This dataset represents the radioisoptopic tracers for selected rocks in the province of Saskatchewan, Canada.This dataset represents the compilation of radioisoptopic tracers for selected rocks in the province of Saskatchewan, Canada.  **Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse. They are therefore identical and share the same refresh schedule.

Transport Features is composed of, among others, the National Road Network (NRN) and the National Railway Network (NRWN). Transport Features entities are: Nautical Facility, Track Segment, Track Junction, Railway Station, Track Crossing, Track Marker Post, Track Structure, Rail Ferry, Road Segment, Road Ferry, Road Junction, Blocked Passage, Toll Point, Aerial Cableway, Footbridge, Trail, Navigational Aid, Marina, and Runway. CanVec is a digital cartographic reference product of Natural Resources Canada (NRCan). It originates from the best available data sources covering Canadian territory, offers quality topographical information in vector format and complies with international geomatics standards. CanVec is a multi-source product coming mainly from the National Topographic Data Base (NTDB), the Mapping the North process conducted by the Canada Center for Mapping and Earth Observation (CCMEO), the Atlas of Canada data, the GeoBase initiative and the data update using satellite imagery coverage (e.g. Landsat 7, Spot, Radarsat, etc.).Distributed 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@gov.yk. ca](mailto:geomatics.help@yukon.ca)

Registered Trapping Concessions (RTCs) are legal boundaries that define an area where the holder of the concession has the exclusive right to trap furbearing animals. Because trapping is done primarily along waterways, RTCs are often defined by watersheds, using height of land (ridges and mountain peaks) as their boundaries. This is the opposite of GMAs which are defined by mountains. Sometimes RTCs are grouped together to form a Group Trapping Concession (in which groups of individual share the right to trap). This may or may not involve the elimination of the component RTC boundaries. The Yukon has 360 RTCs and 13 Group Trapping Concessions. Only Kluane National Park, Kluane Wildlife Sanctuary, and Ddhaw Ghro Habitat Protection are are not covered by RTCs. This data was built using the 1:250,000 National Topographic Data Base (NTDB) as the digitizing base.Distributed 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)

Notice - Replacement of the English and French Web services (WMS and ESRI REST) with a bilingual one.The NRN product is distributed in the form of thirteen provincial or territorial datasets and consists of two linear entities (Road Segment and Ferry Connection Segment) and three punctual entities (Junction, Blocked Passage, Toll Point) with which is associated a series of descriptive attributes such as, among others: First House Number, Last House Number, Street Name Body, Place Name, Functional Road Class, Pavement Status, Number Of Lanes, Structure Type, Route Number, Route Name, Exit Number. The development of the NRN was realized by means of individual meetings and national workshops with interested data providers from the federal, provincial, territorial and municipal governments. In 2005, the NRN edition 2.0 was alternately adopted by members from the Inter-Agency Committee on Geomatics (IACG) and the Canadian Council on Geomatics (CCOG). The NRN content largely conforms to the ISO 14825 from ISO/TC 204.

The transport features of the CanVec series are derived from the National Road Network (NRN) and the National Railway Network (NRWN). The dataset describes roads, trails, bridges, railroads and their related information. The transport features include nautical facilities, track segments, track junctions, railway stations, track crossings, track marker posts, track structures, rail ferry segments, road segments, road ferry segments, road junctions, blocked passages, toll points, aerial cableway features, footbridges, trails, navigational aids, marinas and runways.The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.Related Products (Open Maps Links):[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)

Transportation networks (transportation)The means and aids for conveying people and goods. For example, resources describing roads, airports and airstrips, shipping routes, tunnels, nautical charts, vehicle or vessel location, aeronautical charts, and railways.

RAILLINE_OFFICIAL is one of the important layers for Saskatchewan Upgraded Road Network (SURN) and National Road Network (NRN). The RAILLINE_OFFICIAL provides the information of Railine to clients that require accurate, relatively up-to-date and detailed description of Saskatchewan Railline Network.RAILLINE_OFFICIAL data layer was developed by the Saskatchewan Ministry of Highways & infrastructure and contains the OFFICIAL version of the rail lines network in the province. RAILLINE_OFFICIAL layer has the linear geomtry of the CN, CP and provincial/shortline rail line in Saskatchewan. This version of the network is the one used for mapping, querying and plotting.

Transport Features is composed of, among others, the National Road Network (NRN) and the National Railway Network (NRWN). Transport Features entities are: Nautical Facility, Track Segment, Track Junction, Railway Station, Track Crossing, Track Marker Post, Track Structure, Rail Ferry, Road Segment, Road Ferry, Road Junction, Blocked Passage, Toll Point, Aerial Cableway, Footbridge, Trail, Navigational Aid, Marina, and Runway. CanVec is a digital cartographic reference product of Natural Resources Canada (NRCan). It originates from the best available data sources covering Canadian territory, offers quality topographical information in vector format and complies with international geomatics standards. CanVec is a multi-source product coming mainly from the National Topographic Data Base (NTDB), the Mapping the North process conducted by the Canada Center for Mapping and Earth Observation (CCMEO), the Atlas of Canada data, the GeoBase initiative and the data update using satellite imagery coverage (e.g. Landsat 7, Spot, Radarsat, etc.).Distributed 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)

