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From 1 - 10 / 1896
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    Department of ENR/ITI Administrative Boundaries

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    The Canadian National Wetlands Inventory (CNWI) is a comprehensive, publicly available national geodatabase developed by the Canadian Wildlife Service (CWS) of Environment and Climate Change Canada (ECCC), in collaboration with federal, provincial, and territorial governments, academia, Indigenous groups, and Non-Governmental Organizations (NGOs). It consists of the best available wetland mapping data, along with its metadata, published in a standardized manner. The CNWI is continuously updated through the compilation of existing data and the acquisition of new high-resolution datasets to address coverage gaps, with an emphasis on peatlands and coastal wetlands, which are key habitats for greenhouse gas (GHG) sequestration. ECCC plans to use the CNWI to train and validate machine-learning algorithms to delineate and classify wetlands at a national scale and to measure trends over time. This will directly support Canada’s Nature-Based Climate Solutions by informing biodiversity conservation, guiding climate change mitigation and adaptation strategies, and supporting GHG emissions reporting. The CNWI was initially released in February 2024 with 13 source datasets. In June 2025, the Inventory was updated to include 14 additional datasets. Collectively, these 27 source datasets comprise approximately 12.1 million wetland polygon features, covering a total area of roughly 640,000 square kilometers across ten provinces and territories (BC, MB, NB, NL, NS, PE, ON, QC, SK, YT). These source datasets were cross-walked into a standardized CNWI classification schema, which is based on two foundational documents: the Canadian Wetland Classification System (National Wetlands Working Group, 1997) and the Canadian Wetland Inventory Data Model (2016). The CNWI Schema contains five major wetland classes (Bog, Fen, Swamp, Marsh, and Shallow/Open Water) and eight subclasses (Rich Fen, Poor Fen, Organic Swamp, Mineral Swamp, Organic Marsh, Mineral Marsh, Shallow Water, and Open Water). Non-conforming wetlands can be categorized into three groups: Peatland, Mixed, and Unclassified. For more information on the CNWI and the related database, please refer to the CNWI User Manual and other supporting documents that accompany this publication. The User Manual provides detailed information on how data are collected, managed, and distributed to meet CNWI data standards.

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    Prospecting Permits

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    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.

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    Proposed Protected and Conservation Areas in the NWT

  • These shorebird surveys are conducted intermittently at a series of sites near the town of Tofino on the west coast of Vancouver Island, British Columbia, during northward (April to May) and southward migration (July to November). This survey includes all shorebird species. Surveyors used binoculars or a spotting scope to count the total number of shorebirds present within the natural boundaries of each survey site during the northward and/or southward migration periods. They used a boat to count birds within the entire area of Arakun Flats and Ducking Flats by traveling along the outer edge of the mudflats, and by stopping at standardized vantage points on land. They also used a boat to view as much area as possible within Maltby Slough, South Bay and Grice Bay from the openings to each of these bays. Surveyors walked the entire length of Chesterman Beach including the tombolo to Frank Island. Surveys were done at least twice a week at each site. Most boat surveys began at low tide when the mudflats were exposed and continued on the rising tide. Road accessible sites were usually surveyed during the hour before high tide or at high tide in 2011. Surveys were not conducted in weather that reduced visibility or made boat travel unsafe (heavy rain or high wind). Surveyors counted birds individually when they were within flocks of fewer than 200 birds. They estimated the size of larger flocks by counting 50 or 100 birds and then judged how many similar-sized groups made up the entire flock. Distant flocks were recorded as small or large shorebirds and assumed to have the same species composition as those closer to shore in 1995 or identified to species group and recorded as either “dowitchers” or “peeps” in 2011.

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    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).

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    This is a point shape file representing 2 kilometre incremental distances along each of the 8 NWT highways.  These 2km points do not represent the actual location of 2km highway posts found along the sides of the highways.  The feature class points are placed every 2 kilometres along a highway and represent the distance from a fixed commencement point, the beginning of that highway.

  • This entry provides access to the figures and data tables that feature in the CSAS Research Document titled 'Optical, chemical, and biological oceanographic conditions on the Scotian Shelf and in the eastern Gulf of Maine in 2015'. Please consult the meta-data text file that accompanies the zip file download for the figure on the data usage policy and appropriate citation. The meta-data file also provides field descriptors and any other information that may be useful in interpreting the data provided in relation to the accompanying imagery. Abstract: As warm and variable ocean conditions persisted in the Maritimes Region in 2015, there was increasing evidence of a shift in both phytoplankton and zooplankton communities away from the dominance of large phytoplankton and copepods toward smaller phytoplankton and copepod species. Although deep-water nitrate inventories were mainly higher than average in 2015, deep silicate and phosphate inventories were lower than average on the Scotian Shelf for the third year in a row. The spring bloom started later than normal and was weaker in magnitude and shorter in duration than usual. Phytoplankton biomass anomalies were mixed across the Shelf, but the abundance of large phytoplankton, particularly diatoms, was lower than average, continuing a pattern started in 2009. The abundance of the biomass-dominant copepod species Calanus finmarchicus and zooplankton biomass overall were lower than average overall in 2015, as was the abundance of Arctic Calanus species, continuing a pattern started during the last 4-7 years. In contrast, the abundances of offshore copepods were higher than average. Changes in phytoplankton and zooplankton communities observed in recent years indicate poor feeding conditions for planktivorous fish, birds, and mammals. Continuous Plankton Recorder sampling, the reporting of which lags Atlantic Zone Monitoring Program sampling by one year, indicated that in 2014 the spring phytoplankton bloom occurred earlier and was of shorter duration than normal over the entire Scotian Shelf and that the springtime peaks in abundance of the dominant zooplankton taxa Calanus I-IV and C. finmarchicus V-VI were also relatively early and relatively short-lived. 2014 annual abundance anomalies were unusually high for hyperiid amphipods and foraminifera over the entire Scotian Shelf in 2014, and unusually low for euphausiids. Annual abundance anomalies for most other taxa were at near normal levels on the western Scotian Shelf and below normal levels on the eastern Scotian Shelf. http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2017/2017_012-eng.html

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    Mineral Claims