This dataset includes statistics by: * year * age * language * parental language * gender * geography * household type * family type All counts are rounded to a base of five.

Boundaries identifying similar behavioural ecotypes and sub-populations of Grizzly bears. This dataset contains versions from multiple years. From 2018 on, NatureServe conservation concern ranking categories (e.g., Very Low, Low, Moderate, High, Extreme Concern) supersede the pre-2018 population status categories (e.g., Viable, Threatened, Extirpated) contained in the field STATUS. NatureServe conservation concern ranking categories reflect population size and trend, genetic and demographic isolation, as well as threats to bears and their habitats. The NatureServe conservation concern ranking fields are named CONSERVATION_CONCERN_RANK and CONSERVATION_CONCERN_DESC. Please view the attached PDF file for a summary of changes to this dataset from 2012 onward. To download only the 2018 units, in the link below, select the "Export" tab, then select the "Provincial Layer Download" button: https://maps.gov.bc.ca/ess/hm/imap4m/?catalogLayers=7744,7745 Grizzly Bear Conservation Ranking results table is available here: https://catalogue.data.gov.bc.ca/dataset/e08876a1-3f9c-46bf-b69a-3d88de1da725 Grizzly Bear population estimates from various years are available here: https://catalogue.data.gov.bc.ca/dataset/2bf91935-9158-4f77-9c2c-4310480e6c29 Grizzly Bear reports are available here: https://www2.gov.bc.ca/gov/content/environment/plants-animals-ecosystems/wildlife/wildlife-conservation/grizzly-bear

This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census division. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

Map of the number of individuals in official language minority communities (according to first official language spoken, adjusted responses) by economic region. Multiple responses distributed equally among respondents. Data from 2016 Census of Canada, 100% sample.

PURPOSE:As a part of a two-decade series of research, this study aims to provide a comprehensive synthesis of the effects of harvest and environmental change on fisheries in Great Bear Lake. The main objectives are to assess demographic traits and the current status of harvested species, with a focus on evaluating sustainable harvest levels of lake trout, a cold-adapted species with a relatively narrow thermal niche. As part of this research, trends in water quality and primary productivity are monitored to evaluate potential effects of change on fisheries. DESCRIPTION:Great Bear Lake, one of the largest lakes in North America, contains culturally and recreationally important fish species. Great Bear Lake is located in the sub-Arctic and Arctic Circle. As part of a two-decade series of research aimed to provide a comprehensive synthesis of the effects of harvest and environmental change on fisheries in Great Bear Lake, the main objectives of this study are to assess demographic traits and the current status of harvested species, with a focus on evaluating sustainable harvest levels of lake trout, a cold-adapted species with a relatively narrow thermal niche. As part of this research, trends in water quality and primary productivity are monitored to evaluate potential effects of change on fisheries. From 2012 to 2019, surface water temperature data was collected at depths of 0.1 to 1.0 meters using a Hydrolab Series 5 Data Sonde Multiparameter instrument through partnered community-led and community/Fisheries and Oceans Canada/university partners collaborative sampling. The project has strong community involvement, including youth through the Guardian Program, to facilitate capacity building and community leadership in the long-term monitoring of Great Bear Lake fisheries and the aquatic ecosystem. This data is an extension of baseline data sets on water quality on the lake. These data will contribute to a better understanding cumulative impacts of climate change on the functioning of large northern lake ecosystems and provide a benchmark for monitoring further change. This data will be important for developing effective strategies for maintaining community-led aquatic monitoring and managing natural resources, particularly fish, which are expected to be increasingly important to communities with declines in other country foods such as caribou. We acknowledge the data were collected in the Sahtú Settlement Area and are made publicly available with the agreement of the Délı̨nę Renewable Resources Council (Délı̨nę Ɂehdzo Got’ı̨nę (Renewable Resources Council)).Collaborators include: the Community of Délı̨nę partners (data collection), Délı̨nę Renewable Resource Council, University of Manitoba, University of Queens, University of British Columbia, University of Alberta, Environment and Climate Change Canada, and Great Lakes Fisheries Commission, Sahtú Renewable Resource Board. Community of Délı̨nę partners and field workers that participated in data collection include Daniel Baton, Morris Betsidea, Joey Dillion, Jade English, Stanley Ferdanan, Bruce Kenny, Elaine Kenny, Darren Kenny, Greg Kenny, Joseph Kenny, Rocky Kenny, Ted Mackienzo, George Menacho, Bobby Modeste, Gina Nyelle, Brent Taniton, Allison Tatti, Gerald Tutcho, Archie Vital, Barbara Yukon, Caroline Yukon, Chris Yukon, and Cyre Yukon.Funding and logistical support was provided by: Northwest Territories Cumulative Impact Monitoring, Natural Sciences and Engineering Research Council of Canada, Environment and Climate Change Canada, Sahtú Renewable Resource Board, the Polar Continental Shelf Program, and Fisheries and Oceans Canada.

