Statistically downscaled multi-model ensembles of minimum 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 minimum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded minimum 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 minimum 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.

The Agri-Environmental Indicator Risk of Water Contamination by Coliforms provides two variables including the Soil Coliform Load and the Coliform Risk to Water. The Soil Coliform Load indicator is the estimated accumulation of coliforms on the soil and the Coliform Risk to Water indicator is the relative risk of coliforms getting into the waterways. Products in this data series present results for predefined areas as defined by the Soil Landscapes of Canada (SLC v.3.2) data series, uniquely identified by SOIL_LANDSCAPE_ID values.

The health of individual amphibians, amphibian populations, and their wetland habitats are monitored in the oil sands region and at reference locations. Contaminants assessments are done at all sites. Amphibians developing near oil sands activities may be exposed to concentrations of oil sands-related contaminants, through air emissions as well as water contamination. The focus of field investigations is to evaluate the health of wild amphibian populations at varying distances from oil sands operations. Wood frog (Lithobates sylvaticus) populations are being studied in Alberta, Saskatchewan and the Northwest Territories in order to examine the relationship of proximity to oil sands activities and to prevalence of infectious diseases, malformation rates, endocrine and stress responses, genotoxicity, and concentrations of heavy metals, naphthenic acids and polycyclic aromatic hydrocarbons.

The ‘Land use allocation to Soils and Landforms by year’ dataset links agricultural land use activities to soils and landscapes within Soil Landscapes of Canada (SLC) polygons. The land use allocations to soils area datasets were generated on an annual time step (1971-2015). Agricultural land use is categorized and allocated based on the following general land use types: Annual cropland, Perennial cropland, Specialty Crops, Improved pasture and Unimproved Pasture.

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in total precipitation 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 precipitation (mm/day) from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded precipitation dataset of Canada (ANUSPLIN) was used as the downscaling target. Projected relative change in total precipitation is with respect to the reference period of 1986-2005 and expressed as a percentage (%). Seasonal and annual averages of projected precipitation change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of projected precipitation change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in statistically downscaled total precipitation (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of downscaled CMIP5 climate models is provided. 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.

The “Soil Landscapes of Canada (SLC) Version 3.2” dataset series provides a set of geo-referenced soil areas (polygons) that are linked to attribute data found in the associated Component Table (CMP), Component Rating Table (CRT), Soil Names Table (SNT), Soil Layer Table (SLT), Landscape Segmentation Table (LST), Landform Extent Table (LET), Landform Definition Table and Ecological Framework Table (EFT). Together, these datasets describe the spatial distribution of soils and associated landscapes for the agricultural areas of Canada. However, some provinces (Alberta, Nova Scotia, and Prince Edward Island) contain CMP, SNT and SLT data for the entire province (that is, beyond the agricultural areas). This version is complemented by the previous SLC version 2.2, which covers the entire country.

Growing Degree Days (GDDs) are used to estimate the growth and development of plants and insects during the growing season. Insect and plant development are very dependent on temperature and the daily accumulation of heat. The amount of heat required to move a plant or pest to the next development stage remains constant from year to year. However, the actual amount of time (days) can vary considerably from year to year because of weather conditions. Base temperatures are a point below which development does not occur for the organism in question. Base 0 temperatures are commonly used for cereals. These values are calculated across Canada in 10x10 km cells.

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in sea ice concentration based on an ensemble of twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Sea ice concentration is represented as the percentage (%) of grid cell area. Therefore, projected change in sea ice concentration is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of sea ice concentration change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in sea ice concentration (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. 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.