Vegetation biophysical parameters correspond to physical properties of vegetation structure (e.g. density, height, biomass), biochemistry (e.g. chlorophyll and water content) or energy exchange (e.g. albedo, temperature). These parameters have been identified by the Global Climate Observing System as an essential climate variable required for ecosystem, weather and climate modelling and monitoring. The Canada wide products are derived from systematically acquired satellite imagery with spatial resolution from 10m to 30m and provided as monthly temporal or peak-season composites due to cloud cover. Products are derived applying algorithms developed at Canada Centre for Remote Sensing (NRCan) to Copernicus Sentinel 2 satellite imagery.Select a related product first to view content.

Vegetation biophysical parameters correspond to physical properties of vegetation structure (e.g. density, height, biomass), biochemistry (e.g. chlorophyll and water content) or eneregy exchange (e.g. albedo, temperature). The Canada wide products are derived from systematically acquired satellite imagery with spatial resolution from 10m to 30m and provided as monthly temporal or peak-season composites due to cloud cover. Version 0 corresponds to products derived using the European Space Agency Simplified Level 2 Prototype Processor. This collection includes Peak Season Fraction of Vegetation Cover of Canada from Medium Resolution Satellite Imagery and Peak Season Leaf Area Index of Canada from Medium Resolution Satellite Imagery data sets. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

Vegetation biophysical parameters correspond to physical properties of vegetation structure (e.g. density, height, biomass), biochemistry (e.g. chlorophyll and water content) or eneregy exchange (e.g. albedo, temperature). The Canada wide products are derived from systematically acquired satellite imagery with spatial resolution from 10m to 30m and provided as monthly temporal or peak-season composites due to cloud cover. Version 0 corresponds to products derived using the European Space Agency Simplified Level 2 Prototype Processor. This collection includes Peak Season Fraction of Vegetation Cover of Canada from Medium Resolution Satellite Imagery and Peak Season Leaf Area Index of Canada from Medium Resolution Satellite Imagery data sets. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

Vegetation biophysical parameters correspond to physical properties of vegetation structure (e.g. density, height, biomass), biochemistry (e.g. chlorophyll and water content) or eneregy exchange (e.g. albedo, temperature). The Canada wide products are derived from systematically acquired satellite imagery with spatial resolution from 10m to 30m and provided as monthly temporal or peak-season composites due to cloud cover. Version 0 corresponds to products derived using the European Space Agency Simplified Level 2 Prototype Processor. This collection includes Peak Season Fraction of Vegetation Cover of Canada from Medium Resolution Satellite Imagery and Peak Season Leaf Area Index of Canada from Medium Resolution Satellite Imagery data sets. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

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.

Biological samples of Geoduck Clams have been collected during surveys in British Columbia as part of the broader survey objectives of determining Geoduck density, distribution and population structure. Samples of Geoducks were collected from 41 locations throughout British Columbia between 1993 and 2002. Clams were measured for total weight, shell length, shell weight and were aged. Biological parameters are presented here for individual clams sampled. See Bureau D., W. Hajas, N.W. Surry, C.M. Hand, G. Dovey and A. Campbell. 2002. Age, size structure and growth parameters of Geoducks (Panopea abrupta, Conrad 1849) from 34 locations in British Columbia sampled between 1993 and 2000. Can Tech. Rep. Fish. Aquat. Sci. 2413: 84 p. and Bureau D., W. Hajas, C.M. Hand and G. Dovey. 2003. Age, size structure and growth parameters of Geoducks (Panopea abrupta, Conrad 1849) from seven locations in British Columbia sampled in 2001 and 2002. Can. Tech. Rep. Fish. Aquat. Sci. 2494: 29 p.

This record contains information on the samples collected and the intended parameters for analysis from sediment cores collected as part of this project including bacteria, chemistry, stable isotopes, fatty acids, or meiofauna.

Yukon Biophysical Plot locations are derived from the Yukon Biophysical Information System (YBIS) database, which is the Government of Yukon's repository for storing biophysical data . Data contain a combination of site, soil and vegetation information which are collected by multiple agencies to support vegetation inventory, habitat assessment and baseline ecosystem products collected from 1975 - 2018. Data are collected and input into the database using standardized biophysical field forms as per the "Field Manual for Describing Yukon Ecosystems" data collection standards. Data contributors include Government of Yukon, Government of Canada, First Nations Governments, private contractors, academia and the public. Location accuracy of plot data may vary based on the project year and location collection method. YBIS is an active database, which is subject to periodic updates and revisions. Because of this, the onus is on the end-user to ensure that they are using the most current version of the data. Although every effort has been made to ensure the correctness of the data, there still may be errors. Please report errors in the data to the Custodian.Contact Information:Ecological and Landscape Classification (ELC) Coordinator, elc@yukon.ca Ecological and Landscape Classification Program, Fish and Wildlife Branch, Department of Environment Government of Yukon, Box 2703, Whitehorse, Yukon Y1A 2C6 ph. (867) 667-3081Distributed 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)

Bathymetry line data was collected to assess fish habitat in Ontario. Spot depths (bathymetry points) were used to measure the depth contours, which function like isobars to show lines of constant depth. Their density and positional accuracies vary depending on the survey style and parameters. This data should never be used for navigation.

This dataset represents the Environmental and Socio-economic Assessments (ESA) submitted to the Canada Energy Regulator (CER). The CER has made this and other ESAs available through an online search tool called BERDI (Biophysical Socio-Economic Regional Data and Information). Data extraction methodology is available on the BERDI website. Pipelines represented in this layer include a start and end point.