This national dataset contains geographic range data for 488 Species at risk based on NatureServe data, SAR recovery strategies, Environment Canada resources and COSEWIC status reports.

Established Protected and Conservation Areas in the NWT

The Boreal Caribou data Package includes layers that are used for Boreal Caribou Range Planning in the NWT. This includes fire history, human disturbance, range planning regions as well as the 2020 Resource Selection Function layers for all seasons. Data sources and contact information can be found within each layer's metadata.

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.

Department of ENR/ITI Administrative Boundaries

A database of verified tornado tracks 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.

Description: These commercial whale watching data are comprised of two datasets. First, the ‘whale_watching_trips_jun_sep_british_columbia’ data layer summarizes commercial whale watching trips that took place in 2019, 2020 and 2021 during the summer months (June to September). The second data layer, ‘wildlife_viewing_events_jun_sep_british_columbia’ contains estimated wildlife viewing events carried out by commercial whale watching vessels for the same years (2019, 2020 and 2021) and months (June to September). Commercial whale watching trips and wildlife viewing events are summarized using the same grid, and they can be related using the unique cell identifier field ‘cell_id’. The bulk of this work was carried out at University of Victoria and was funded by the Marine Environmental Observation, Prediction and Response (MEOPAR) Network under the ‘Whale watching AIS Vessel movement Evaluation’ or WAVE project (2018 – 2022). The aim of the WAVE project was to increase the understanding of whale watching activities in Canada’s Pacific region using vessel traffic data derived from AIS (Automatic Identification System). The work was finalized by DFO Science in the Pacific Region. These spatial data products of commercial whale watching operations can be used to inform Marine Spatial Planning, conservation planning activities, and threat assessments involving vessel activities in British Columbia. Methods: A list of commercial whale watching vessels based in British Columbia and Washington State and their corresponding MMSIs (Maritime Mobile Service Identity) was compiled from the whale watching companies and Marine Traffic (www.marinetraffic.com). This list was used to query cleaned CCG AIS data to extract AIS positions corresponding to commercial whale watching vessels. A commercial whale watching trip was defined as a set of consecutive AIS points belonging to the same vessel departing and ending in one of the previously identified whale watching home ports. A classification model (unsupervised Hidden Markov Model) using vessel speed as the main variable was developed to classify AIS vessel positions into wildlife-viewing and non wildlife viewing events. Commercial whale watching trips in the south and north-east of Vancouver Island were limited to a duration of minimum 1 hour and maximum 3.5 hours. For trips in the west coast of Vancouver island the maximum duration was set to 6 hours. Wildlife-viewing events duration was set to minimum of 10 minutes to a maximum of 1 hour duration. For more information on methodology, consult metadata pdf available with the Open Data record. References: Nesdoly, A. 2021. Modelling marine vessels engaged in wildlife-viewing behaviour using Automatic Identification Systems (AIS). Available from: https://dspace.library.uvic.ca/handle/1828/13300. Data Sources: Oceans Network Canada (ONC) provided encoded AIS data for years 2019, 2020 and 2021, within a bounding box including Vancouver Island and Puget Sound used to generate these products. This AIS data was in turn provided by the Canadian Coast Guard (CCG) via a licensing agreement between the CCG and ONC for the non-commercial use of CCG AIS Data. More information here: https://www.oceannetworks.ca/science/community-based-monitoring/marine-domain-awareness-program/ Molly Fraser provided marine mammal sightings data collected on board a whale watching vessels to develop wildlife-viewing events classification models. More information about this dataset here: https://www.sciencedirect.com/science/article/pii/S0308597X20306709?via%3Dihub Uncertainties: The main source of uncertainty is with the conversion of AIS point locations into track segments, specifically when the distance between positions is large (e.g., greater than 1000 meters).

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

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.