Organic soils in the boreal forest commonly store as much carbon as the vegetation above ground. While recent efforts through the National Forest Inventory has yielded new spatial datasets of forest structure across the vast area of Canada’s boreal forest, organic soils are poorly mapped. In this geospatial dataset, we produce a map primarily of forested and treed peatlands, those with more than 40 cm of peat accumulation and over 10% tree canopy cover. National Forest Inventory ground plots were used to identify the range of forest structure that corresponds to the presence of over 40 cm of peat soils. Areas containing that range of forest cover were identified using the National Forest Inventory k-NN forest structure maps and assigned a probability (0-100% as integer) of being a forested or treed peatland according to a statistical model. While this mapping product captures the distribution of forested and treed peatlands at a 250 m resolution, open, completely treeless peatlands are not fully captured by this mapping product as forest cover information was used to create the maps. The methodology used in the creation of this product is described in:Thompson DK, Simpson BN, Beaudoin A. 2016. Using forest structure to predict the distribution of treed boreal peatlands in Canada. Forest Ecology and Management, 372, 19-27. https://cfs.nrcan.gc.ca/publications?id=36751 This distribution uses an updated forest attribute layer current to 2011 from:Beaudoin A, Bernier PY, Villemaire P, Guindon L, Guo XJ. 2017. Species composition, forest properties and land cover types across Canada’s forests at 250m resolution for 2001 and 2011. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990 Additionally, this distribution varies slightly from the original published in 2016 in that here slope data is derived from the CDEM: https://open.canada.ca/data/en/dataset/7f245e4d-76c2-4caa-951a-45d1d2051333 The above peatland probability map was further processed to delineate bogs vs fens (based on mapped Larix content via the k-NN maps), as well as an approximation of the extent of open peatlands using EOSD data. The result is a 9-type peatland map with a more complete methodology as detailed in: Webster, K. L., Bhatti, J. S., Thompson, D. K., Nelson, S. A., Shaw, C. H., Bona, K. A., Hayne, S. L., & Kurz, W. A. (2018). Spatially-integrated estimates of net ecosystem exchange and methane fluxes from Canadian peatlands. Carbon Balance and Management, 13(1), 16. https://doi.org/10.1186/s13021-018-0105-5 In plain text, the legend for the 9-class map is as follows:value="0" label="not peat" alpha="0"value="1" label="Open Bog" alpha="255" color="#0a4b32"value="2" label="Open Poor Fen" alpha="255" color="#5c5430"value="3" label="Open Rich Fen" alpha="255" color="#792652"value="4" label="Treed Bog" alpha="255" color="#6a917b"value="5" label="Treed Poor Fen" alpha="255" color="#aba476"value="6" label="Treed Rich Fen" alpha="255" color="#af7a8f"value="7" label="Forested Bog" alpha="255" color="#aad7bf"value="8" label="Forested Poor Fen" alpha="255" color="#fbfabc"value="9" label="Forested Rich Fen" alpha="255" color="#ffb6db"This colour scale is given in qml/xml format in the resources below. The 9-type peatland map from Webster et al 2018 was further refined slightly following two simple conditions: (1) any 250-m raster cell with greater than 40% pine content is classified as upland (non-peat); (2) all 250-m raster cells classified as water or agriculture via the NRCan North American Land Cover Monitoring System (https://doi.org/10.3390/rs9111098) is also classified as non-peatland (value of zero in the 9-class map. This mapping scheme was used at a regional scale in the following paper: Thompson, D. K., Simpson, B. N., Whitman, E., Barber, Q. E., & Parisien, M.-A. (2019). Peatland Hydrological Dynamics as A Driver of Landscape Connectivity and Fire Activity in the Boreal Plain of Canada. Forests, 10(7), 534. https://doi.org/10.3390/f10070534 And is reproduced here at a national scale. Note that this mapping product does not fully capture all permafrost peatland features covered by open canopy spruce woodland with lichen ground cover. Nor are treeless peatlands near the northern treeline captured in the training data, resulting in unknown mapping quality in those regions.

The peatland geodatabase consists of polygon entities that depict the perimeter of individual peatlands and point entities that locate field sample sites. Basic attribute data is provided including data that can be used to link the geographical information to several published geoscientific databases.

