developed a dynamic QM adjustment method that uses the most strongly correlated homogeneous segment of nearby station data as a reference. They found that when station density is too low to identify suitable reference stations, adjustments without a reference could perform better than those with one, although results are similar for most stations. This approach may not be applicable to precipitation datasets with much higher station density or to variables with greater spatial coherence (e.g., surface air temperature). The QM method adjusts the entire distribution of data in one segment to match another (Wang et al., 2026; Wang et al., 2023; Wang & Feng, 2013; Wang et al., 2010), ensuring that distribution changes—including variance shifts—at identified changepoints are homogenized. Differences from AHCCD adjusted precipitation data • CanHomP V2: Adjusted, gap-filled, homogenized monthly and daily precipitation data for 425 core stations for the period up to 2023. • AHCCD adjusted precipitation: Adjusted but unhomogenized monthly and daily precipitation data for 464 manual stations for the period up to 2012 (Mekis & Vincent, 2011). References Wang, X. L., Feng, Y., Zwiers, F. W., & Cheng, V. Y. S. (2026). Precipitation trends in version 2 of Canadian homogenized monthly precipitation dataset. Atmosphere-Ocean, 1-16. https://doi.org/10.1080/07055900.2026.2617861. Wang, X. L., & Feng, Y. (2026). Observed trends in precipitation extreme indices as inferred from a homogenized daily precipitation dataset for Canada. Weather and Climate Extremes, 51, 100860. https://authors.elsevier.com/sd/article/S2212-0947(26)00011-3. Wang, X.L, Y. Feng, V. Y. S. Cheng, H. Xu, 2023: Observed precipitation trends inferred from Canada’s homogenized monthly precipitation dataset, J. Clim., 36, 7957-7971. DOI: 10.1175/JCLI-D-23-0193.1. Wang, X. L., H. Xu, B. Qian, Y. Feng, E. Mekis, 2017: The adjusted daily rainfall and snowfall data for Canada. Atmos.-Ocean, 55:3, 155-168, DOI:10.1080/07055900.2017.1342163. Cheng, V. Y. S., Wang, X.L., and Y. Feng, 2024: A quality control system for historical in situ precipitation data. Atmosphere-Ocean, 62(4), 271-287, https://doi.org/10.1080/07055900.2024.2394836. 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. MacDonald, H., D. W. McKenney, X. L. Wang, J. Pedlar, P. Papadopol, K. Lawrence, M. F. Hutchinson, 2021: Spatial Models of adjusted precipitation for Canada at varying time scales. J. Appl. Meteor. And Climatol., 60, 291-304. DOI: 10.1175/JAMC-D-20-0041.1. Slivinski, L. and coauthors, 2019: Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system. Q. J. R. Meteor. Soc., 2876-2908, https://doi.org/10.1002/qj.3598. Mekis, E., & Vincent, L. A. (2011). An overview of the second generation adjusted daily precipitation dataset for trend analysis in Canada. Atmosphere-Ocean, 49, 163–177. https://doi.org/10.1080/07055900.2011.583910.

Mineral Claims

Department of ENR/ITI Administrative Boundaries

The Canadian Protected and Conserved Areas Database (CPCAD) is the authoritative source of data on protected and conserved areas in Canada. The database consists of the most up-to-date spatial and attribute data on marine and terrestrial protected areas in all governance categories recognized by the International Union for Conservation of Nature (IUCN), as well as Other effective area-based conservation measures (OECMs, or conserved areas) across the country. Indigenous Protected and Conserved Areas (IPCAs) are also included if they are recognized as protected or conserved areas. CPCAD adheres to national reporting standards and is freely available to the public. CPCAD is compiled and managed by Environment and Climate Change Canada (ECCC), in collaboration with federal, provincial, territorial, and other reporting authorities that provide the data. The database contains combined data from all these Canadian reporting authorities, who have determined that their areas meet the Canadian criteria as protected or conserved areas. CPCAD is used by a wide range of organizations, including governments, environmental non-governmental organizations (ENGOs), academia, land managers, industry, and the general public. CPCAD supports many of the Government of Canada’s priorities including Canada’s national reporting on protected areas, Canada’s international reporting on protected areas as a result of Canada’s commitments under the United Nations Convention on Biological Diversity, and Canada’s protected areas program by providing baseline information. More detailed information on CPCAD is available by downloading the User Manual. The data is current as of the date of the most recent revision. For prior years, please reach out to scf-geocarto-cws-geomapping@ec.gc.ca.

