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    Data presented here comes from the 2016 Census of Canada, Statistics Canada. These datasets are part of the Official-Language Minority Communities Dashboard, an initiative of the Research Team of the Official Languages Branch at Canadian Heritage. Four datasets have been organized based on different population groups and universes and explore selected variables such as age, language, socio-economic and socio-demographic characteristics.

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    The “AAFC Annual Unit Runoff in Canada" data series illustrates runoff trends across the country by isolines of annual unit runoff for a variety of probabilities of exceedence commonly used by decision makers Annual unit runoff is a measure of runoff volume per square kilometre. This series uses units of cubic decametres (1000 m3) per square kilometre (dam3/km2), which is equivalent to millimetres depth on the landscape. It includes a point data set for the hydrologic stations that were analyzed and seven sets of line work to show the adjusted isolines for 10%, 25%, 50%, 70%, 75%, 80%, and 90% probability of exceedence.

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    The Agri-Environmental Indicator Risk of Water Contamination by Pesticides dataset reports the annual and semi-decadal status of pesticide transport to surface water, the concentration of pesticide in ground water, and the risk of water contamination by pesticide. 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.

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    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. Time periods calculated for monthly precipitation percentiles are 1, 2, 3, 6, 9, 12, 18, 24 months. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday. Historical record goes back to 1980. The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

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    “Biomass Inventory Mapping and Analysis – Business Data” provides a number of datasets related to the yield and production of residues from the agricultural and forestry industry, agricultural crops, and municipal solid wastes across Canada. The datasets contain agricultural residue production information (i.e., straw or stover) for barley, wheat, flax, oats and corn, and crop production information for barley, wheat, flax, oats, corn, canola and soybean. They also include information about amounts of straw required for cattle bedding and feeding, the type of tillage used in an area, and the amount of residue needed for soil conservation purposes. Datasets in the series provide the yield, production and other information for the median year and 1-in-10 year and 1-in-20 year lows. The forestry inventory dataset provides information about the location and quantity of residues from the forestry industry, as well as urban wood waste and potential sites and productivity of plantations of fast-growing trees that are grown as feedstock. Forestry residues include material left at the roadside after harvesting and excess and waste materials from mills. The municipal solid waste inventory dataset provides information about the approximate location and quantity of different types of municipal solid wastes, such as organics (including food and yard), paper and total. A transportation network dataset and datasets that are used to calculate cost to harvest and transport biomass are also included in this series.

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    A soil survey is an inventory of soils and their spatial distribution over a landscape. Soil survey reports contain two parts. The first part is a soil map or series of maps at a particular scale with coding for each soil. Soil survey reports also include a supporting document that contains background information such as how the soil survey was conducted, and an explanation of interpretive criteria and a summary of the area occupied by various soil types. The detailed soil surveys identify more of the variation in soil types across smaller landscapes, as compared to Generalized (1:100 000, i.e. provincial overview) and Reconnaissance or General (1:125 000, or 1/2 inch to 1 mile.) soil surveys. Detailed soil survey information is much more accurate and reliable for making decisions at the farm-level. Soil surveys have been published for most of the agricultural areas, and many surrounding areas, across Canada. Data from these surveys comprise the most detailed soil inventory information in the National Soil Database (NSDB). Version 3 was created by Agriculture and Agri-Food Canada in the 2010's by amalgamating version 2 data. It introduced some minor refinements to the version 2 data structure to provide closer alignment with the Soil Landscapes of Canada data structure.

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    Multi-model ensembles of sea ice concentration based on projections from twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of sea ice concentration as represented as the percentage (%) of grid cell area, are available for the historical time period, 1900-2005, 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.

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    Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in minimum temperature (°C) 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. Projected change in minimum temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected minimum temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of minimum temperature 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 mean minimum temperature (°C) 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.

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    Frost Day Count (0 °C) is defined as the number of days in a calendar month where the minimum daily temperature for the climate day was at or below 0 °C. These values are calculated across Canada in 10x10 km cells.

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    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.