The raster maps depict a suite of forest attributes in 2001* and 2011 at 250 m by 250 m spatial resolution. The maps were produced using the k nearest neighbours method applied to MODIS imagery and trained from National Forest Inventory photo plot data. For detailed information about map production methods please refer to Beaudoin et al. (2018) "Tracking forest attributes across Canada between 2001 and 2011 using the k nearest neighbours mapping approach applied to MODIS imagery." Canadian Journal of Forest Research 48, 85-93. https://cfs.nrcan.gc.ca/publications?id=38979 The map datasets may be downloaded from https://nfi.nfis.org/downloads/nfi_knn2011.zip or https://open.canada.ca/data/en/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 * Note: the forest composition (leading tree genus) map depicts forest attributes in 2001.How can this data be used?The resolution and accuracy of these map products are best suited for strategic-level forest reporting and informing policy and decision making at regional to national scales. As these maps also offer a coherent set of quantitative values for a large suite of forest attributes, they can be used as baseline information for modelling and in calculations such as merchantable forest volume or percentage of tree species. It is also possible to overlay these maps with other maps produced on the same pixel grid to make assessments of disturbance impacts, such as fire and harvests.

A benthic imagery survey was conducted along the Eastern Scotian Slope in June 2018 to collect data in support of a Strategic Program for Ecosystem-Based Research and Advice project to evaluate the effectiveness of the Lophelia Coral Conservation Area and identify new areas of importance for benthic species that may qualify for protection under Fisheries and Oceans Canada’s 2009 Policy for Managing the Impact of Fishing on Sensitive Benthic Areas. Linear video and photographic transects from ~200 to 1000 m depth were collected at 10 stations between the Gully Marine Protected Area and the Lophelia Coral Conservation Area using the video and photographic camera system Campod and the ‘4K Camera’ drop camera system. Here we present a quantitative assessment of the corals and sponges observed at each of these 10 stations. Patterns in distribution by transect and depth are presented, as well as the relationship between coral distribution and groundfish fishing effort. We highlight the importance of the slope outside the canyons for the distribution of corals and sponges, where nearly 25 taxa were recorded between 167 – 970 m depth. Diversity and abundance appeared to show a west-to-east gradient across the study area, being highest on those stations adjacent to the Lophelia Coral Conservation Area. Groundfish fishing activity overlapped the distribution of corals and sponges in some parts of the study area, particularly between 200 and 500 m where the large branching corals Paragorgia arborea and Primnoa resedaeformis were observed, and also suggested that fishing may have taken place within the boundaries of the Lophelia Coral Conservation Area since its implementation in 2004. An extension of the boundaries of this closure may ensure its continued effectiveness and provide protection for the diverse and abundant coral and sponge communities that reside beyond its boundaries.Cite this data as: Beazley, Lindsay; Lirette, Camille; Guijarro, Javier (2019). Characterization of the Corals and Sponges of the Eastern Scotian Slope from a Benthic Imagery Survey. Published July 2023. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b6567b77-4fda-4fcf-b059-fcfeb4dcc2fb

Broad Ecosystem Units were mapped using predictive modeling methods from various data sources (ranging from 1:50,000 to 1:250,000 in scale) and are referenced to the CanVec digital spatial framework (1:50,000). Broad Ecosystem Units (BEU) are a level in the Yukon bioclimate ecosystem classification system that represents areas with similar broad vegetation communities, terrain type (soils and topography) within bioclimate zones. Broad Ecosystem Units are described in the accompanying report "Regional Ecosystems of West-Central Yukon, Part 1: Ecosystem descriptions ".The intended application for mapped broad ecosystem units is 1:100,000 or smaller (1:100,000 - 1:250,000 scale) - interpretations derived from the map products should not be applied at more detailed scales, even though the resultant 30m raster map allows users to view results at more detailed resolutions. With new information, boundaries and designations of Broad Ecosystem Units can change. Updates to Broad Ecosystem Units occur only periodically. For the most current information, or if you have questions, please contact the Ecological and Landscape Classification Program (ELC@yukon.ca).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)

STE_SCANNED_MAP_BOUNDARY_SP includes an index of the mapsheet grid location of Soils, Terrain, Ecosystems and related scanned maps (including Agriculture Capability and Climate Capability maps). These maps are intended for on-screen viewing or printing. The majority of the maps have been geo-referenced. Mapping may not cover the whole map grid area. Some maps are interim or draft and may have been superseded. Some files are of related legends and map project text. Associated scanned map boundary attributes describe the project map (project level metadata) and provide a link for downloading the map, plus links to related reports, geo-referenced maps, and GIS digital data available from other sources. ATTENTION - The IMAGE_URL link is only useable by BC government staff. Public users can download the scanned maps by using the ECOCAT_URL link. There is no charge for the scanned map files. Please note that some maps and more recent mapping may also be available in digital GIS format. See - Ecosystem and Terrain Mapping Data Inventory.

