Predicted cation exchange capacity (meq/100g) at a defined depth range (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm). The interchange of a cation in solution and another cation on the surface of any surface-active material such as clay colloid or organic colloid.

Forest Percentage Above 2m 2015Percentage of first returns above 2 m (%). Represents canopy cover. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. 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. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Predicted silt percentage (%) at a defined depth range (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm).

Predicted bulk density (g/cm3) at defined depth ranges (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm). The mass of dry soil per unit bulk volume.

Level curves with an equidistance of 1 m derived from a lidar survey conducted in 2024.attributes:ID - Unique IDSubtype - Master (1) or secondary (2) level curve SCORE - Elevation value (m) The High Resolution Digital Elevation Model (m) product The High Resolution Digital Elevation Model (HRDM) product is available on the Open Government website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Predicted clay percentage (%) at a defined depth range (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm).

This service shows the predominant mother tongue in each census division based on English, French or non-official language. The data is from the data table Mother Tongue (10), Age (27) and Sex (3) for the Population of Canada, Provinces and Territories, Census Divisions and Census Subdivisions, 2016 Census - 100% Data, Statistics Canada Catalogue no. 98-400-X2016046.Mother tongue refers to the first language learned at home in childhood and still understood by the person at the time the data was collected. If the person no longer understands the first language learned, the mother tongue is the second language learned. For a person who learned two languages at the same time in early childhood, the mother tongue is the language this person spoke most often at home before starting school. The person has two mother tongues only if the two languages were used equally often and are still understood by the person. For a child who has not yet learned to speak, the mother tongue is the language spoken most often to this child at home. The child has two mother tongues only if both languages are spoken equally often so that the child learns both languages at the same time.For additional information refer to the 2016 Census Dictionary for 'Mother tongue'.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

This dataset represents abundance data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey. Data is binned into 5-mm shell height bins, is prorated to an 800 m tow length and 17.5 feet (5.334 m) drag width (i.e., representing an area swept of 4267 m2), and was collected using unlined dredge gear. Each row represents a tow and contains information such as tow date, cruise name, gear type, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Commercial Size Abundance Data. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ecc09d98-56ed-4a27-ad62-5c3714a1d9b4

Annual and five-year (5YA) average wet deposition maps for the ammonium ion are available. The file formats include geodatabase files (*.gdb) compatible with geospatial software (e.g. ESRI ArcGIS) and KMZ files compatible with virtual globe software (e.g. Google Earth™). Maps can also be viewed online via Open Maps and the ArcGIS online viewer. Annual deposition from each site was screened for completeness using the following criteria: (1) precipitation amounts were recorded for >90% of the year and >60% of each quarter, and (2) ammonium concentrations were reported for >70% of the precipitation measured over the year and for >60% of each quarter. Five-year average wet deposition values are averaged annual deposition values with a completeness criterion >60% for the five-year period. Units for wet deposition fluxes are in kg of NH4 per hectare per year (kg ha-1 y-1). Sources of measurement data and spatial interpolation method are described here: https://doi.org/10.18164/e8896575-1fb8-4e53-8acd-8579c3c055c2. Recommended citation: Environment and Climate Change Canada, [year published]. NH4 Wet Deposition Maps. Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada. [URL/DOI], accessed [date].Recommended acknowledgement: The author(s) acknowledge Environment and Climate Change Canada for the provision of Canada-U.S. wet deposition kriging maps accessed from the Government of Canada Open Government Portal at open.canada.ca, and the data providers referenced therein.

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)