EMR Natural Resource SubdistrictsDistributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

EMR Natural Resource DistrictsDistributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

Province wide spatial view showing aquifers designated as a Water Reservation. These Reserves set aside water in an aquifer specifically for future treaty obligations, and are formally established through Orders in Council issued by the Lieutenant Governor in Council, as authorized under Sections 39–41 of the Water Sustainability Act.

Situated in the Gwich’in settlement Area (GSA), the Rat River is inhabited by anadromous Dolly Varden (Salvelinus malma malma) that are harvested by both Gwich’in and Inuvialuit beneficiaries. The harvest of Dolly Varden from the Rat River occurs during the summer at feeding areas along the coast (by the Inuvialuit) and during upstream migration in the Mackenzie Delta (by both Gwich’in and Inuvialuit). Dolly Varden stocks are co-managed under an Integrated Fisheries Management Plan (IFMP) whose signatories include Fisheries and Oceans Canada (DFO), Gwich'in Renewable Resources Board, Fisheries Joint Management Committee, and Parks Canada Agency. The Rat River Working Group, the co-management body that makes recommendations for harvest levels for Dolly Varden stocks in the GSA, has supported research activities that facilitate implementation of the IFMP, including studies to monitor harvest levels and assess population status. Population studies (e.g., abundance estimates, biological and genetic sampling) and coastal harvest monitoring activities allow for a comprehensive assessment of this stock. The data are used to inform co-management partners on the status of Dolly Varden from the Rat River.

A "contaminant attenuation zone" is a three-dimensional zone that is, * located on land adjacent to a landfilling site, * in the subservice or extends into the subsurface, and * is used or is intended to be used for the attenuation of contaminants from the landfilling site to levels that will not have an unacceptable impact beyond the boundary of the zone. This product requires the use of geographic information system (GIS) software.

This data report provides information on temperature and salinity in the Godbout region of the St. Lawrence Estuary. Sampling was carried out from 2019 to 2021 over an area of <5 km2. The databases provide information on temperature and salinity at an hourly rate for 2 years. The aim of this project is to analyze telemetry data from sea urchins (Strongylocentrotus droebachiensis), snow crabs (Chionoecetes opilio), rock crabs (Cancer irroratus), spider crabs (Hyas spp.) and whelks (Buccinum undatum). This report focuses on the presentation of benthic environmental data collected throughout the study with high spatial and temporal resolution. All reported variables were collected at the seafloor, as the aim of the project was to study the movement of epibenthic species. Temperature data were collected from three devices: telemetry receivers with integrated temperature sensors (InnovaseaTM), HoboTM and Star-OddiTM probes. Temperature data processing involved cleaning up extreme values (below 2°C and above 20°C) and homogenizing the data to fit the bathymetry matrix (1m x 1m cells) of the study site. Temperature data are provided in a NetCDF file with a matrix of the entire study site, where there is a stratum for each hour between August 2019 and October 2021 and in each file, a temperature value for each pixel of the raster. Salinity data were collected from Star-OddiTM probes only. Salinity values were averaged hourly for the entire study area. Salinity data is provided as a CSV file with one salinity value per hour for the entire study area.

The dataset identifies the location and types of Areas of Natural and Scientific Interest (ANSIs) that are commonly used in maps for resource management purposes. Official GEO title: ANSI

The raster maps depict a suite of forest attributes in 2001* and 2011 at 250 m by 250 m spatial resolution. The maps were produced using the k nearest neighbours method applied to MODIS imagery and trained from National Forest Inventory photo plot data. For detailed information about map production methods please refer to Beaudoin et al. (2018) "Tracking forest attributes across Canada between 2001 and 2011 using the k nearest neighbours mapping approach applied to MODIS imagery." Canadian Journal of Forest Research 48, 85-93. https://cfs.nrcan.gc.ca/publications?id=38979 The map datasets may be downloaded from https://nfi.nfis.org/downloads/nfi_knn2011.zip or https://open.canada.ca/data/en/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 * Note: the forest composition (leading tree genus) map depicts forest attributes in 2001.How can this data be used?The resolution and accuracy of these map products are best suited for strategic-level forest reporting and informing policy and decision making at regional to national scales. As these maps also offer a coherent set of quantitative values for a large suite of forest attributes, they can be used as baseline information for modelling and in calculations such as merchantable forest volume or percentage of tree species. It is also possible to overlay these maps with other maps produced on the same pixel grid to make assessments of disturbance impacts, such as fire and harvests.

Administrative divisions corresponding to the territories represented by the municipal councilors.Attributs:id - ID - Unique IdentifierNumero - Electoral district numberMunicipality - Municipality codeName - Name of the electoral district councilor - Name of the electoral district councilor - Name of the electoral district councilor**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The blue whale (Balaenopterus musculus) is a wide-ranging cetacean that can be found in all oceans, inhabiting coastal and oceanic habitats. In the North Atlantic, little is known about blue whale distribution and genetic structure, and if whether animals found in Icelandic waters, the Azores, or Northwest Africa are part of the same population as those from the Northwest Atlantic. In the Northwest Atlantic, seasonal movements of blue whales and habitat use, including the location of breeding and wintering areas, are poorly understood.The behaviour of remotely-monitored animals can be inferred from a time series of location data. This is because animals tend to demonstrate stochasticity in their movement paths as a result of spatial variation in environmental characteristics, such as topography or prey density (Curio 1976; Gardner et al. 1989; Turchin 1991; Wiens et al. 1993). Predators are expected to decrease travel speed and/or increase turning frequency and turning angle when a suitable resource, e.g., food patch, is encountered (Turchin 1991), otherwise known as area-restricted search (ARS). In contrast, animals in transit or travelling tend to move at faster and more regular speeds, with infrequent and smaller turning angles (Kareiva and Odell 1987; Turchin 1998).Based on satellite telemetry to track the seasonal movements of 24 blue whales from eastern Canada in 2002 and from 2010 to 2015, it was possible to estimate trajectories and locations where ARS behaviour of blue whales was inferred at a 4h time interval.To assess blue whale movements and behavior, a Bayesian switching statespace model (SSSM) was applied to Argos-derived telemetry data (Jonsen et al. 2005; Jonsen et al. 2013). An SSSM essentially estimates animal location at fixed time intervals, movement parameters and behavioral patterns.Two important sources of uncertainty can be measured separately: estimation error resulting from inaccurate observations (Argos location error) and process variability linked to the stochasticity of the movement process (behavior mode estimation) (Jonsen et al. 2003; Patterson et al. 2008).The points visible on land are the result of errors in the Argos geographic position calculation. They have been deliberately left unchanged to assess the performance of the model, which was able to clean up some positions, but not all.Lesage, V., Gavrilchuk, K., Andrews, R.D., and Sears, R. 2016. Wintering areas, fall movements and foraging sites of blue whales satellite-tracked in the Western North Atlantic. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/078. v + 38 p.