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.

Seed Planning Unit (SPU) geometry is comprised of Seed Planning Zone geometry delineated by elevation ranges. Each SEED_PLAN_UNIT_ID relates to a SEED_PLAN_ZONE for a specific tree species and minimum/maximum elevation in meters. Seed Planning Units only apply to Genetic Class A (orchard/parent tree). Some coastal species also have a latitude range. The geometry can be joined to the SEED_PLAN_UNIT table using SEEED_PLAN_UNIT_ID to determine the Seed Planning Zone, tree species and elevation range.

The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed the presence of Cod in the Population Ecology Division (DFO Science) Ecosystem Survey trawls to describe the likelihood of presence. The survey consists of a stratified random design using a bottom trawl. This layer was created for consideration in oil spill response planning. A version of this dataset was created for the National Environmental Emergency Center (NEEC) following their data model and is available for download in the Resources section. Cite this data as: Lazin, G., Hamer, A.,Corrigan, S., Bower, B., and Harvey, C. Data of: Likelihood of presence of Atlantic Cod in Area Response Planning pilot areas. Published: June 2018. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/af2bf6c0-481d-4445-bbc6-7a785d2a9aa9

“Pukaskwa National Park - Total GHG Emissions” datasets consist of estimates of GHG emissions (carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)) in carbon dioxide equivalents (CO2e) from forested ecosystems in Pukaskwa National Park from 1990 to 2020 (tonnes carbon dioxide equivalent per hectare). Total GHG emissions for 31 national parks were estimated using the Generic Carbon Budget Model (GCBM), a spatially explicit carbon budget model developed by Canadian Forest Service which uses forest inventory, disturbance, and mean annual temperature data along with yield data to estimate growth and merchantable volume for dominant tree species. Species- and Ecozone-specific equations are then used to convert merchantable volume to aboveground and belowground biomass carbon. The GCBM simulates carbon dynamics to produce spatially explicit estimations of carbon stocks and fluxes. The model simulates and tracks carbon stocks, transfers between Intergovernmental Panel on Climate Change (IPCC)-defined pools, and other metrics including net ecosystem production, net biome production, and emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in annual time steps. The stocks and fluxes are also tracked by disturbance event (e.g., forest fires). Total GHG emissions include those from natural processes like respiration and decomposition and those due to natural and anthropogenic disturbances, including wildfires, prescribed burns, and insect outbreaks. These were calculated as the sum of CO2, CH4, and N2O emission estimates in tonnes carbon (tonnes C) generated by the GCBM. Emissions estimates were then converted to carbon dioxide equivalents (CO2e) using the 100-year Global Warming Potential (IPCC Fourth Assessment Report) factors for CH4 (25) and N2O (298). These products have a spatial resolution of 30m. This information is part of the Parks Canada Carbon Atlas Series. To obtain a copy of this report, please contact changementclimatique-climatechange@pc.gc.ca. When using this data, please cite as follows: Sharma, T., Kurz, W.A., Fellows, M., MacDonald, A.L., Richards, J., Chisholm, C., Seutin, G., Richardson, K., Keenleyside, K. (2023). Parks Canada Carbon Atlas Series: Carbon Dynamics in the Forests of Canada’s National Parks. Scientific Report. Parks Canada Agency, Gatineau, QC, Canada, 104 p.

