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We have found 134 datasets for the keyword "substrat". You can continue exploring the search results in the list below.
Datasets: 105,253
Contributors: 42
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134 Datasets, Page 1 of 14
Benthos monitoring
The objective of benthos monitoring is to know the state of benthic macroinvertebrate communities in rivers according, in particular, to the composition of the substrate and the type of flow. Information on benthic macroinvertebrate samples collected at benthos monitoring stations is classified according to the benthos health index: iSBG for coarse-substrate streams and iSBM for soft-substrate streams. The Benthos Health Index (ISB) is a multimetric index based on benthic macroinvertebrates that assesses the biotic integrity of shallow streams. The benthos monitoring dataset includes a layer of sampling stations sampled between 2003 and 2023 and a layer of drainage areas for each of the types of substrate, either coarse or loose. The drainage area attribute table also provides a compilation of land use by category for the last year available at the time of data production, i.e. the year 2020.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
A substrate classification for the Inshore Scotian Shelf and Bay of Fundy, Maritimes Region
A coastal surficial substrate layer for the coastal Scotian Shelf and Bay of Fundy. To create the layer, previous geological characterizations from NRCan were translated into consistent substrate and habitat characterizations; including surficial grain size and primary habitat type. In areas where no geological description was available, data including digital elevation models and substrate samples from NRCan, CHS and DFO Science were interpreted to produce a regional scale substrate and habitat characterization. Each characterization in the layer was given a ranking of confidence and original data resolution to ensure that decision makers are informed of the quality and scale of data that went into each interpretation.Cite this data as: Greenlaw, M., Harvey, C. Data of: A substrate classification for the Inshore Scotian Shelf and Bay of Fundy, Maritimes Region. Published: March 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/f2c493e4-ceaa-11eb-be59-1860247f53e3
Shallow substrate model (20m) of the Pacific Canadian coast
The shallow substrate bottom type model was created to support near shore habitat modelling. Data sources include both available observations of bottom type and environmental predictor layers including oceanographic layers, fetch, and bathymetry and its derivatives. Using weighted random forest classification from the ranger R package, the relationship between observed bottom type and predictor layers can be determined, allowing bottom type to be classified across the study areas. The predicted raster files are classified as follows: 1) Rock, 2) Mixed, 3) Sand, 4) MudThe categorical substrate model domains are restricted to the extent of the input bathymetry layers (see data sources) which is 5 km from the 50 m depth contour.
Glacial Drift Thickness
This dataset represents surface to bedrock isopach (thickness in metres) map of glacial drift for the Province of Saskatchewan at 1:1 000 000 scale.This dataset represents surface to bedrock isopach (thickness in metres) map of glacial drift at 1:1 000 000 scale. This 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.
A Soft-Shelled Clam (Mya arenaria) Habitat Suitability Model For The DFO Maritimes Region
The data in this layer represents habitat suitability of soft-shelled clams (Mya arenaria) in the DFO Maritimes region, and was developed using an interdepartmental approach. Substrate classification data as well as bathymetric data for the Region were used to identify potential habitat for soft-shelled clams. Substrates identified as suitable included: sand, mud, sand and mud (Greenlaw, 2022). Contours (0m and 70m) from GEBCO bathymetric data were used to isolate depths between which soft-shelled clams are present. At this stage, a polygon reflecting soft substrates from 0-70m was created as "Suitable". A "Not Suitable" layer was similarly created using the substrates: boulders, continuous bedrock, discontinuous bedrock, gravel, mixed sediment, sand and gravel.To digitally validate the model, the Regional shoreline was divided into subsectors (developed by Environment and Climate Change Canada for the Canadian Shellfish Sanitation Program). Data from DFO (clam harvesting intensity) as well as Conservation and Protection (clam harvesting infraction locations) were used to established species presence within each sub-sector. If there had been any harvesting activity, legal or illegal, in an individual subsector, it was considered "Suitable and Validated". Merged into one final product, the model includes areas that are "Not Suitable", "Suitable", as well as "Suitable and Validated" for soft-shelled clam habitat.Cite this data as: Harvey, C., Vincent, M., Greyson, P., Hamer, A. (2024) Data of: A Soft-Shelled Clam (Mya arenaria) Habitat Suitability Model For The DFO Maritimes Region.Published: January 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/c76f7813-d802-4b31-8ebe-476f8a7cacf2
Deep substrate model (100m) of the Pacific Canadian shelf
