“Automatically Extracted Buildings” is a raw digital product in vector format created by NRCan. The feature classes of this product delineate polygonal building footprints automatically extracted from airborne Lidar data, high-resolution optical imagery or other sources.The first feature class, Automatically Extracted Buildings by acquisition source, contains building footprints delivered according to the spatial extent of each source dataset used for extraction. When the spatial extents of acquisition sources overlap, footprints for the same building may therefore be duplicated in this class.The second feature class, Optimized Buildings Layer, is an assembled and harmonized layer derived from the buildings by acquisition source. Its objective is to provide a unique representation of each building footprint by removing duplicates and resolving overlaps between sources.

Marine classification schemes based on abiotic surrogates often inform regional marine conservation planning in lieu of detailed biological data. However, theses chemes may poorly represent ecologically relevant biological patterns required for effective design and management strategies. We used a community-level modeling approach to characterize and delineate representative mesoscale (tens to thousands of kilometers) assemblages of demersal fish and benthic invertebrates in the North-west Atlantic. Hierarchical clustering of species occurrence data from four regional annual multispecies trawl surveys revealed three to six groupings (predominant assemblage types) in each survey region, broadly associated with geomorphic and oceanographic features. Indicator analyses identified 3–34 emblematic taxa of each assemblage type. Random forest classifications accurately predicted assemblage dis-tributions from environmental covariates (AUC > 0.95) and identified thermal limits (annual minimum and maximum bottom temperatures) as important pre-dictors of distribution in each region. Using forecasted oceanographic conditions for the year 2075 and a regional classification model, we projected assemblage dis-tributions in the southernmost bioregion (Scotian Shelf-Bay of Fundy) under ahigh emissions climate scenario (RCP 8.5). Range expansions to the north eastare projected for assemblages associated with warmer and shallower waters of the Western Scotian Shelf over the 21st century as thermal habitat on the rela-tively cooler Eastern Scotian Shelf becomes more favorable. Community-level modeling provides a biotic-informed approach for identifying broadscale ecolog-ical structure required for the design and management of ecologically coherent, representative, well-connected networks of Marine Protected Areas. When com-bined with oceanographic forecasts, this modeling approach provides a spatial tool for assessing sensitivity and resilience to climate change, which can improve conservation planning, monitoring, and adaptive management.Cite this data as: O'Brien, J.M., Stanley, R.R.E., Jeffery, N.W., Heaslip, S.W., DiBacco, C., and Wang, Z. Demersal fish and benthic invertebrate assemblages in the Northwest Atlantic.Published: December 2024. Coastal Ecosystems Science Division, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS.https://open.canada.ca/data/en/dataset/14d55ea5-b17d-478c-b9ee-6a7c04439d2b

Catch, effort, location (latitude and longitude), and associated biological data from the Hecate Strait Multispecies Assemblage Bottom Trawl Surveys in Hecate Strait, British Columbia.Introduction The Hecate Strait Multispecies Assemblage Bottom Trawl survey series consists of twelve surveys that were conducted from 1984 to 2003 by the Pacific Biological Station, Fisheries and Oceans Canada. The main objective of this survey series was to collect detailed catch and biological data on species assemblages in order to develop an ecological basis for mixed species stock assessment in Hecate Strait. These surveys also provided abundance indices for individual species and were a source of information on recruitment. The surveys were conducted using a combination of charter vessels and two Canadian Coast Guard Research Vessels, the R/V G.B. Reed and R/V W.E. Ricker. To determine haul locations, a grid of 19 km² (10 nautical miles²) blocks were used with an attempt made to establish one trawl site within each 18 metre depth interval within each block. The 1984 survey involved one chartered and one research vessel; all other surveys were single vessel surveys. The Hecate Strait Multispecies Assemblage Bottom Trawl survey series surveyed Pacific Fishery Management areas 4, 5, and 101 to 106. A total of 1,111 number of tows were made with a Yankee 36 trawl net. This survey series is the predecessor for the present day Hecate Strait Synoptic Bottom Trawl Survey and represents one of the longest running time series of fisheries independent groundfish surveys on the west coast.For further details about the Hecate Strait Multispecies assemblage bottom trawl survey series, a list of reports can be found in the supporting documents section.EffortThis table contains information about the survey trips and fishing events (trawl tows/sets) that are part of this survey series. Trip-level information includes the year the survey took place, a unique trip identifier, the vessel that conducted the survey, and the trip start and end dates (the dates the vessel was away from the dock conducting the survey). Set-level information includes the date, time, location, and depth that fishing took place, as well as information that can be used to calculate fishing effort (duration) and swept area. All successful fishing events are included, regardless of what was caught. CatchThis table contains the catch information from successful fishing events. Catches are identified to species or to the lowest taxonomic level possible. Most catches are weighed, but some are too small (“trace” amounts) or too large (e.g. very large Big Skate). The unique trip identifier and set number are included so that catches can be related to the fishing event information (including capture location). BiologyThis table contains the available biological data for catches which were sampled. Data may include any or all of length, sex, weight, age. Different length types are measured depending on the species. Age structures are collected when possible for species where validated aging methods exist and are archived until required for an assessment; therefore, all existing structures have not been aged at this time. The unique trip identifier and set number are included so that samples can be related to the fishing event and catch information.BiomassThis table contains relative biomass indices of species that have been captured in every survey of the time series. The coefficient of variation and bootstrapped 95% confidence intervals are provided for each index. The groundfish data synopsis report (Anderson et al. 2019) provides an explanation of how the relative biomass indices are derived.

