This data series was compiled by AAFC and Statistics Canada using a combination of agroclimate data and satellite-derived Normalized Difference Vegetation Index (NDVI) data for the current growing season. The forecast is made based on a statistical model using historical yield, climate and NDVI data.

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.

The Agri-Environmental Indicator of Risk of Water Contamination by Phosphorus dataset estimates the relative risk of phosphorus loss from Soil Landscapes of Canada agricultural areas to surface water. The data series for this indicator consists of four (4) datasets: Annual P-Balance, Soil-P-Source, Edge of Field and IROWC-P. 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.

This data series was compiled by AAFC and Statistics Canada using a combination of agroclimate data and satellite-derived Normalized Difference Vegetation Index (NDVI) data for the current growing season. The forecast is made based on a statistical model using historical yield, climate and NDVI data.

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

Crop development stage in a numerical scale. All living organisms move from one stage of development to the next over time. For annual crops, it life cycle (growing season) completed within a year. Crop water use differs from one stage to another mostly due to the differences in the amount of green leaves, thus crop stage is closely related to its water consumption and water stress condition. Crop stages are mostly controlled by growing season heat accumulation and regulated by day-length crop some crops. The crop stages provided here are determined by a biometeorlogical time scale model (Robertson, 1968) for cool season crops (wheat, barley etc.) , and a Crop Heat Unit (Brown and Bootsma, 1993) algorithm for warm season crops (corn and soybean etc.).

These products represent crop health indices derived from the Versatile Soil Moisture Budget (VSMB) model using crop specific coefficients and station based precipitation and temperature measurements to simulate crop growth. The VSMB model simulates soil moisture dynamics and water stress conditions based on water availability in the soil profile and simulated evapotranspiration during the crop growing season. Crop phenological stages, which are related to crop water use, are determined by a biometeorlogical time scale model (Robertson, 1968) for cool season crops (wheat, barley etc.) and a Crop Heat Unit (Brown and Bootsma, 1993) algorithm for warm season crops (corn and soybean etc.).

Multi-model ensembles of surface wind speed based on projections from twenty-nine 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 surface wind speed (m/s) 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.

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.

Canada's National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 106 km2 of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data. We used the k nearest neighbours (kNN) method with 26 geospatial data layers including MODIS spectral data and climatic and topographic variables to produce maps of 127 forest attributes at a 250 × 250 m resolution. The stand-level attributes include land cover, structure, and tree species relative abundance. In this article, we report only on total live aboveground tree biomass, with all other attributes covered in the supplementary data (http://nrcresearchpress.com/doi/suppl/10.1139/cjfr-2013-0401). In general, deviations in predicted pixel-level values from those in a PP validation set are greater in mountainous regions and in areas with either low biomass or sparse PP sampling. Predicted pixel-level values are overestimated at small observed values and underestimated at large ones. Accuracy measures are improved through the spatial aggregation of pixels to 1 km2 and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org) Related Products (16): - **[Poplars, Aspens and Cottonwoods (Genus Populus) in Canada 2006](https://ouvert.canada.ca/data/en/dataset/08620b3f-0bda-46f2-968d-e47d5a6032de)** - **[Birches (Genus Betula) in Canada 2006](https://ouvert.canada.ca/data/en/dataset/1410d784-ffde-43c8-a816-14cdfa0aa9c4)** - **[Treed land in Canada 2006](https://ouvert.canada.ca/data/en/dataset/1f1806b9-3927-496c-8c91-8789809f4472)** - **[Merchantable forest volume in Canada 2006](https://ouvert.canada.ca/data/en/dataset/2b3569c6-ff95-40a5-a958-dc68e3aa558b)** - **[Needle-leaved species in Canada 2006](https://ouvert.canada.ca/data/en/dataset/39ffee48-f89b-4b65-af03-58a706bac7a1)** - **[Forest height in Canada 2006](https://ouvert.canada.ca/data/en/dataset/3b860e37-32e6-4f47-a423-a7519ffa4429)** - **[Total live above-ground biomass in Canada 2006](https://ouvert.canada.ca/data/en/dataset/53af4b0e-015b-405e-8de8-e7eb4498eda1)** - **[Total forest volume in Canada 2006](https://ouvert.canada.ca/data/en/dataset/5b6b60d5-8299-45d4-8bd2-c274e75bc115)** - **[Spruces (Genus Picea) in Canada 2006](https://ouvert.canada.ca/data/en/dataset/72af5640-bb51-4c7a-8f41-6b71227a598f)** - **[Tree Crown Closure in Canada 2006](https://ouvert.canada.ca/data/en/dataset/a1510fe3-8ef0-4130-9ee4-8a7ea1f9a22d)** - **[Forest Composition across Canada 2006](https://ouvert.canada.ca/data/en/dataset/a42bd5d6-83a7-4fb7-a257-389dcf7ea48d)** - **[True Firs (Genus Abies) in Canada 2006](https://ouvert.canada.ca/data/en/dataset/d845f357-e2b5-494c-821f-064dba664427)** - **[Hemlocks (Genus Tsuga) in Canada 2006](https://ouvert.canada.ca/data/en/dataset/e676e5ab-b709-46ba-b471-4e982dce0c07)** - **[Broad-leaved species in Canada 2006](https://ouvert.canada.ca/data/en/dataset/e7b9b34a-70f8-47c6-9498-94361b9febbf)** - **[Maples (Genus Acer) in Canada 2006](https://ouvert.canada.ca/data/en/dataset/ed296d14-b222-45e7-9dcb-0ca8015207ad)** - **[Cedars (Genus Thuja) in Canada 2006](https://ouvert.canada.ca/data/en/dataset/fc8bb212-9ffe-447f-9152-e26baff7a735)**