A research survey on Stimpson's surfclam (Mactromeris polynyma) was conducted from June 15 to June 26 2017 in the Estuary of the St. Lawrence River on the Forestville deposit (Fishing Area 1A). The primary objective of this survey was to investigate the spatial distribution of pre-commercial (< 80 mm) and commercial (≥ 80 mm) sizes of Stimpson's surfclams as well as to assess the abundance and diversity of benthic species associated with the sandy habitat of the Stimpson's surfclam. Only benthic species data associated with Stimpson's surfclam habitat are presented in this dataset. Data were collected according to a systematic sampling design consisting of 77 stations, between 7 and 45 m depth. Stations were spaced 200 m apart and dispersed along a total of 18 transects perpendicular to the bathymetry. Transects were parallel and spaced 500 m apart. Specimens were collected using a hydraulic dredge of the "New England" type with a total length of 2.29 meters and a total width of 1.68 meters, of which 1.35 meters was knife width. The dredge was lined with a 19 millimeter mesh Vexar™ to harvest small individuals. The hauls were made at a speed of 0.2-0.3 knots for a duration of 2 to 3 minutes. Start and end positions were recorded to calculate the distance traveled at each tow using the geosphere library in R. The average tow distance was approximately 25 m. The area covered at each stroke was the product of the width of the dredge blade and the 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.

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)

A Priority Place is an area of high biodiversity value that is seen as a distinct place with a common ecological theme by the people who live and work there. As part of the Pan-Canadian approach to transforming species at risk conservation in Canada, a total of 11 Priority Places were affirmed by federal, provincial, and territorial governments in December 2018. One additional priority place was affirmed in 2024. The places selected have significant biodiversity, concentrations of species at risk, and opportunities to advance conservation efforts. In each Priority Place, the federal and provincial or territorial governments are working with Indigenous Peoples, partners, and stakeholders to develop conservation implementation plans. This dataset captures a small sample of the projects that are underway in these Priority Places. Over time, it will be expanded to include more projects. Some projects span various areas of a Priority Place but are reflected in this dataset as a single center point. This dataset is not to be used for legal purposes.

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).

Assessment Watersheds are mesoscale aquatic units designed to replace the 3rd order 1:50K watersheds. Assessment Watersheds are based on groupings of fundamental watersheds using FWA watershed code and local code, with a target size of between 2,000ha and 10,000ha.

This dataset contains information on flood protection structures (IPAs) listed in Quebec. For example, they may be embankment dikes or protective walls.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Hydrographic Annotation based on the 1:50,000 scale Canadian National Topographic Series of Maps.

Satellite-based forest area consistent with FAO definitions for Canada. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The forest area is based on the Food and Agricultural Organization of the United Nations (FAO) definition. The FAO definition incorporates land use, whereby trees removed by fire and harvesting for instance, remain forest as the trees will return. The included map displays the current forest cover for year as noted (i.e. 2022), plus the satellite-based temporally informed forest area where tree cover has been temporarily lost due to stand replacing disturbances (i.e., fire, harvest). For an overview of the methods, data, image processing, as well as information on accuracy assessment see Wulder et al. (2020). Open Access: Wulder, M.A., T. Hermosilla, G. Stinson, F.A. Gougeon, J.C. White, D.A. Hill, B.P. Smiley. (2020). Satellite-based time series land cover and change information to map forest area consistent with national and international reporting requirements. Forestry: An International Journal of Forest Research 93(3), 331-34, https://doi.org/10.1093/forestry/cpaa0063 . ( Wulder et al. 2020)