Assessment Watersheds are mesoscale aquatic units designed to replace the 3rd order 1:50K watersheds. Assessment Watersheds are based on groupings of fundamental watersheds using FWA watershed code and local code, with a target size of between 2,000ha and 10,000ha.

Canada's National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 106 km2 of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data. We used the k nearest neighbours (kNN) method with 26 geospatial data layers including MODIS spectral data and climatic and topographic variables to produce maps of 127 forest attributes at a 250 × 250 m resolution. The stand-level attributes include land cover, structure, and tree species relative abundance. In this article, we report only on total live aboveground tree biomass, with all other attributes covered in the supplementary data (http://nrcresearchpress.com/doi/suppl/10.1139/cjfr-2013-0401). In general, deviations in predicted pixel-level values from those in a PP validation set are greater in mountainous regions and in areas with either low biomass or sparse PP sampling. Predicted pixel-level values are overestimated at small observed values and underestimated at large ones. Accuracy measures are improved through the spatial aggregation of pixels to 1 km2 and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org) Collection: - **[Canada's National Forest Inventory (NFI) 2006](https://open.canada.ca/data/en/dataset/e2fadaeb-3106-4111-9d1c-f9791d83fbf4)**

The purpose of this dataset is to depict the boundaries of the Niagara Escarpment Plan. The outer boundary of the area covered by the Niagara Escarpment Plan is fixed and inflexible. It can only be changed by a plan amendment. It is formed by a combination of features like: * roads * railways * electrical transmission lines * municipal and property boundaries * lot lines * rivers * other topographic features [More information](http://www.escarpment.org)

In September 1732 a damaging earthquake occurred immediately beneath the Island of Montréal. This scenario visualizes the effects of that event if it occurred today with a magnitude of 5.0, and represents a strong ground shaking event that could strike Montréal.

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in sea ice thickness, based on an ensemble of twenty-six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Projected change in sea ice thickness is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensemble of sea ice thickness change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in sea ice thickness (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

Quad biking trails in Saguenay**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The Blended Index (BI) is a model which employs multiple potential indicators of drought and excess moisture, such as the Palmer drought index, rolling precipitation amounts and soil moisture, and combines them into a weighted, normalized value between 0 and 100. The inputs and weights used in this model are subject to change periodically as it is optimized to best represent extent, duration and severity of impactful weather conditions. The blended index is deployed as two variations; short term (st) focusing on 1 to 3 months, and long term (lt) focusing on 6 months to 5 years.

The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. These indicators track human-related emissions to air of 3 substances (mercury, lead and cadmium) and facility-based emissions to air of 1 substance (arsenic). The 4 substances are defined as toxic under the Canadian Environmental Protection Act, 1999. For each substance, data are provided at the national, regional (provincial and territorial) and facility level, and by source. Global emissions data are also provided for mercury. The indicators inform Canadians about emissions of mercury, lead and cadmium to air from human activity and emissions of arsenic from facility-based reporting in Canada. These indicators also help the government to identify priorities and develop or revise strategies to inform further risk management and to track progress on policies put in place to reduce or control these 4 substances and air pollution in general. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated. Canadian Environmental Sustainability Indicators: https://www.canada.ca/environmental-indicators

