PURPOSE:Understanding and predicting species range shifts is crucial for conservation amid global warming. This study analyzes life-history traits of four seal species (ringed (Pusa hispida Schreber, 1775), bearded (Erignathus barbatus Pallas, 1811), harp (Pagophilus groenlandicus Erxleben, 1777), and harbour (Phoca vitulina Linnaeus, 1758) seals) in the Canadian Arctic using data from Inuit subsistence harvests. Bearded seals are largest, followed by harp seals, harbour seals, and ringed seals. Seasonal blubber depth patterns show minimal variation in bearded seals, whereas harbour and ringed seals accumulate fat in open-water seasons and use it during ice-covered seasons. Endemic Arctic seals (ringed and bearded) exhibit greater longevity and determinate body growth, reaching maximum size by 5 years, while harbour and harp seals grow indeterminately, physically maturing around 10-15 years. Age of maturation varies, with ringed and harbour seals being more sensitive to environmental fluctuations. Most bearded seals reproduce successfully each year, while ringed seals exhibit more variability in their annual reproductive success. Analysis of isoprenoid lipids in liver tissue indicates that ringed and bearded seals rely on ice-algal production, whereas harp and harbour seals depend on open-water phytoplankton production. Bearded seals appear more specialized and potentially face less competition, while harp seals may adapt better to changing habitats. Despite expected range shifts to higher latitudes, all species exhibit tradeoffs, complicating predictions for the evolving Arctic environment. DESCRIPTION:This dataset contains the data reported in Steven H. Ferguson, Jeff W. Higdon, Brent G. Young, Stephen D. Petersen, Cody G. Carlyle, Ellen V. Lea, Caroline C. Sauvé, Doreen Kohlbach, Aaron T. Fisk, Gregory W. Thiemann, Katie R. N. Florko, Derek C. G. Muir, Charmain D. Hamilton, Magali Houde, Enooyaq Sudlovenick, and David J. Yurkowski. 2024. A comparative analysis of life-history features and adaptive strategies of Arctic and subarctic seal species - who will win the climate change challenge? Canadian Journal of Zoology 2024-0093.R1The data set includes species, location, harvest date, sex, age, standard length, girth, fat depth, teste size, parity status, pregnancy status, corpora lutea (n), corpus albicans (n), follicles (n). This dataset includes raw, unfiltered, and unprocessed historical data provided by harvesters that have not been screened for outliers. Individual users should screen the data for their specific use.Cite these data as:Steven H. Ferguson, Jeff W. Higdon, Brent G. Young, Stephen D. Petersen, Cody G. Carlyle, Ellen V. Lea, Caroline C. Sauvé, Doreen Kohlbach, Aaron T. Fisk, Gregory W. Thiemann, Katie R. N. Florko, Derek C. G. Muir, Charmain D. Hamilton, Magali Houde, Enooyaq Sudlovenick, and David J. Yurkowski. 2024. Arctic and Aquatic Research Division, Fisheries and Oceans Canada, Winnipeg, MB. https://open.canada.ca/data/en/dataset/ea9ff038-8b16-11ef-8cce-55cc7f028297

The wind power density layer shows the modeled wind power density [W/m2] at a height of 100 m above ground level, at each grid point, averaged over the three year period from January 1, 2008 to December 31, 2010. Values are presented in bins with ranges of 0.5 W/m2 each. Further details including data at different heights, and for individual years, can be obtained by clicking on the dot representing the grid point location.

This dataset contains the data reported in Wesley R Ogloff, Randi A Anderson, David J Yurkowski, Cassandra D Debets, W Gary Anderson, Steven H Ferguson, Spatiotemporal variation of ringed seal blubber cortisol levels in the Canadian Arctic, Journal of Mammalogy, 2022;, gyac047, https://doi.org/10.1093/jmammal/gyac047Cite this data as:Wesley R Ogloff, Randi A Anderson, David J Yurkowski, Cassandra D Debets, W Gary Anderson, Steven H Ferguson. 2022 Spatiotemporal variation of ringed seal blubber cortisol levels in the Canadian Arctic. Arctic and Aquatic Research Division, Fisheries and Oceans Canada, Winnipeg, MB. https://open.canada.ca/data/en/dataset/e1c6b350-0159-11ed-8212-1860247f53e3

Facilities designed to recover natural gas liquids from a stream of natural gas. These facilities control the quality of the natural gas to be marketed.Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.Parent Collection:[North American Cooperation on Energy Information, Mapping Data](https://open.canada.ca/data/en/dataset/aae6619f-f9f3-435d-bc32-42decd58b674)

This model is derived from geological and geophysical data, which is processed using deep learning and natural language processing techniques. Displayed is a Pan-Canadian probability map indicating the likelihood of discovering next-generation lithium-cesium-tantalum (LCT) pegmatites. This map was generated using known Canadian LCT pegmatites and their associated geospatial features, incorporating geological and geophysical data analyzed through deep learning and natural language processing techniques. Higher probability values highlight areas with an increased likelihood of hosting next-generation deposits, making this map a valuable tool for decision-making.