This deep water substrate bottom type model was created to aid in habitat modeling, and to complement the nearshore bottom patches. It was created from a combination of bathymetrically-derived layers in addition to bottom type observations. Using random forest classification, the relationship between observed substrates and bathymetric derivatives was estimated across the entire area of interest. The raster is categorized into: 1) Rock, 2) Mixed, 3) Sand, 4) Mud
Data of eelgrass (Zostera marina) occurrences in Nova Scotia
This is a collection of eelgrass (Zostera marina) presence and absence records collected between 2009-2025 in coastal waters in Nova Scotia, Canada. The data collection has been collated by the Coastal Benthic Ecology Lab (CBEL) at the Bedford Institute of Oceanography, Fisheries and Oceans Canada (DFO) under the supervision of Dr. Melisa Wong. Records include those from various research groups at DFO, Nova Scotia provincial departments, academia, and non-profit organizations.Data were collected using various methods including field measurements of eelgrass presence or absence via boat, snorkel and drop camera video transects, surface observations, and various sample collections (including plants, core, sediment, trawl, pop net, seine, etc.). Please see specific record references for associated metadata and detailed descriptions of the methods for eelgrass occurrence data collection. Where available, water depth (m) and substrate type (rock, soft, or mixed) are provided. The substrate type (hard substrate, mixed, mud, rocky, sand, or various combinations) used for the species distribution model published by O’Brien et al. 2022 is also provided where available.The data owner, data source (i.e., reference(s)), and use of the data in the species distribution model of O’Brien et al. 2022 are provided. All records from sources external to DFO are included under data sharing agreements or permission from the data owner.Cite this data as: Wong, M.C., Fraser, M., Thomson, J. A., O’Brien, J. Data of eelgrass (Zostera marina) occurrences in Nova Scotia. Published: April 2026. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS.
Bedrock Geology
British Columbia Digital Geology is the data source used for the seamless province-wide, up-to-date, and detailed bedrock geology. The bedrock geology is standardized with consistent stratigraphic code and geometries, and integrates all details of compilations from 1:50,000 to 1:250,000. The latest release (Open File 2017-8) is maintained by a geospatial frame data model, which consists of attributed geological contacts and faults as linework, and outcrops or centroids as points attributed with bedrock information. Techniques are used to simplify the integration process and shorten the timeframe from field mapping, compilation, integration, to data delivery. The release also contains: tables for geological units and colours; ESRI layer files containing bedrock colour symbols; and a map of British Columbia illustrating the suggested colour theme for the bedrock polygons. Related data sets are Geology Faults and Quaternary Alluvium and Cover. Bedrock Geology is interactive with other geoscience data on MapPlace and MapPlace 2 and is available for download in shapefile format.
Epifauna Diversity on Dockside Surface Perimeters in Burrard Inlet and Fraser River Delta, British Columbia
These data sets provide information pertaining to epifauna and substrate estimates collected at dockside perimeters of floating docks located in Burrard Inlet and Fraser River Delta, British Columbia, between August and November, 2020. Data sets were compiled and formatted by Meagan Mak.Epifauna diversity was examined along surface perimeters of floating docks in Burrard Inlet and Fraser River Delta in southwestern British Columbia. Diversity estimates were obtained from video surveys collected over three depth-intervals: 1) Splash zone (SZ): depth-interval directly 15-cm above air-water interface; 2) Subsurface zone (SSZ): depth-interval (0-21 cm) below air-water interface; and 3) Deep-water zone (DZ): depth-interval below the SSZ (21-41 cm). Dock substrate consisted of combinations of wood, concrete, tires, plastic-floats, and metal, while epifauna and epiflora included anemones, tunicates, sponge, tube-worms, sea stars, bivalves, crabs, nudibranchs, urchins, barnacles, limpets, chitons, isopods, macroalgae and seagrass. Mussels ranged between 46% and 95% coverage across docks (median: 93%), while frequency of occurrence ranged between 85% and 100% (median: 99%), providing a biological-based substrate for other epifauna. The splash-zone consisted of outcropped mussels, encroached macroalgae from the waterline, and invertebrates above the waterline (limpets, chiton). If present, Ulva spp. typically formed a consistent narrow band (2-3 cm) above the waterline across all docks. Benthic (pipefish, sculpin) and pelagic (perch) fish were associated with epifaunal coverage and pelagic (open-water medium) settings. The Coast Guard Sea Island dock may experience episodic low-salinity intrusions supporting marine organisms at this site (ochre star, sculpin, limpet).
Bedrock map index
A Yukon-wide compilation of map footprints and associated citation data for 191 published bedrock geology maps that were incorporated into the Yukon bedrock geology compilation. The maps were originally produced by the GSC, YGS, Yukon Government and various universities at various scales ranging from 1:10,000 to 1:500,000. Attribute data for each map footprint includes: year, scale, author, publisher, map number, NTS sheet and title.Distributed from [GeoYukon](https://yukon.ca/en/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)
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