The framework of the Cordilleran orogen of northwestern North America is commonly depicted as a 'collage' of terranes - crustal blocks containing records of a variety of geodynamic environments including continental fragments, pieces of island arc crust and oceanic crust.The series of maps available here are derived from a GIS compilation of terranes based on the map first published by Colpron et al. (2007) and more recently revised by Nelson et al. (2013). These maps are presented here in digital formats including ArcGIS file geodatabase (.gdb), shapefiles (.shp and related files), Google Earth (.kmz), as well as graphic files (.pdf). The GIS data includes terrane polygons and selected major Late Cretaceous and Tertiary strike-slip faults. Graphic PDF files derived from the GIS compilation were prepared for the Northern Cordillera (Alaska, Yukon and BC), the Canadian Cordillera (BC and Yukon), Yukon, and British Columbia. These maps are intended for page-size display (\~1:5,000,000 and smaller). Polygons are accurate to \~1 km for Yukon and BC, \~5 km for Alaska. More detailed geological data are available from both BCGC, USGS and YGS websites. Descriptions of the terranes, their tectonic evolution and metallogeny can be found in Colpron et al. (2007), Nelson and Colpron (2007), Colpron and Nelson (2009), Nelson et al. (2013) and references therein.The terrane map project is a collaborative effort of the BC Geological Survey and the Yukon Geological Survey.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

The framework of the Cordilleran orogen of northwestern North America is commonly depicted as a 'collage' of terranes - crustal blocks containing records of a variety of geodynamic environments including continental fragments, pieces of island arc crust and oceanic crust.The series of maps available here are derived from a GIS compilation of terranes based on the map first published by Colpron et al. (2007) and more recently revised by Nelson et al. (2013). These maps are presented here in digital formats including ArcGIS file geodatabase (.gdb), shapefiles (.shp and related files), Google Earth (.kmz), as well as graphic files (.pdf). The GIS data includes terrane polygons and selected major Late Cretaceous and Tertiary strike-slip faults. Graphic PDF files derived from the GIS compilation were prepared for the Northern Cordillera (Alaska, Yukon and BC), the Canadian Cordillera (BC and Yukon), Yukon, and British Columbia. These maps are intended for page-size display (\~1:5,000,000 and smaller). Polygons are accurate to \~1 km for Yukon and BC, \~5 km for Alaska. More detailed geological data are available from both BCGC, USGS and YGS websites. Descriptions of the terranes, their tectonic evolution and metallogeny can be found in Colpron et al. (2007), Nelson and Colpron (2007), Colpron and Nelson (2009), Nelson et al. (2013) and references therein.The terrane map project is a collaborative effort of the BC Geological Survey and the Yukon Geological Survey.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

The administration of coal projects in the Yukon is governed under the Territorial Lands (Yukon) Act (TLYA) and the Coal Regulations enabled under the TLYA. The land use permits necessary for coal exploration and development are issued by the Energy Mines and Resources Lands Branch under the TLYA. The remaining coal licenses and coal leases are issued and administered by the Mineral Resources Branch Mining Lands offices.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

Annual mapping of national level forest harvesting for Canada detected inclusive of 1985 to 2015 from Landsat satellite imagery.This dataset is composed of two layers: (1) binary harvest mask, and (2) year of harvest disturbance detection. The information outcomes represent 31 years of harvesting activity in Canada’s forests, derived from a single, consistent, spatially-explicit data source in an automated manner. Time series of Landsat data with 30-m spatial resolution were used to characterize national trends in stand replacing forest disturbances, including those attributed to harvest for the period 1985–2015 for Canada's 650 million hectare forested ecosystems (Hermosilla et al. 2016). See references below for an overview regarding the data, image processing, and time-series change detection methods applied, as well as information on independent accuracy assessment of the data. 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. ( Hermosilla et al. 2016) For additional resources on the data used and methods applied, please see: 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., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., 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.( Hermosilla et al. 2017)

