The wind power density layer shows the modeled wind power density [W/m2] at a height of 100 m above ground level, at each grid point, averaged over the three year period from January 1, 2008 to December 31, 2010. Values are presented in bins with ranges of 0.5 W/m2 each. Further details including data at different heights, and for individual years, can be obtained by clicking on the dot representing the grid point location.

Wildfire ignition density rasters separated by cause (human, natural (lightning)) for mean and normalized mean summaries from 1980 to 2023.

A population ecumene is the area of inhabited lands or settled areas generally delimited by a minimum population density. This ecumene shows the areas of the densest and most extended population within census subdivisions. A census subdivision (CSD) is the general term for municipalities (as determined by provincial or territorial legislation) or areas treated as municipal equivalents for statistical purposes (e.g., Indigenous Peoples reserves and communities and unorganized territories). Municipal status is defined by laws in effect in each province and territory in Canada. For further information, consult the Statistics Canada’s 2016 Illustrated Glossary (see below under Data Resources).The assemblage of dissemination block population density data from the 2016 Census of Population are used to form the ecumene areas within census subdivisions. Areas included in the ecumene are dissemination blocks where the population density is greater than or equal to 0.4 persons per square kilometre or about one person per square mile. In some areas to capture more population within the ecumene the criteria was extended to 0.2 persons per square kilometre. The ecumene areas were generalized in certain areas to remove small uninhabited areas within the ecumene areas in census subdivisions.This map can be used as an “ecumene” overlay to differentiate the sparsely populated areas from the ecumene in conjunction with census subdivision data or other large-scale maps. This ecumene shows a more meaningful distribution of the population for Canada.

A population ecumene is the area of inhabited lands or settled areas generally delimited by a minimum population density. This ecumene shows the areas of the densest and most extended population within census divisions. Census divisions are the provincially legislated areas (such as county, municipalité régionale de comté, and regional district) or their equivalents. Census divisions are intermediate geographic areas between the province or territory level and the municipality (census subdivision). For further information, consult the Statistics Canada’s 2016 Illustrated Glossary (see below under Data Resources).The assemblage of dissemination area population density data from the 2016 Census of Population are used to form the ecumene within census divisions. Areas included in the ecumene are dissemination areas where the population density is greater than or equal to 0.4 persons per square kilometre or about one person per square mile. In some areas to capture more population within the ecumene the criteria was extended to 0.2 persons per square kilometre. The ecumene areas were generalized in certain areas to enhance the size of some isolated ecumene areas in northern Canada.This map can be used as an “ecumene” overlay to differentiate the sparsely populated areas from the ecumene in conjunction with census division data or other small-scale maps. This ecumene shows a more meaningful distribution of the population for Canada.

Average grid cell density is a polygon feature class containing the average density value for each grid cell per species/groups and season.

Forest Percent Above Mean 2015Percentage of first returns above the mean height (%). It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Represents the canopy cover above mean canopy height. 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

The monthly mean is the average of daily mean values for a given month.

The daily mean is the average of all unit values for a given day.

Mean Temperature Difference From Normal values are computed by subtracting the normal monthly average temperature from the average monthly temperature of the month. The average monthly temperature is computed by obtaining the mean value of average daily temperatures for a month. If the month was colder than normal the value computed will be negative and if it was warmer the value will be positive.

The St. Lawrence Estuary is known as a summer foraging area for several species of marine mammals, including several species of rorquals. Among these is the blue whale, which feeds almost exclusively on euphausiids. Therefore, the abundance, distribution and local density of krill should logically be a strong explanatory variable for the distribution of blue whales. However little is known about the spatial association of blue whales with the aggregation dynamics of krill in eastern Canada. Six years of acoustic surveys, conducted in August from 2009 to 2014, were undertaken to study the medium- and small-scale distribution of krill within the northwestern Gulf of St. Lawrence and estuary. The data shows a mosaic of the maximum annual density of arctic krill (T. raschii) made from these surveys.McQuinn, I.H., Gosselin, J.-F., Bourassa, M.-N., Mosnier, A., St-Pierre, J.-F., Plourde, S., Lesage, V., Raymond, A. 2016. The spatial association of blue whales (Balaenoptera musculus) with krill patches (Thysanoessa spp. and Meganyctiphanes norvegica) in the estuary and northwestern Gulf of St. Lawrence. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/104. iv + 19 p.