* This dataset is updated on a daily basis. The ‘Record Modified’ date refers to the last metadata update.This dataset contains the extent of mineral claims held in Nunavut. A mineral claim is an area of Crown Land that is selected using the Nunavut Map Selection system by an individual or mineral exploration company that holds a valid licence to prospect. This grants the individual or mineral exploration company the mineral rights to the recorded area as provided for under the Nunavut Mining Regulations, SOR/2014-69. If the holder of a mineral claim wishes to produce minerals from the claim, or to hold it for more than thirty years, the holder must apply for a lease of the claim. This digital coverage provides a record and tracking mechanism for mining exploration in Nunavut.For more information, visit https://www.rcaanc-cirnac.gc.ca/eng/1100100036000/1547749889500. Note: This is one of the four (4) datasets that describe mineral tenure in Nunavut. It includes mineral claims, mining leases, prospecting permits as well as coal exploration licences.

This dataset provides treed area dynamics across Canada's 650 Mha forested ecosystems from 1984 to 2022, derived from Landsat-based annual land cover layers at a 30-m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). This dataset identifies areas that remained treed, transitioned to treed (newly treed), or transitioned to other cover that is not treed vegetation (was-treed). The data enable national and regional assessments of long-term changes in treed area, capturing trends in treed area, post-disturbance recovery, and shifts in forest extent.When using this data, please cite as: Hermosilla, T., Wulder, M.A., White, J.C., Bater, C.W., Baral, S.K., Leach, J.A., 2025. Expansion of treed area over Canada’s forested ecosystems: spatial and temporal trends. Forestry: An International Journal of Forest Research 98(5) 786-799. https://doi.org/10.1093/forestry/cpaf015. (Hermosilla et al. 2025)

Situated in the Gwich’in settlement Area (GSA), the Rat River is inhabited by anadromous Dolly Varden (Salvelinus malma malma) that are harvested by both Gwich’in and Inuvialuit beneficiaries. The harvest of Dolly Varden from the Rat River occurs during the summer at feeding areas along the coast (by the Inuvialuit) and during upstream migration in the Mackenzie Delta (by both Gwich’in and Inuvialuit). Dolly Varden stocks are co-managed under an Integrated Fisheries Management Plan (IFMP) whose signatories include Fisheries and Oceans Canada (DFO), Gwich'in Renewable Resources Board, Fisheries Joint Management Committee, and Parks Canada Agency. The Rat River Working Group, the co-management body that makes recommendations for harvest levels for Dolly Varden stocks in the GSA, has supported research activities that facilitate implementation of the IFMP, including studies to monitor harvest levels and assess population status. Population studies (e.g., abundance estimates, biological and genetic sampling) and coastal harvest monitoring activities allow for a comprehensive assessment of this stock. The data are used to inform co-management partners on the status of Dolly Varden from the Rat River.

Historical Open Range - 1963-1994 is a polygon layer that depicts grasslands and shrublands (originally designated as 'on land deemed with no potential for growing trees'). Data were derived from a (retired) Provincial Forest Cover Polygon dataset which was interpreted from air photos. Photograph and interpretation dates range from 1963 to 1994. This dataset has value as temporal snapshots of ecosystems under siege from human and natural processes. Data is useful for identification and analysis of forest ingrowth into grasslands from fire suppression. Encroachment can shift over time, for example from changing climate and disturbance events, and this data provides one measure of that shift. Data may also inform location of wildfire safety buffers around communities.

The locations of the 2 specialty crop areas in the Greenbelt Plan: * the Holland Marsh * Niagara Peninsula Tender Fruit and Grape Lands