This dataset provides the background radiation dose results from Health Canada’s Canadian Radiological Monitoring Network (CRMN) monitoring sites. More information about the CRMN network can be found on the Health Canada website (see link below).This background radiation data contains both “monitoring” and “transit” dosimeters starting in 2016. The historical background radiation dose data can be found on the Open Data portal. A transit dosimeter is sent along with the monitoring dosimeter to determine if there is a significant dose recorded by the dosimeter while it is in transit to the sampling station. The transit dosimeter is shipped out with a station monitor, and shipped back with the station monitor from the previous quarter. The monitoring dosimeters are deployed over a longer time (around three months) than the transit dosimeters (around 3 weeks). This difference largely explains the lower recorded dose values for the transit dosimeter. The results provided for the monitoring and transit dosimeters are expressed as ambient dose equivalent to a cesium source, in units of millisieverts (mSv). The measured dose rate is reported in mSv/day. The external dose can be attributed almost exclusively to natural radiation (of terrestrial and cosmic origin) with fluctuations based on several factors including location, soil characteristics, and seasonal changes. The map shows the approximate sampling location for each monitoring station. Stations are found within the associated location range.

Harvest changes occurred from 1985 to 2022 displaying the year of greatest harvest disturbance. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The information outcomes represent 38 years of harvest activity in Canada's forests, derived from a single, consistent, spatially explicit data source in a fully automated manner. Time series of Landsat data with 30 m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by harvest for the period 1985-2022 for Canada's 650-million-hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. https://doi.org/10.1080/17538947.2016.1187673 ( Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution, and time series change detection methods applied, as well as information on independent accuracy assessment of the data.Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., (2015). An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. ( Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., (2015). Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. ( Hermosilla et al. 2015b).Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G. W. Hobart, (2017). Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation. 63,104-111. https://doi.org/10.1016/j.jag.2017.07.013 (Hermosilla et al. 2017)

A research survey on the common whelk (Buccinum undatum) has been conducted biennially in three sectors of the St. Lawrence Estuary since 2005 to assess the abundance of whelk and benthic species associated with whelk habitat. Only data for benthic species associated with whelk habitat are presented in this dataset. The survey was initiated in 2005 following the intensive fishery of the early 2000s in the Upper North Shore region. The three sectors covered by the survey were based on the distribution of commercial fishing effort from 2001 to 2004.Surveys were conducted between mid-July and early August from 2005 to 2019 on the North Shore of the St. Lawrence Estuary between Portneuf-sur-Mer and Baie-Comeau according to a fixed station sampling design. Three sectors were surveyed at each survey: Forestville (69°03'11"W-48°39'24"N and 68°56'02"W-48°46'16"N), Pointe-aux-Outardes (68°35'53"W-48°59'32"N and 68°25'30"W-49°01'06"N) and Baie-Comeau (68°06'04"W-49°08'40"N and 68°05'10"W-49°12'26"N). Since 2007, the sampling plan consists of 55 stations in Forestville, 26 stations in Pointe-aux-Outardes and 11 stations in Baie-Comeau. The targeted depth interval at the three sectors was approximately 5 to 40 m. Specimens were collected using a Digby-type scallop dredge with a total width of 3.04 m consisting of four 19 mm mesh Vexar™ lined baskets to harvest small individuals. Start and end positions were recorded to calculate the distance traveled at each tow using the geosphere library in R. Since 2011, the average tow distance was approximately 300 m. The area covered at each tow was the product of the dredge width and distance.The three files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event_information" file includes generic event information, including date and location. The "additional_information_event_and_occurrence" file includes sample size, sampling protocol and sampling effort, among others. The "taxon_occurrence" file includes the taxonomy of the species observed, identified to the species or lowest possible taxonomic level. For abundance and biomass estimates, contact Virginie Roy (virginie.roy@dfo-mpo.gc.ca).For quality controls, all taxonomic names were checked against the World Register of Marine Species (WoRMS) to match recognized standards. The WoRMS match was placed in the "scientificNameID" field of the occurrence file. Special cases were noted in "identificationRemarks" and selected specimens were confirmed using field photos. Data quality checks were performed using the R obistools and worrms libraries. All sampling locations were spatially validated.

Wildfire change year 1985-2022.Wildfire changes occurred from 1985 to 2022 displaying the year of greatest wildfire disturbance. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The information outcomes represent 38 years of wildfires in Canada's forests, derived from a single, consistent, spatially explicit data source in a fully automated manner. Time series of Landsat data with 30 m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by wildfire for the period 1985-2022 for Canada's 650-million-hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. https://doi.org/10.1080/17538947.2016.1187673 (Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution, and time series change detection methods applied, as well as information on independent accuracy assessment of the data..Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., (2015). An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. https://doi.org/10.1016/j.rse.2014.11.005 (Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., (2015). Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. https://doi.org/10.1016/j.rse.2015.09.004 (Hermosilla et al. 2015b).Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G. W. Hobart, (2017). Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation. 63,104-111. https://doi.org/10.1016/j.jag.2017.07.013 (Hermosilla et al. 2017).

Natural gas onshore facilities used to receive, unload, load, store, gasify, liquefy, process and transport by ship, natural gas that is imported from a foreign country, exported to a foreign country, or interior commerce.Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.