Statistics Canada, in collaboration with the Public Health Agency of Canada and Natural Resources Canada, is presenting selected Census data to help inform Canadians on the public health risk of the COVID-19 pandemic and to be used for modelling analysis.The data provided here show the population counts and percentage distribution for various geographic levels by broad age groups, males, females and both sexes, from the 2016 Census.

A vector representation of stream networks is a crucial dataset for the modelling the surface water and groundwater components of the hydrologic cycle. For many usages a crucial attribute of the drainage network is a digital topology and hierarchal stream order attribute (e.g., Strahler stream order). In Canada jurisdictional stream networks are available for the provinces and territories and nationally for Canada in the National Hydrological Network (NHN) dataset. Unfortunately, the NHN data lacks the same topological and attribute information that is available for numerous provinces due to standardization for the entire country. For Canada1Water it was also necessary to have a harmonized dataset with the United States, for both the southern transboundary watersheds and the Alaskan watersheds. This report documents the processes completed to upgrade the topological and graph network support for NHN and provide continuous connectivity with US datasets. It also highlights and corrects a number of stream density and stream order issues that occur within Canada across provincial and territorial borders and NTS tiles. All vector processing was completed in RivEX software extension for ArcMap. Following complete topological correction stream classification was assigned and a table of the node graph network developed. Additional work was then completed to normalize stream density particularly amongst low-order streams between British Columbia and the Yukon and amongst local NTS tiles in Quebec and Ontario. Corrected NHN Strahler stream order assignment was validated against a number of provincial and watershed datasets, all of which already have Strahler stream order attributed. These datasets are the same underlying digitized vector data, so there are no differences in node or polyline positions. Strahler stream order assignment validation was only done by visual comparison as due to differences in vector segments a statistical comparison is complicated. The transboundary integrated C1W stream network with complete classification provides a seamless national dataset to support transdisciplinary studies (fisheries, wildlife, health, pesticide and nutrient issues, mining impact, ecosystem restoration, numeric modelling) that involve a knowledge of stream distribution and ranking.

The bedrock geologic units designate units of the same types of rock which composed the solid rock exposed at ground surface (as outcrop) or which underlies unconsolidated surficial sediments. This dataset represents a general description of the stratigraphy and geology, including geologic unit thickness, morphology, age and rank. It features a list of the geologic unit names and types of rock (lithology) in the hydrogeological unit, from a controlled vocabulary. While the preferred format to deliver this data is by using a shapefile and its linked attributes, this dataset can be delivered also by providing link to external data which should have at least the same properties or also by joining a georeferenced image of the map.

This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census subdivision. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.

This dataset comprises all of the feature classes in the Alberta Provincial Electoral Divisions profiles. This data is derived from the Census of Canada and the National Household Survey from Statistics Canada from 2011 and 2016. This does not constitute an endorsement by Statistics Canada of this product.