The Canada Basemap Transportation (CBMT) is a raster tile service that provides spatial reference context with an emphasis on transportation networks across Canada. It is designed especially for use as a background layer in a web mapping application or geographic information system (GIS). Access: Access is free of charge under the terms of the Open Government Licence - Canada.Data Sources: Data for the CBMT is sourced from the following datasets:- Topographic data of Canada – CanVec Series- Official names from the Canadian Geographical Names Database (CGNDB).Projections:- Data is provided in the EPSG:3978 (NAD83 Canada Atlas Lambert) projected coordinate system.- Data is provided in the EPSG:3857 (WGS84 Pseudo-Mercator) projected coordinate system.Geographic Coverage: - The CBMT in the EPSG:3857 has complete coverage of the world, with full datasets in Canada and only partial data in other parts of the world including boundaries, Country Names, and major cities.- The CBMT in the EPSG:3978 covers the entire geographic area of Canada and some major transportation routes and cities in the northern States of the USA.Additional Versions: - The CBMT is available as a dynamic service (WMS) or a tiled service (ESRI REST and WMTS). - A geometry-only version (CBMT GEOM) and a text-only version (CBMT TXT) are available. - French versions of the basemap are accessible via the Carte de base du Canada - Transport (CBCT).

Description:This dataset consists of three simulations from the Northeastern Pacific Canadian Ocean Ecosystem Model (NEP36-CanOE) which is a configuration of the Nucleus for European Modelling of the Ocean (NEMO) V3.6. The historical simulation is an estimate of the 1986-2005 mean climate. The future simulations project the 2046-2065 mean climate for representative concentration pathways (RCP) 4.5 (moderate mitigation scenario) and 8.5 (no mitigation scenario). Each simulation is forced by a climatology of atmospheric forcing fields calculated over these 20 year periods and the winds are augmented with high frequency variability, which introduces a small amount of interannual variability. Model outputs are averaged over 3 successive years of simulation (the last 3, following an equilibration period); standard deviation among the 3 years is available upon request. For each simulation, the dataset includes the air-sea carbon dioxide flux, monthly 3D fields for potential temperature, salinity, potential density, total alkalinity, dissolved inorganic carbon, nitrate, oxygen, pH, total chlorophyll, aragonite saturation state, total primary production, and monthly maximum and minimum values for oxygen, pH, and potential temperature. The data includes 50 vertical levels at a 1/36 degree spatial resolution and a mask is provided that indicates regions where these data should be used cautiously or not at all. For a more detailed description please refer to Holdsworth et al. 2021.The data available here are the outputs of NEP36-CanOE_RCP 8.5; a projection of the 2046-2065 climate for the no mitigation scenario RCP 8.5.Methods:This study uses a multi-stage downscaling approach to dynamically downscale global climate projections at a 1/36° (1.5 − 2.25 km) resolution. We chose to use the second-generation Canadian Earth System model (CanESM2) because high-resolution downscaled projections of the atmosphere over the region of interest are available from the Canadian Regional Climate Model version 4 (CanRCM4). We used anomalies from CanESM2 with a resolution of about 1° at the open boundaries, and the regional atmospheric model, CanRCM4 (Scinocca et al., 2016) for the surface boundary conditions. CanRCM4 is an atmosphere only model with a 0.22° resolution and was used to downscale climate projections from CanESM2 over North America and its adjacent oceans.The model used is computationally expensive. This is due to the relatively high number of points in the domain (715 × 1,021 × 50) and the relatively complex biogeochemical model (19 tracers). Therefore, rather than carrying out interannual simulations for the historical and future periods, we implemented a new method that uses atmospheric climatologies with augmented winds to force the ocean. We show that augmenting the winds with hourly anomalies allows for a more realistic representation of the surface freshwater distribution than using the climatologies alone.Section 2.1 describes the ocean model that is used to estimate the historical climate and project the ocean state under future climate scenarios. The time periods are somewhat arbitrary; 1986–2005 was chosen because the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations end in 2005 as no community-accepted estimates of emissions were available beyond that date (Taylor et al., 2009); 2046–2065 was chosen to be far enough in the future that changes in 20 year mean fields are unambiguously due to changing GHG forcing (as opposed to model internal variability) (e.g., Christian, 2014), but near enough to be considered relevant for management purposes.While it is true that 30 years rather than 20 is the canonical value for averaging over natural variability, in practice the difference between a 20 and a 30 year mean is small (e.g., if we average successive periods of an unforced control run, the variance among 20 year means will be only slightly larger than for 30 year means). Also, there is concern that longer averaging periods are inappropriate in a non-stationary climate (Livezey et al., 2007; Arguez and Vose, 2011). We chose 20 year periods because they are adequate to give a mean annual cycle with little influence from natural variability, while minimizing aliasing of the secular trend into the means. As the midpoints of the two time periods are separated by 60 years, the contribution of natural variability to the differences between the historical and future simulations is negligible e.g., (Hawkins and Sutton, 2009; Frölicher et al., 2016).Section 2.2 describes how climatologies derived from observations were used for the initialization and open boundary conditions for the historical simulations and pseudo-climatologies were used for the future scenarios. The limited availability of observations means that the years used for these climatologies differs somewhat from the historical and future periods. Section 2.3 details the atmospheric forcing fields and the method that we developed to generate winds with realistic high-frequency variability while preserving the daily climatological means from the CanRCM4 data. Section 2.4 shows the equilibration of key modeled variables to the forcing conditionsData Sources:Model outputUncertainties:These climate projections are downscaled from a single global climate model (CanESM2/CanRCM4) because the cost of ensembles is presently prohibitive. Our experimental design uses climatological forcing for each time period so the differences between them are almost entirely due to anthropogenic forcing with little effect of natural variability.