The porbeagle shark (Lamna nasus), is a species found in Atlantic Canadian waters which is encountered in commercial and recreational fisheries. Pop-up Satellite Archival Tags (PSAT) from Wildlife Computers were applied to porbeagle sharks from 2005 to 2021 to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada and the Faroe Islands on commercial, recreational and scientific charters, typically in summer and fall but some over winter when the porbeagle commercial fishery was active in Canada. A variety of tag models were deployed: PAT 4 (n=1), Mk10 (N=41), and MiniPAT (N=15) and 51 of 57 tags reported. One individual shark was recaptured and the physical tag was returned. The porbeagle sharks tagged ranged in size from 76 cm to 249 cm Fork Length (curved); 42 were female, 15 were male. Time at liberty ranged from 4 – 356 days and 14 tags remained on for the programmed duration. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

The Rocky Mountains Forest Reserve dataset is comprised of all the polygons that represent Rocky Mountains Forest Reserves in Alberta. The Rocky Mountains Forest Reserve is an area designated through a Legislature Act in 1948 that provides the conservation of the forests and the protection of the watersheds and rivers on the eastern slope of the Rocky Mountains.

PURPOSE:This study is 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 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 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 are monitored to evaluate potential effects of change on fisheries. From 2000 to 2011, surface water temperature data was collected at depths of approximately 0.1 to 1.0 meters using a handheld digital thermometer 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 the beginning in a series of baseline data sets on water quality from this lake. These data will contribute to a better understanding of 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, Sahtú Renewable Resource Board, Great Lakes Fisheries Commission, and University of Alberta. Community of Délı̨nę partners and field workers that participated in data collection include Jane Baptiste, Doug Baton, Moise Beyonnie, Gloria Gaudette, Bruce Kenny, Greg Kenny, Hughie Kenny, Jonas Kenny, Morris Lennie, George Menacho, Morris Modeste, Nathan Modeste, Isreal Neyelle, Lyle Neyelle, Clyde Takazo, Lucy Ann Takazo, Freddie Vital, Cameron Yukon, Cyre Yukon, Tyrone Yukon, Charity Yukon, Chris Yukon, Archie Vital, John Betsidea, and Barbara Yukon.Funding and logistical support was provided by: Northwest Territories Cumulative Impact Monitoring, Sahtú Renewable Resource Board, the Polar Continental Shelf Program, Canadian Circumpolar Institute, Natural Sciences and Engineering Research Council of Canada, Government of Northwest Territories Renewable Resources Délı̨nę, and Fisheries and Oceans Canada.

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%3DihubUncertainties: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).

PURPOSE:The focus of this research is on changes in the distribution of killer whales in the Canadian Arctic, which is within the field of marine biogeography and marine megafauna. Our research details change in killer whale presence and ties it to changes in sea ice coverage. These are novel results, presenting trends in the arrival and departure dates of killer whales into the eastern Canadian Arctic for the first time. We go on to discuss the impacts of these changes on other aspects of Arctic ecosystems and how increasing in killer whale presence might affect other species and the management of those species in Canada. Killer whales are a widespread species of interest, especially in the Canadian Arctic as their presence is tied to multiple aspects of a region rapidly changing from the effects of climate change. DESCRIPTION:This study examines 20 years of killer whale (Orcinus orca) sightings in the eastern Canadian Arctic, drawing from a comprehensive sighting database spanning 1850-2023. Despite inherent biases favoring data collection near communities and coastal areas, spatiotemporal analyses reveal significant shifts in killer whale distribution linked to changing sea ice conditions. We developed a clustering metric representing the mean distance to the five nearest sightings and results show that killer whales are progressively moving away from historically high-use areas and that sighting locations are becoming more dispersed over time. A significant year × sea ice interaction indicates observations occur earlier during their arrival period at lower sea ice concentrations over time, suggesting that declining sea iceconcentration contributes to earlier arrival. Conversely, for departure periods, killer whales are observed farther south later in the year, likely linked to earlier freeze-up at higher latitudes, and are overall observed later into the year over time. This trend has led to a near doubling of their average presence from 26 days in 2002 to 48 days in 2023 (27 July to 13 September) reflecting an extended open-water season. These findings underscore the prolonged seasonal use of Arctic regions by killer whales, driven by diminishing sea ice and expanding openwater habitat. Such shifts highlight potential implications for Arctic marine ecosystems as killer whales increasingly overlap with endemic species.

This record contains data on bowhead whale locations reported in Harwood, L.A. and P. Norton. 1996. Aerial survey data from the southeast Beaufort Sea, Mackenzie River estuary and west. Amundsen Gulf, July 1992. Canadian Data Report of Fisheries and Aquatic Sciences No. 964