The Canada Nature Fund for Aquatic Species at Risk (CNFASAR) is a contribution program that focuses on providing funding for recovery and threat mitigation activities in nine priority places and to address two marine threats to aquatic species at risk. The Priority Places and Marine Threats layer supports CNFASAR by delineating the location of the places and threats.The Canada Nature Fund for Aquatic Species at Risk (CNFASAR) supports applicants in the design and delivery of stewardship projects. These projects support the recovery and protection of aquatic species at risk. DFO has identified 2 priority marine threats and 9 priority places as the focus for projects funded by CNFASAR, these areas are included in this dataset.

644 datasets of Typical Meteorological Years (TMY) created by joining twelve Typical Meteorological Months selected from a database of up to 20 years of CWEEDS hourly data. The months are chosen by statistically comparing individual monthly means with long-term monthly means for daily total global solar irradiance, mean, minimum and maximum dry bulb temperature, mean, minimum and maximum dew point temperature, and mean and maximum wind speed. These hourly datasets are used by the engineering and scientific community mainly as inputs for solar system design and analysis and building energy systems analysis tools. This dataset has been updated with the most recent changes made in March 2023. The solar values in these files are based on 0.1° x 0.1° (11 km x 11 km grid) for all of Canada. Refer to Data Resources below for additional information on the TMY file format.

**ATTENTION! The files in this dataset are designed for streaming, not downloading. For the best experience, please follow the instructions available in the resources.**In replacement of the former Canadian Digital Elevation Model (CDEM) that is no longer supported, the Medium Resolution Digital Elevation Model (MRDEM) product is a multi-source product that integrates elevation data from the Copernicus DEM** acquired during the TanDEM-X Mission (AIRBUS, 2022), and the High Resolution Digital Elevation Model data derived from airborne lidar. This product provides a complete, 30 meters resolution, nationwide coverage for Canada. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived products. The spatial coverage extends into the USA, where needed, to provide coverage for cross-border watersheds in support of hydrological studies and applications. The MRDEM-30-DSM is partially based on the GLO-30 version of the Copernicus DEM** (hereafter named GLO-30). Since elevation values from the GLO-30 are referenced to the EGM2008 geoid model, they were transformed to the Canadian Height Reference System of 2013 (CGVD2013), using the CGG2013 geoid model. Where available, the MRDEM-30-DSM integrates surface data from the lidar-derived HRDEM mosaic, resampled from 1 m to 30 m. The process to generate the MRDEM-30-DTM is more complex. Where available, the HRDEM Mosaic derived from lidar was used since it already provides reliable terrain elevation values. The HRDEM Mosaic data used was resampled from 1m to 30m. Elsewhere, the processing workflow combines a forest removal model and a settlement removal model that is applied to the GLO-30 values in order to estimate the terrain elevation values. Both datasets are projected to Canada Atlas Lambert NAD83 (CSRS) (EPSG:3979).The MRDEM is referenced to the CGVD2013 which is the reference standard for orthometric heights across Canada.The product Medium Resolution Digital Elevation Model (MRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan.** This product was in part produced using Copernicus WorldDEM-30 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014- 2018 provided under COPERNICUS by the European Union and ESA; all rights reserved.The organisations in charge of the Copernicus program by law or by delegation do not incur any liability for any use of the Copernicus WorldDEM-30.

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 counts of the population in nursing homes and/or residences for senior citizens by broad age groups (0 to 79 years and 80 years and over) and sex, from the 2016 Census.Nursing homes and/or residences for senior citizens are facilities for elderly residents that provide accommodations with health care services or personal support or assisted living care.Health care services include professional health monitoring and skilled nursing care and supervision 24 hours a day, 7 days a week, for people who are not independent in most activities of daily living.Support or assisted living care services include meals, housekeeping, laundry, medication supervision, assistance in bathing or dressing, etc., for people who are independent in most activities of daily living.Included are nursing homes, residences for senior citizens, and facilities that are a mix of both a nursing home and a residence for senior citizens.Excluded are facilities licensed as hospitals, and facilities that do not provide any services (which are considered private dwellings).

Each pixel value corresponds to the difference (anomaly) between the mean “Best-Quality” Max-NDVI of the week specified (e.g. Week 18, 2000-2014) and the “Best-Quality” Max-NDVI of the same week in a specific year (e.g. Week 18, 2015). Max-NDVI anomalies < 0 indicate where weekly Max-NDVI is lower than normal. Anomalies > 0 indicate where weekly Max-NDVI is higher than normal. Anomalies close to 0 indicate where weekly Max-NDVI is similar to normal.

