Description: Seasonal mean primary production from the British Columbia continental margin model (BCCM) were averaged over the 1981 to 2010 period and depth-integrated to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone. Methods: Total primary production is the sum of diatoms and flagellates production. 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 a raster layer of seasonal depth-integrated primary production climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution. 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.

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.

The Agri-Environmental Indicator - Agriculture Ammonia Emissions datasets provides estimated amounts of ammonia (NH3) emitted into the atmosphere through agricultural activities. 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.

Monthly mean salinity from Bedford Institute of Oceanography North Atlantic Model (BNAM) results were averaged over 1990 to 2015 period to create monthly mean climatology for the Northwest Atlantic Ocean, which can be considered as a representation of the climatological state of the Northwest Atlantic Ocean. The BNAM model is eddy-resolving, NEMO-based ice-ocean coupled North Atlantic Ocean model developed at the Bedford Institute of Oceanography (BIO) to support DFO monitoring programs. The data available here is monthly climatology for eight selected depths (surface, 110 m, 156 m, 222 m, 318 m, 541 m, 1062 m, bottom) in 1/12 degree spatial resolution. The data for each month from 1990 until present for the entire model domain ( 8°–75°N latitude and 100°W–30°E longitude) and various depths is available upon request. The 1990-2017 model hindcast result is compared with observational data from surface drifter and satellite altimetry. The model demonstrates good skill in simulating surface currents, winter convection events in the Labrador Sea, and the Atlantic Meridional Overturning Circulation as observed at 26.5°N and 41°N. Model results have been used to interpret changes in the Labrador Current and observed warming events on the Scotian Shelf, and are reported through the annual AZMP Canadian Science Advisory Secretariat Process. When using data please cite following: Wang, Z., Lu, Y., Greenan, B., Brickman, D., and DeTracey, B., 2018. BNAM: An eddy resolving North Atlantic Ocean model to support ocean monitoring. Can. Tech. Rep. Hydrogr. Ocean. Sci. 327: vii + 18p

Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Wagmatcook 2007 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Wagmatcook 2007. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

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.

LiDAR data collected in 2018 of water control structures in Tennaille, Newton, and Huff Lake in Saskatchewan, Canada. Includes Digital Terrain Models, Contours, and Orthorectified imagery. LiDAR Data to be used by AAFC to assess whether additional land control should be pursued and other hydrological studies including potential dam break failure scenarios.

This data represents the dryness of the land surface based on vegetation conditions. The data is created weekly and uses weekly information on precipitation anomalies (namely the Standardized Precipitation Index or SPI) and satellite vegetation condition derived from Normalized Difference Vegetation Index (NDVI) from the MODIS Satellite. These dynamic data sets along with static data sets on land cover, soil water holding capacity, irrigation, ecozones and land surface elevation are used to model the drought severity, based on the Palmer Drought Severity Index (PDSI). The mapcubist model was trained on historical data and applied in real time to the dynamic inputs to produce drought severity ratings. The model is run at a 1km resolution and was developed by the AAFC, the United States Geological Survey and the United States Drought Monitor at the University of Nebraska Lincoln.

Acid-Sensitive Lakes Nine hundred and thirty-three lakes located in Saskatchewan, Alberta and the Northwest Territories were sampled to establish current acidification status. Of the 933 lakes, 244 (or 26%) are considered acid sensitive, almost always because of naturally low calcium and magnesium (or "base cation") concentrations. The most acid-sensitive lakes (i.e., those with extremely low base cation concentrations) are located on the Canadian Shield in both Alberta and Saskatchewan and east of the oils sands development area. Fifty-one of the 244 acid-sensitive lakes were sampled twice annually (spring and fall) to identify chemical changes through trend analyses. Results revealed that 55% of these lakes had concentrations of some metals in excess of Canadian Council of Ministers of the Environment guidelines. Of the 291 samples taken in the 51 lakes, iron concentrations were greater than guidelines in 36% (105 samples), aluminum in 33% (97 samples), lead in 0.3% (1 sample) and copper in 0.3% (1 sample). The metals in these lakes occur naturally and are expected to be found in a wide range of concentrations given the geology and physiography of the Canadian Shield. It remains to establish the relationship between acid sensitivity, geology and high metal concentrations.