AIS NL Biofouling Species Fisheries and Oceans Canada's (DFO) National Marine Biofouling Monitoring Program conducts annual field surveys to monitor the introduction, establishment, spread, species richness, and relative abundance of native and some non-native species in Newfoundland and Labrador (NL) Region since 2006. Standardized monitoring protocols employed by DFO's NL, Maritimes, Gulf, and Quebec regions include biofouling collector plates deployed from May to October at georeferenced intertidal and shallow subtidal sites, including public docks, and public and private marinas and nautical clubs. Initially, (2006-2017), the collectors consisted of three 10 cm by 10 cm PVC plates deployed in a vertical array and spaced approximately 40 cm apart, with the shallowest plate suspended at least 1 m below the surface to sample subtidal and shallow intertidal species (McKenzie et al 2016a). Three replicate arrays were deployed at least 5 m apart per site. Since 2018, collector networks have been modified to improve statistical replication, including up to 10 individual collectors deployed per site at 1 m depth and at least 5 m apart (as above) from May to October. Since 2006, seven invasive biofouling organisms have been detected in Newfoundland and Labrador harbours, marinas and coastal areas. Should be cited as follows: DFO Newfoundland and Labrador Region Aquatic Invasive Species Marine Biofouling Monitoring Program. Published March 2024. Coastal and Freshwater Ecology, Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John’s, Newfoundland and Labrador. Reference: Tunicates Vase tunicate (Ciona intestinalis) 2012 The Vase tunicate, is a high impact solitary invader and was first detected by DFO in 2012 on the Burin Peninsula at Ship Cove and Little Bay, Placentia Bay. Various mitigation measures (McKenzie et al. 2016b) contained this invasive tunicate to a small area for six years within Placentia Bay. First detected in Fortune Bay as an established population in 2019, increasing reports of the Vase tunicate have been made along the south coast of Newfoundland. The data provided here indicates the detections of this AIS in coastal NL. From 2018-2022, the Coastal Environmental Baseline Program provided additional support to enhance sampling efforts in Placentia Bay.

Wildlife habitat capacity is the extent and quality of habitat that can support a diversity of species. When we convert wilderness to agricultural land we lose a great deal of wildlife habitat capacity. However, we can manage agricultural land to regain some of this capacity. Agricultural land includes not only fields for food production but also other types of land cover. Wooded areas, wetlands, shoreline areas and natural pastures on agricultural land are important habitats for wildlife. The indicator shows how well wildlife habitat is maintained for feeding and reproduction while producing the food we need. 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. Data is provided for the following years: 2000, 2005, 2010, 2015 and 2020. The annual results respect provincial boundaries which can be of use when analyzing results per province.

"Banff National Park - Total Ecosystem Forest Carbon Density” is the annual carbon density (tonnes carbon per hectare) within Banff’s forested ecosystems over a 31-year period from 1990 to 2020. Total Ecosystem Forest Carbon Density includes aboveground and belowground biomass, soil carbon, and dead organic matter. Total Ecosystem Forest Carbon Density was estimated for 31 national parks using the Generic Carbon Budget Model (GCBM), a spatially explicit carbon budget model developed by Canadian Forest Service which uses forest inventory, disturbance, and mean annual temperature data along with yield data to estimate growth and merchantable volume for dominant tree species. Species- and Ecozone-specific equations are then used to convert merchantable volume to aboveground and belowground biomass carbon. Ecozones were classified according to Canada Ecological Land Classification Level 1. The GCBM simulates carbon dynamics to produce spatially explicit estimations of carbon stocks and fluxes. The model simulates and tracks carbon stocks, transfers between Intergovernmental Panel on Climate Change-defined pools, and other metrics including net ecosystem production, net biome production, and emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in annual time steps. The stocks and fluxes are also tracked by disturbance event (e.g., forest fires, insect outbreaks). Total Ecosystem Forest Carbon Density accounts for the effects of natural and anthropogenic disturbances, including wildfires, prescribed burns, and insect outbreaks. These products have a spatial resolution of 30m. This information is part of the Parks Canada Carbon Atlas Series. To obtain a copy of this report, please contact changementclimatique-climatechange@pc.gc.ca. When using this data, please cite as follows: Sharma, T., Kurz, W.A., Fellows, M., MacDonald, A.L., Richards, J., Chisholm, C., Seutin, G., Richardson, K., Keenleyside, K. (2023). Parks Canada Carbon Atlas Series: Carbon Dynamics in the Forests of Canada’s National Parks. Scientific Report. Parks Canada Agency, Gatineau, QC, Canada, 104 p.

Dry spell periods are defined as the number of days (April 1 – October 31) where daily precipitation is less than 0.5 mm. This is not an accumulation of precipitation, simply a count of days. Dry spell products are only generated during the Growing Season, April 1 through October 31.

The Natural Environment Management Plan (PGMN) identifies the area for which the City of Lévis has conservation goals. This corresponds to map 13 of the Development Plan “The Natural Environments Conservation Area”.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**