This data is from the Newfoundland and Labrador Region Multispecies Trawl survey, specific to Snow Crab from 2018-25, with only successful tows included in the database. Details of annual survey coverage and an overview of the survey program can be found in Rideout et al. (2025) and references therein. This trawl survey follows a depth-stratified random design, designated by type = 1 (Survey). From 2021-23, a comparative fishing program (i.e., direct side-by-side paired comparison between old and new vessels) was undertaken to determine differences in catchability due to vessel changes and associated modifications to the trawl gear with the retirement of the CCGS Alfred Needler and CCGS Teleost (called ‘old vessels’) and the introduction of the CCGS Capt. Jacques Cartier and CCGS John Cabot (called ‘new vessels’). During this period other set types are in the dataset (6 and 7) from paired tows and all station allocation may not have been stratified random. The DFO NL Region comparative fishing success varied by year, NAFO division, and vessel combinations and resulted in conversion factors to adjust the catches of Snow Crab in the old vessels time series into the same units as the new vessels. Methodologies and conversion factors are described in Wheeland et al. (2024), Trueman et al. (2025), Trueman et al. (2026), and Pantin et al. (in prep). Conversion factors have been applied to the numbers of Snow Crab caught, where conversion factors exist, and are in the converted_number column. An NA in the converted_number column indicates that conversion factors do not exist for this vessel/area combination and therefore direct comparisons cannot be made between old vessels and new vessels. Weights are those recorded at sea and do not have conversion factors applied. Analyses by the DFO NL Snow Crab group apply a length-weight relationship to the converted numbers to determine converted weights, which is not in this dataset. All reasonable attempts are made to standardize fishing time during trawl surveys, however there is always some variation in the actual time on bottom. The species weights and numbers in this dataset are not standardized for tow distance/duration. Spatial coverage of this survey has varied over time, therefore, not all divisions, or depths within divisions, are sampled every year or season. Biological measurements are described in Pantin et al. (2025). Tows that caught zero Snow Crab are denoted in the dataset by a ‘number’ of 0.References:McCallum, B. R., and S. J. Walsh. 1996. Groundfish survey trawls used at the Northwest Atlantic Fisheries Centre, 1971-present. NAFO Sci. Coun. Studies, 29: 93-104.Pantin, J., D. Mullowney, K. Baker, K. Lefort, W. Coffey, F. Cyr, H. Munro, and Koen-Alonso, M. 2025. An Assessment of Newfoundland and Labrador Snow Crab (Chionoecetes opilio) in 2023. DFO. Can. Sci. Advis. Sec. Res. Doc. 2025/080. iv + 152 p.Pantin, J., Charmley, K., Mullowney, D., Baker, K., Lefort, K., Coyne, J., Munro, H., and Koen-Alonso, M. In prep. An Assessment of Newfoundland and Labrador Snow Crab (Chionoecetes opilio) in 2024. DFO Can. Sci. Advis. Sec. Res. Doc. year/nnn.Rideout, R.M., Wheeland, L., Perreault, A., Regular, P., Skanes, K., Simms, L., and Makrides, J. 2025. Canadian (Newfoundland and Labrador Region) Multi-Species Research vessel Bottom Trawl Survey Report for Surveys Conducted in 2024. NAFO SCR Doc. 25/028: 1-68.Trueman, S., Wheeland, L., Benoît, H., Munro, H., Nguyen, T., Novaczek, E., Skanes, K., and Yin, Y. 2025. Results of Comparative Fishing Between the CCGS Teleost and CCGS Alfred Needler with the CCGS John Cabot and CCGS Capt. Jacques Cartier in the Newfoundland and Labrador Region in 2021 and 2022. DFO Can. Sci. Advis. Sec. Res. Doc. 2025/021. v + 237 p. Trueman, S., Wheeland, L., Pantin, J., Baker, K., and Mullowney, D. 2026. On the relative catchability of Snow Crab in the Newfoundland and Labrador Multispecies trawl surveys. DFO Can. Sci. Advis. Sec. Res. Doc. 2026/008. iv + 41 p. Wheeland, L., Skanes, K. and Trueman, S. 2024. Summary of Comparative Fishing Data Collected in Newfoundland & Labrador from 2021-2022. Can. Tech. Rep. Fish. Aquat. Sci. 3579: iv + 132 p.

## Purpose The Ministry of Agriculture, Food and Agribusiness (OMAFA) is responsible for Ontario’s provincial soil maps and maintains and update them as necessary. Digital Soil Mapping (DSM) is a modern methodology using spatially explicit soils and environmental data to predict soil variation throughout a landscape at a high, consistent resolution. Digital soil maps are being rolled out throughout Ontario’s agricultural land base to update provincial soil maps. ## Reach Provincial soil maps are used in many decision-making processes including: * land use planning * land evaluation * farming practices * best management practices * ecological monitoring * land resource mapping Potential users of this data include: * farmers * certified crop advisors * conservation authorities * academic researchers * land use planners ## Potential impacts Digital soil maps provide more accurate and precise soils data and enables improved management of soil resources across multiple stakeholders. This allows for better decision making to maximize land use efficiency, improve economic efficiency of soil resources and promote soil health and soil conservation. ## Technical description Digital soil mapping combines geo-referenced soil observations with geo-referenced environmental layers to mathematically model soil variation as a function of environment variation. These models are based on well established, but often complex relationships, between soil properties and topography, biology, geology and hydrology.

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)