These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

A Retaining Wall is a structure designed to protect the road infrastructure by retaining materials on the fill side to prevent road bed slips and by retaining materials on the cut side to prevent the road surface from being covered by debris. Retaining walls that are greater than or equal to 2m in height are stored in the MoT Bridge Structure Road dataset. It is a Linear feature

Punctual location of structures under the management of MTMD (various types of: bridge, culvert (over 4.5 meters), gantry, wall and tunnel).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Wall-to-wall map of water bodies across Canada's forested ecosystems for the year 2022, derived from the "water" class of the annual Virtual Land Cover of Engine (VLCE) product. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The VLCE maps are based on Landsat image time-series composites and represent annual land cover classifications from 1984 to 2022 at a spatial resolution of 30 m. The classification process integrates forest change information and ancillary topographic and hydrologic variables, applying a regional modeling framework based on a 150x150 km tiling system ( Hermosilla et al., 2022). Training data are drawn from multiple land cover sources and selected proportionally to land cover distributions using a distance-weighted approach. Classifications are refined over time using a Hidden Markov Model to ensure consistency and reduce classification noise between years.Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C. 2022. Land cover classification in an era of big and open data: Optimizing localized implementation and training data selection to improve mapping outcomes. Remote Sensing of Environment. 268, 112780. https://doi.org/10.1016/j.rse.2021.112780. ( Hermosilla et al., 2022)Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W. 2018. Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series. Canadian Journal of Remote Sensing. 44(1) 67-87. https://doi.org/10.1080/07038992.2018.1437719.( Hermosilla et al., 2018)

The manmade features of the CanVec series include dams, protection structures (breakwater, dike/levees), liquid storage facilities (basin, swimming pool, etc.), tanks, buildings, delimiting structures (fence, walls, etc.), landmark features (cross, radar, crane, forts, etc.), chimneys, towers, sewage pipelines, conduit bridges, waste, leisure areas, residential areas, commercial and institutional areas and ritual cultural areas (shrine, cemeteries, etc.).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)

PURPOSE:The purpose of this work was to determine (1) how the population genomic structure relates to gut microbiota composition of White Hake (Urophycis tenuis), and (2) whether microbiota community variation provides complementary insights into population structure of this species in eastern Canada.DESCRIPTION:Integrating host-associated microbiota with genomic approaches offers an opportunity to better understand the multiple biological dimensions shaping population structure in marine fishes. A clear understanding of population structure and dynamics is essential for informed fisheries management and conservation decisions; however, while genomic approaches have greatly improved our ability to delineate biological populations, they provide only a partial representation of biological structure, as patterns of differentiation reflect both historical divergence and contemporary ecological conditions. Host-associated microbiota can influence population-level ecological processes by contributing functional, potentially heritable variation that shapes host phenotype and fitness.In this study, we combined genotyping-by-sequencing with 16S rRNA gene amplicon sequencing to examine how population genomic structure relates to gut microbiota composition and to evaluate whether microbiota community variation provides complementary insights into population structure in White Hake (Urophycis tenuis) in eastern Canada. Genomic analyses identified two populations with greater spatial overlap than previously reported. Variation partitioning revealed that host genetics explained a negligible proportion of microbiota variation compared to environmental factors and fish length, suggesting that ontogenetic shifts in habitat use and resource acquisition influence gut microbiota composition. Several taxa were differentially abundant among fish length categories used as a proxy for diet, including taxa with chitin-degrading potential such as Photobacterium and Lachnospirales, which were enriched in smaller fish known to consume a crustacean-dominated diet. Together, these results indicate that gut microbiota composition in White Hake primarily reflects ecological and life-history processes rather than host population structure. PARAMETERS COLLECTED:Environmental parameters were also collected at most sampling sites, including depth, water temperature, oxygen and salinity levels.PHYSICAL SAMPLE DETAILS:Fin samples were collected to characterize the fish genotypes. Intestine (rectum) samples were collected to study fish gut microbiome.SAMPLING METHODS:In 2022 and 2023, White Hake were sampled during Fisheries and Oceans Canada (DFO) annual bottom trawl ecosystem monitoring surveys.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

All stops in the public transport network managed by the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The Blended Index (BI) is a model which employs multiple potential indicators of drought and excess moisture, such as the Palmer drought index, rolling precipitation amounts and soil moisture, and combines them into a weighted, normalized value between 0 and 100. The inputs and weights used in this model are subject to change periodically as it is optimized to best represent extent, duration and severity of impactful weather conditions. The blended index is deployed as two variations; short term (st) focusing on 1 to 3 months, and long term (lt) focusing on 6 months to 5 years.

The BC Indigenous Business Listings dataset offers a brief summary of Indigenous businesses operating in the province. For each business listed in the dataset, information including the Indigenous owner(s) of the company, location, links to websites as well as primary contact information including email addresses and phone numbers is provided where available. This information is intended to facilitate connections between business owners and consumers, investors, and industry. It is also meant to support an understanding of ownership trends among Indigenous businesses.

The Ontario Hydro Network (OHN) is a provincial medium scale originating from data with regional scales of 1: 10,000 in Southern Ontario, 1: 20,000 in Northern Ontario and 1: 50,000 in the Far North. The shoreline is taken from the OHN - Waterbody data class. This data is used for cartographic purposes and web mapping services. This product requires the use of geographic information system (GIS) software. [Ontario Hydro Network (OHN) User Guide (Word)](https://www.sdc.gov.on.ca/sites/MNRF-PublicDocs/EN/CMID/OHN%20-%20UserGuide.docx)