A database of verified tornado occurrences across Canada has been created covering the 30-year period from 1980 to 2009. The tornado data have undergone a number of quality control checks and represent the most current knowledge of past tornado events over the period. However, updates may be made to the database as new or more accurate information becomes available. The data have been converted to a geo-referenced mapping file that can be viewed and manipulated using GIS software.

This data set includes the locations of all known seabird colonies along the coast of British Columbia, and provides a compilation of the population estimates of seabirds breeding at those colonies since 1980, and historical estimates prior to 1980 for some colonies. It does not include an estimate of the numbers of juvenile birds or non-breeders in the population. The rationale for developing this inventory was the recognized need for a product that could assist with: coastal zone and conservation area planning; emergency response to environmental emergencies and identifying areas of potential interactions between seabirds and anthropogenic activities. In addition, the data used to develop the document provides a baseline to compare with future seabird population estimates in order to measure the impacts of shifts in composition, abundance and/or distribution of prey, and climatic and oceanographic changes. The database is not a substitute for on-site surveys usually required for environmental assessment. Here we present data on the breeding colony population estimates of the 17 species of seabirds (including two storm petrels, three cormorants, one gull, and eight alcids) and one shorebird (Black Oystercatcher Haematopus bachmani) that breed on the coast of British Columbia. Over 5.5 million colonial birds are currently estimated to nest at 649 sites (Rodway et al. 2024). Five species (Cassin's Auklets Ptychoramphus aleuticus, Fork-tailed Storm-petrels (Hydrobates fucatus), Rhinoceros Auklets Cerorhinca monocerata, Ancient Murrelets Synthliboramphus antiquus, and Leach's Storm-petrels (Hydrobates leucorhous), comprise the vast majority of that population, although Black Oystercatchers (Haematopus bachmani), Pigeon Guillemots (Cepphus columba), and Glaucous-winged Gulls (Larus glaucescens), nest at the most sites. Marbled Murrelets (Brachyramphus marmoratus), which nest on the mossy limbs of mature and old-growth trees within the coastal forests, are not included in this database, due to their dispersed nesting habit. The population estimates presented in this database are compiled from the results of several surveys. Many of the seabird breeding colonies in British Columbia have been known for more than 50 years, but because of the remoteness of the sites, visits to them have been rare. The majority of the data are the results of comprehensive inventories of colonial nesting seabirds along the British Columbia coastline conducted between 1974 and 1977 by the British Columbia Provincial Museum (BCPM; now Royal British Columbia Museum ) and between 1980 and 1989 by the Canadian Wildlife Service of Environment and Climate Change Canada (CWS). The goal of the BCPM surveys was to explore the entire BC coast to identify seabird nesting sites. Reliable, quantitative data were gathered on the breeding populations of all surface-nesting seabird species and rough estimates of population sizes were made for burrow-nesting species. The goal of the CWS survey program was to establish baseline estimates of breeding populations of burrow-nesting species in BC using standardized survey techniques to allow future comparisons and monitoring of those populations. During the 1980s, repeat surveys of surface-nesting species were also conducted by CWS in most regions of the BC coast. A few colonies on small remote islands were not visited during those surveys. Therefore, for some colonies the most current population estimates are from the first complete survey of the BC coastline, carried out by the Royal British Columbia Museum in the mid 1970’s. Since 1989, surveys have been conducted by CWS on some alcid, cormorant and gull colonies along the BC coast, and results have been included in the dataset (data entry ongoing). As well as data from CWS surveys, we have attempted to obtain recent data from all other sources including Parks Canada, Transport Canada, the BC Ministry of Forests, Lands, Natural Resource Operations and Rural Development, the City of Vancouver, the Bamfield Marine Station, and the Laskeek Bay Conservation Society. Since 2000, inventories of nesting Black Oystercatchers have been conducted in some regions of the coast by Parks Canada and partners (Gulf Islands National Park Reserve, Pacific Rim National Park Reserve, and Gwaii Haanas National Park Reserve) and results have been included in the dataset (data entry ongoing). A long time series of nesting Black Oystercatcher data collected by Laskeek Bay Conservation Society in the Laskeek Bay area of the East Coast of Moresby Island has also been included in this dataset.