Fish Habitat Assessment Output: 5 of 16 High Water Level (75.4m ASL) - Juvenile/Adult Habitat - High Vegetation Association Species (All Thermal Guilds) Habitat suitability was assessed for the Bay of Quinte Area of Concern, at a 3 m grid resolution, using the Habitat Ecosystem Assessment Tool (HEAT), temperature algorithms, vegetation models, and water level input. Habitat classifications were based on three variables: depth (elevation), vegetation, and substrate; and modified by temperature suitabilities. The final suitability maps were based on documented habitat and temperature associations for the fish in the area. Different life stages (spawning requirements, nursery habitat, adult habitat) were modeled for the years of 1972-2011. Suitability values were scaled from 0 (not suitable) to 1 (highly suitable) and converted to suitability classes of very low, low, medium, and high. The final maps for each guild – life stage combination are maximum suitability values from the 39-year period modelled.

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 Georgia Basin Boundary dataset displays the extent of the Georgia Basin Ecosystem Initiative undertaken by the federal, provincial, and municipal governments. The objectives of the project are to support initiatives for clean air, clean water, habitat and species protection, and improved environmental decision-making in the Georgia Basin. The dataset consists of both a polygon layer and line layer

Nova Scotia provincial ambient air quality monitoring stations, including locations and other attributes.

“Cape Breton Highlands National Park - Total Ecosystem Forest Carbon Density” is the annual carbon density (tonnes carbon per hectare) within Cape Breton Highlands’ 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.

Research surveys targeting Icelandic scallops (Chlamys islandica) have been conducted by Fisheries and Oceans Canada (DFO) at one- or two-year intervals in the Mingan Archipelago (since 1990 in fishing area 16E and since 2004 in fishing area 16F). The main objective of this survey is to assess the status of Icelandic scallop stocks. The study area is situated around the Mingan Archipelago, where scallop beds are sampled at depths ranging from approximately 8 to 136 m, but typically around 40 to 60 m. Sampling is conducted along transects at fixed stations in the study area. Each station is sampled using a lined Digby scallop dredge (20 mm mesh size), towed for roughly 150 m across the seabed. This publication includes three files: the file biometriePetoncle_16, which contains detailed biometric data (species, size, weights and sex) from 2001 to 2025; the file taillePetoncle_16, which provides the size of the individuals sampled from 2010 to 2024; and the file traitPetoncle_16 which contains the abundances and densities per tow from 2004 to 2024. Data on abundances and densities per tow from 2001-2003 is available upon request. This dataset is updated every one to two years as data becomes available. A cleaning of aberrant data has been carried out. However, there is missing data in various columns of the dataset – use the data with caution. If you have any questions please contact DFO.DataManagementSAISB-GestionDonneesDAISS.MPO@dfo-mpo.gc.ca or the author. For certain time periods, associated species are identified and semi-quantitatively counted directly on the sorting table, and the results are presented in the following publication: - https://open.canada.ca/data/en/dataset/7d29bdb1-7e39-43ee-9fb1-bbf33cc9c9b9

We are referring here to the main social districts in Longueuil. The concept of sociological district does not refer to a formal administrative division. It illustrates the Longueuil territories (neighborhood) identified and recognized by local actors on the basis of history, belonging and socio-community organization and the challenges involved.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**