This dataset represents the digital compilation of the Mineral Assessment Underground surveys of the Province of Saskatchewan.This dataset represents the digital compilation of the Mineral Assessment Underground surveys of the Province of Saskatchewan.  This data shows Mineral Assessment Work Catalogue: Outlines of areas and descriptions of work submitted for mineral assessment credits (Underground surveys). This is an ongoing assemblage of mineral assessment airborne surveys. The data was created as a file geodatabase feature class and output for public distribution. **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. 

This dataset represents the digital compilation of the Mineral Assessment Ground surveys of the Province of Saskatchewan.This dataset represents the digital compilation of the Mineral Assessment Ground surveys of the Province of Saskatchewan.  This data shows Mineral Assessment Work Catalogue: Outlines of areas and descriptions of work submitted for mineral assessment credits (Ground surveys). This is an ongoing assemblage of mineral assessment ground surveys. The data was created as a file geodatabase feature class and output for public distribution. **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. 

The 2023 mapping of potential wetlands in Quebec (CMHPQ) 2023, released by the Directorate of Ecological Knowledge (DCE), provides up-to-date information on the potential presence of wetlands for the entire province of Quebec. In particular, version 2023 contains the classification of potentially humid geographical entities according to a selected typology and the assignment of a level of confidence associated with each entity and integrates new data sources. This mapping is an aggregation of different databases produced for other purposes and at different scales. The result of this assembly depends on the precision and accuracy of each of the data sources used. This data must be used while remaining vigilant with regard to their potential and limitations.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This dataset represents the digital compilation of the Mineral Assessment Airborne surveys of the Province of Saskatchewan.This dataset represents the digital compilation of the Mineral Assessment Airborne surveys of the Province of Saskatchewan.  This data shows Mineral Assessment Work Catalogue: Outlines of areas and descriptions of work submitted for mineral assessment credits (Airborne surveys). This is an ongoing assemblage of mineral assessment airborne surveys. The data was created as a file geodatabase feature class and output for public distribution.**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.

The Fish Management Zone dataset is comprised of all the polygons that represent the Fish Management Zones in Alberta. Fish Management Zone is an area having its own unique assemblage of water bodies, species of game fish and management regimes.

Description:Biophysical Units: Under the Pacific Marine Ecological Classification System (PMECS; DFO 2016; Rubidge et al. 2016), biophysical units are areas of distinct physiographic and oceanographic conditions and processes that shape species composition at spatial extents of 1000s of km. Geomorphic units:Geomorphic units or geozones are discrete geomorphological structures at the scale of 100s of km that are assumed to have distinctive biological assemblages (e.g., plateaus, ridges, seamounts, canyons). Although the spatial scale of geomorphic units is nested within biophysical units, a single geomorphic unit such as a trough may span more than one biophysical unit. The following 5 layers are included in this geodatabase:1. Biophysical_Units_L4A - Predicted PMECS Biophysical Units (Level 4A) output from the random forest analysis2. Biophysical_Units_L4B - Predicted PMECS Biophysical Units (Level 4B) output from the random forest analysis3. Biophysical_Units_ProbAssign_L4AB - Layer showing the probability that a grid cell was assigned to a given biophysical unit in the final random forest predictive modelling step4. Cluster_L4AB - Layer showing the output of species assemblage cluster analysis5. Geomorphic_Units - Geomorphic units for the BC coast that combines geomorphic units produced by Rubidge et al. 2016) and Proudfoot and Robb (2022).Methods:Biophysical Units:Rubidge et al. (2016) used a two-step process to identify biophysical units in British Columbia. First, a cluster analysis based on the similarity of species composition was used to group sites with similar species into distinct biological assemblages. Second, a random forest analysis was used to identify environmental correlates of the biological assemblages identified by the cluster analysis and to predict and assign the biological assemblage present in areas with too few biological data. Two different similarity thresholds were used to identify two levels (4A, 4B) of biophysical units; see Rubidge et al. (2016) for details. Indicator species for each assemblage (biophysical unit) were also identified.Geomorphic units:Rubidge et al. (2016) used the benthic terrain modeller (BTM) tool with broad and fine-scale benthic positioning index (BPI) parameters to define geomorphic units on the continental shelf in the Northern Shelf Bioregion and the continental slope in both the Northern Shelf Bioregion and Southern Shelf Bioregion. In 2022, geomorphic units were produced for the Strait of Georgia and Southern Shelf Bioregions following the same methods as Rubidge et al. (2016) (Proudfoot and Robb 2022). The geomorphic units produced as part of the PMECS process were merged with the geomorphic units produced for the Strait of Georgia and Southern Shelf bioregions to produce a continuous spatial data product representing geomorphic units for the Canadian Pacific continental shelf and slope. After merging, the geomorphic units produced in 2016 were unchanged (i.e., they are consistent with the original geomorphic units described in Rubidge et al. 2016).Data Sources:From Rubidge et al. (2016): Species data was taken from Fisheries and Oceans Canada (DFO) standardized fisheries-independent research surveys: groundfish trawl and long-line (2003-2013), Tanner Crab trawl and trap (2000–2006), and Dungeness Crab trap (2000–2014). Environmental data came from NASA, the Canadian Hydrographic Service, Fisheries and Oceans Canada, Bio-ORACLE, and elsewhere (details in Rubidge et al. 2016). From Proudfoot and Robb (2022): bathymetry data came from Natural Resources Canada (details in Proudfoot and Robb 2022).Uncertainties:The data is intended for use at the bioregional scale, and caution should be used for finer-scale analyses.

Industrial sectors.attributs:ID - Unique identifierName - Industrial park name**This third party metadata element was translated using an automated translation tool (Amazon Translate).**