“Gros Morne National Park - Total Ecosystem Forest Carbon Density” is the annual carbon density (tonnes carbon per hectare) within Gros Morne’s forested ecosystems over a 31-year period from 1990 to 2020. Total Ecosystem Forest Carbon Density includes aboveground and belowground biomass, soil carbon, and dead organic matter. Total Ecosystem Forest Carbon Density was estimated for 31 national parks using the Generic Carbon Budget Model (GCBM), a spatially explicit carbon budget model developed by Canadian Forest Service which uses forest inventory, disturbance, and mean annual temperature data along with yield data to estimate growth and merchantable volume for dominant tree species. Species- and Ecozone-specific equations are then used to convert merchantable volume to aboveground and belowground biomass carbon. Ecozones were classified according to Canada Ecological Land Classification Level 1. The GCBM simulates carbon dynamics to produce spatially explicit estimations of carbon stocks and fluxes. The model simulates and tracks carbon stocks, transfers between Intergovernmental Panel on Climate Change-defined pools, and other metrics including net ecosystem production, net biome production, and emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in annual time steps. The stocks and fluxes are also tracked by disturbance event (e.g., forest fires, insect outbreaks). Total Ecosystem Forest Carbon Density accounts for the effects of natural and anthropogenic disturbances, including wildfires, prescribed burns, and insect outbreaks. These products have a spatial resolution of 30m. This information is part of the Parks Canada Carbon Atlas Series. To obtain a copy of this report, please contact changementclimatique-climatechange@pc.gc.ca. When using this data, please cite as follows: Sharma, T., Kurz, W.A., Fellows, M., MacDonald, A.L., Richards, J., Chisholm, C., Seutin, G., Richardson, K., Keenleyside, K. (2023). Parks Canada Carbon Atlas Series: Carbon Dynamics in the Forests of Canada’s National Parks. Scientific Report. Parks Canada Agency, Gatineau, QC, Canada, 104 p.

This dataset identifies potential low head hydropower development sites across Canada, based on a comprehensive review of existing studies and resource databases. Low head hydropower refers to sites where the vertical drop (head) is 15 meters or less. Sites included in this dataset also have an estimated generation capacity of 50 megawatts (MW) or less. The original database was developed by Hatch Ltd. for Natural Resources Canada (NRCan) as part of a national low head hydropower market assessment. It integrates data from multiple sources, including provincial inventories, prior Hatch studies, and legacy fieldwork records. To enhance data completeness, NRCan subsequently revised the database by supplementing missing site names, river names, and geographic coordinates where possible. The finalized dataset comprises 2,629 potential low head hydropower sites distributed across Canada. It is provided in the form of provincial and territorial shapefiles, each containing detailed site-level attributes. Attributes include site name, river name, site ID, source of information, local map number, geographic coordinates (X and Y), site region, presence of a dam, grid connection status, Indigenous affiliation, catchment area, mean annual flow, rated discharge, gross head, penstock length and diameter, estimated installed capacity, dedicated transmission line length, site comments, and Indigenous reserve name. Disclaimer: This dataset was developed to support preliminary assessments of low head hydropower potential in Canada and is subject to the following limitations: • The original database was compiled from various secondary sources, including data provided by third-party contributors and Hatch Ltd.’s own records. Some of these sources date back several decades. The data provided has not necessarily undergone independent verification for its accuracy, completeness, or validity. • NRCan undertook a data revision process involving manual review and geolocation using publicly available mapping tools (e.g., Google Maps) to address missing information. Where geographic coordinates could not be reliably determined, this is explicitly indicated in the dataset. • Site conditions may have changed over time due to natural processes or human activities. NRCan does not accept responsibility for any impact such changes may have on the accuracy or validity of the dataset’s observations, conclusions, or recommendations. • The inclusion of a site in this dataset does not imply technical, economic, or environmental feasibility. Any potential development would require further investigation, including detailed field studies, environmental assessments, and comprehensive technical and financial evaluations. This dataset is provided for informational purposes only and is not intended to serve as the sole basis for investment, planning, or development decisions. Users are strongly advised to undertake independent due diligence, including site-specific assessments and technical evaluations, prior to making any decisions based on the dataset. By accessing or using this dataset, users acknowledge and accept these terms and limitations. The dataset providers expressly disclaim any responsibility or liability for consequences resulting from the use, interpretation, or reliance on the information contained herein. Use of this dataset is entirely at the user’s own risk, and users assume full responsibility for any actions or decisions made based on its contents. This disclaimer is provided in accordance with applicable laws and regulations. By utilizing the dataset, users agree to release the dataset providers from any legal claims, damages, or liabilities that may arise from such use.