Yukon Biophysical Plot locations are derived from the Yukon Biophysical Information System (YBIS) database, which is the Government of Yukon's repository for storing biophysical data . Data contain a combination of site, soil and vegetation information which are collected by multiple agencies to support vegetation inventory, habitat assessment and baseline ecosystem products collected from 1975 - 2018. Data are collected and input into the database using standardized biophysical field forms as per the "Field Manual for Describing Yukon Ecosystems" data collection standards. Data contributors include Government of Yukon, Government of Canada, First Nations Governments, private contractors, academia and the public. Location accuracy of plot data may vary based on the project year and location collection method. YBIS is an active database, which is subject to periodic updates and revisions. Because of this, the onus is on the end-user to ensure that they are using the most current version of the data. Although every effort has been made to ensure the correctness of the data, there still may be errors. Please report errors in the data to the Custodian.Contact Information:Ecological and Landscape Classification (ELC) Coordinator, elc@yukon.ca Ecological and Landscape Classification Program, Fish and Wildlife Branch, Department of Environment Government of Yukon, Box 2703, Whitehorse, Yukon Y1A 2C6 ph. (867) 667-3081Distributed 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)

This dataset provides wall-to-wall maps of forest structure across Canada's 650 million hectare forested ecosystems for the year 2022, generated at a spatial resolution of 30 m. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Structure estimates include key attributes such as canopy height, canopy cover, and aboveground biomass, derived using a combination of airborne lidar and Landsat-based spectral composites. Structure models were trained using the - lidar-plot framework - (Wulder et al. 2012), which integrates co-located airborne lidar data and ground plot measurements with Landsat time-series composites (Hermosilla et al. 2016). A Nearest Neighbour imputation approach was applied to estimate structural attributes across the full extent of Canada's forested area. These nationally consistent products are intended to support strategic-level forest monitoring and assessment and are not designed for operational forest management.For further details on the methods, accuracy assessment, and source data, see Matasci et al. (2018).Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment, 216, 697-714. https://doi.org/10.1016/j.rse.2018.07.024 (Matasci et al. 2018)

The outer boundary of the Province of Ontario. Land identifying the extent of the Province of Ontario for mapping purposes. This product requires the use of geographic information system (GIS) software.

This publication contains thirteen (13) maps of different biogeochemical and soil properties of forest ecosystems of Canada’s managed forest. A scientific article gives additional details on the methodology: Paré, D., Manka, F., Barrette, J., Augustin, F., Beguin, J. 2021. Indicators of site sensitivity to the removal of forest harvest residues at the sub-continental scale: mapping, comparisons, and challenges. Ecol. Indicators. https://dx.doi.org/10.1016/j.ecolind.2021.107516

High-resolution map of leading tree species distribution for Canada’s forested ecosystems (2019). Leading tree species map produced from a 2019 Landsat image composite, geographic and climate data, elevation derivatives, and remote sensing derived phenology following the framework described in Hermosilla et al. (2022). Regional classification models were generated based on Canada’s National Forest Inventory using a 150x150 km tiling system. The leading tree species are defined by representing the most voted tree species from the Random Forests classification models (i.e. the class with the highest class membership probability).The data represents leading tree species of Canada's forested ecosystems in 2019. An image compositing window of August 1 ± 30 days was used to generate the best-available-pixel (BAP) image composites utilized as source data for the classification.The science and methods developed to generate the information outcomes shown here, that track and characterize the history of Canada’s forests, were led by Canadian Forest Service of Natural Resources Canada, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS), partnered with the University of British Columbia, augmented by processing capacity from Digital Research Alliance of Canada.For an overview on the data, image processing, and methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2022) https://doi.org/10.1016/j.rse.2022.113276When using this data, please cite as: Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A., 2022. Mapping the presence and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of Environment 282, 113276.

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.