The Canadian Wildlife Service - Ontario Region Biodiversity Atlas represents the Canadian Wildlife Service biodiversity portfolio across the Ontario portions of the Boreal Hardwood Shield (Bird Conservation Region 12) and Mixedwood Plains (Bird Conservation Region 13) ecozones. These data are the derived product from an extensive landscape assessment that assessed the Canadian Wildlife Service biodiversity portfolio (Species at Risk, migratory birds, habitat) at various resolutions. Biodiversity is mapped by forest, grassland (open country) and wetland quality and quantity, and then progressively combined to identify local High Value Biodiversity Areas. At the finest resolution, scores were applied to each unit of analysis (5 hectare hexagon in Bird Conservation Region 12; 2 hectare hexagon in Bird Conservation Region 13), based on over 30 criteria for landscape habitat condition, Species at Risk and migratory birds. Habitat condition scores were derived from guidance in Environment and Climate Change Canada's existing How Much Habitat is Enough? and in Bird Conservation Region 12, where the landscape is less fragmented, habitat was also based on draft guidance in How Much Disturbance is too Much? Individual scores were summed and various combinations (e.g. top 25% of forest scores + top 25% of Species at Risk (SAR) scores) were calculated to identify areas with multiple conservation value. For each habitat type (forest, grassland and wetland), study units with more than one conservation value were aggregated into High Value Habitat which were subsequently aggregated into High Value Biodiversity Areas (HVBA). The results are areas on the landscape that have high value from a Canadian Wildlife Service specific lens; that is, they are high quality habitats that are important for Species at Risk and/or migratory birds. High value habitats are those forests, grasslands and wetlands with potential high conservation value (PHCV). They contain at least 1 of a possible 3 potential high conservation values: top 25% of overall habitat scores, top 25% of Species at Risk (SAR) scores, and/or top 25% of relevant migratory bird scores. High value forest, grassland and wetland were derived by combining landscape, Species at Risk (SAR) and migratory bird elements (see Table 1). Overall habitat scores were assigned to each study unit based on the combined scores for each forest, grassland and wetland. These overall habitat scores were divided into quartiles, and the top 25% of each total score (overall forest, overall grassland and overall wetland) are considered to be potential high conservation value. Similarly, SAR scores were assigned for each study unit, totalled and broken into quartiles. The top 25% of SAR scores that intersect each of forest, grassland and wetland are considered to be the highest quality habitats important to SAR and have potential high conservation value. Finally, relevant migratory bird scores were totalled within each study unit, divided into quartiles and the top 25% of migratory bird scores that intersect each of forest, grassland and wetland are considered to be the highest quality habitats important to migratory birds and have potential high conservation value. Study units with a PHCV greater than 0 (i.e., contains at least 1 of the possible 3 potential high conservation values) were aggregated together by 750 m to create High Value Habitats. High value biodiversity areas (HVBAs) are those study units that contain multiple high value habitats (high value forest and/or high value grassland and/or high value wetland). High value biodiversity areas (HVBA) were derived by aggregating high value forest, grassland and wetland. Study units with a potential high conservation value greater than 1 were aggregated together by 750 m. Biodiversity sites are areas greater than 20 ha, and secondary biodiversity sites are areas less than 20 ha in area.

Faults in the valleys near Ottawa could rupture and produce strong, shallow earthquakes. This magnitude 5.5 scenario visualizes the effects of such an event. It does not represent the most severe earthquake that could occur, but one that is more likely and could still cause damage.

Statistically downscaled multi-model ensembles of maximum temperature are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target. The 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of downscaled maximum temperature (°C) are available for the historical time period, 1951-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

Description: Seasonal mean total alkalinity from the British Columbia continental margin model (BCCM) were averaged over the 1981 to 2010 period to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone. Methods: Total alkalinities at up to forty-six linearly interpolated vertical levels from surface to 2400 m and at the sea bottom are included. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal total alkalinity climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution and 47 vertical levels. Uncertainties: Model results have been extensively evaluated against observations (e.g. altimetry, CTD and nutrient profiles, observed geostrophic currents), which showed the model can reproduce with reasonable accuracy the main oceanographic features of the region including salient features of the seasonal cycle and the vertical and cross-shore gradient of water properties. However, the model resolution is too coarse to allow for an adequate representation of inlets, nearshore areas, and the Strait of Georgia.

Full rupture of the Cascadia interface fault, the fault defining the boundary between the North American and Pacific Ocean plates. This magnitude 9.0 event, often referred to as ‘The Big One’, affects most communities in southwestern British Columbia.

Precipitation Percentiles represents the accumulated precipitation (mm) for the time period compared to historical information for the same time period. This comparison ranks the current precipitation amount and assigns it a percentile value based on a historic record. Products are produced for the following timeframes: Agricultural Year, Growing Season and Winter Season as well as rolling products for 30, 60, 90 and 180 days

Moored instrument time series data include current velocity, temperature, salinity, oxygen, fluorescence, transmissivity, turbidity, and particle capture of carbon, nitrogen, and silicon as well as sediment trap, ice drift and ice draft data. These data were collected by researchers from the Institute of Ocean Sciences, Sidney, BC, from locations ranging from the North Pacific, the Beaufort Sea, and across the Canadian Arctic Archipelago to Baffin Bay.

This series includes maps of projected average change in mean temperature (°C) based on CMIP5 multi-model ensemble results for RCP2.6, RCP4.5 and RCP8.5 (based on the 50th percentile of the distribution of the CMIP5 ensemble). Maps are provided for three time periods: 2016-2035, 2046-2065 and 2081-2100. For more maps on projected change, please visit the Canadian Climate Data and Scenarios (CCDS) site: https://climate-scenarios.canada.ca/?page=download-cmip5.

The Standardized Precipitation Index (SPI) has been recognized as the most accessible index for quantifying and reporting meteorological drought. On short timescales, the SPI is closely related to soil moisture, while at longer timescales, the SPI can be related to groundwater and reservoir storage. The model uses observed historical precipitation amounts to compute probability distributions which are then normalized using an incomplete gamma function over a range of timescales. The values can be interpreted as the number of standard deviations by which the observed anomaly deviates from the long-term mean. where positive values (greater than zero) result from above average conditions.

30-year Average Number of Days with Minimum Daily Temperature below -30 °C is defined as the count of climate days during the month where the minimum daily temperature was below -30 °C. These values are calculated across Canada in 10x10 km cells.