A systematic oceanographic monitoring program was initiated in September 1989 at twenty-five monitoring stations in the Passamaquoddy Bay area and approaches by Dr. Shawn Robinson based out of the St. Andrews Biological Station (SABS). Stations were established in a uniform grid pattern of two arcminutes latitude and longitude over the study area in order to develop a database on the spatial patterns of water properties. Monthly measurements of the water column for the temperatures and salinity at all stations was completed using a Seacat SBE 19 internally recording CTD from Sea-bird Electronics Inc. The CTD was programmed to record conductivity, temperature, and depth at a frequency of 2 hz, corresponding to 2 measurements per meter of water depth. CTD casts were recorded for each of the 25 stations in the study area monthly using the R/V Pandalus, and later the CCGS Viola M. Davidson based out of SABS. The CTD was configured such that the sensors were oriented towards the benthos and the CTD was then attached to a hydraulic winch on the deck of the ship by a stainless steel cable one meter above a weight, and lowered 1 m below the water's surface in order for the CTD to equilibrate for one minute. The CTD was then lowered at 1 m/s to the benthos using a metered block on the winch to determine when the CTD had reached the maximum depth at that station. Once the weight had touched the bottom, the CTD was retrieved from the water, turned off, and placed in a bucket of fresh seawater in order to minimize equilibration time at the next station. Initially, the CTD measured salinity via water forced through the salinity cell with the drop rate of 1 m/s, but in August 1992, a pump was mounted on the CTD in order to provide a more consistent flow of water across the salinity cell. Surface temperatures were measured from bucket samples collected upon arriving at each station using a hand-held mercury thermometer at each station, and Secchi disk measurements were recorded. All data were downloaded from the CTD upon return to SABS using a DFO computer and the proprietary Sea-Soft software. Downcast data from each profile was retained, binned into 1 m intervals, and processed to remove data spikes, density inversions, and anomalies due to inadequate instrument equilibration. Processed data was then stored in the DFO's Oracle database (PTRAN) under the IMTA_SABS schema in the INVHYD and INVINF tables. Station numbers and locations are recorded in the CTD_STATIONS table in the IMTA_SABS schema.Cite this data: Robinson, S. Data of: Passamaquoddy Bay monthly Conductivity Temperature and Depth (CTD) sampling (1989 - 2018). Published: October 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, NB. https://open.canada.ca/data/en/dataset/12184962-7879-4214-aef0-b31162f04a27

Medical institutions in BC that provide diagnostic and treatment services for people whose illnesses or injuries require that they occupy a bed for at least one night. Hospitals can be distinguished by the level of care they offer (general acute, subacute, extended acute care) and the medical conditions in which they may specialize (specialty hospitals). Definition is protected by Copyright by Information and Referral Federal of Los Angeles County, Inc. See link: (https://211taxonomy.org/subscriptions/#agreement)

Hospitals and other health care facilities in BC that provide 24-hour diagnostic and treatment services for people who have acute, life-threatening injuries or severe illnesses. Definition is protected by Copyright by Information and Referral Federal of Los Angeles County, Inc (https://211taxonomy.org/subscriptions/#agreement)

A National Forest Fire Behaviour Prediction (FBP) Fuel Type (FT) layer, representing fuel types as described in the Canadian Forest Fire Danger Rating System (CFFDRS) Canada-wide. This data is developed through the Spatialized Canadian National Forest Inventory (SCANFI) dataset, specifically the updated SCANFI version 2.0. The Fuel Type layer is produced at variable resolution to best meet the needs of users: 30m (default) and 100m (ideal for fire growth modelling).The purpose of this dataset is to characterize Canadian forests into Fuel Types for use in various applications, including wildland fire management, research, fuel management, and more. This layer is primarily developed to support national scale applications and uses but can be utilized for localized landbases and adapted as required.This data represents the most up-to-date national product and is updated annually prior to the start of the fire season to incorporate burned area and additional data from the previous year. This data will be updated annually and published online by April 30th of each year.Note: In this product Slash fuel types (S-1, S-2, and S-3) are not represented. Conifer Plantation (C-6) is not represented. Raster Grid Value 13 represents vegetated fuels without an effective match to an existing FBP Fuel Type under this ruleset. Grid Value 11 (corresponding to D-1 Leafless Aspen) is assumed to represent true Deciduous fuels as described in the FBP system.

A federal electoral district is an area represented by a member of the House of Commons. The Federal Electoral Districts (FED) dataset is a digital representation of the 338 electoral districts proclaimed by the Representation Order of 2013. This dataset is an update of the 2013 Federal Electoral Districts (FED) 2013.