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.

Summer, Winter Alpine, and Winter Forest-Dwelling habitat model for caribou in the Itcha, Ilgachuz, and Rainbow Mountains of West-Central BC. This habitat model was developed using telemetry from the Itcha-Ilgachuz, Rainbow, and Charlotte Alplands Herds. [Season] field should be used to split the data out into separate summer, winter alpine, and winter forest-dwelling habitat models. Model development is detailed in _Apps, C. D., T. A. Kinley, and J. A. Young. 2001. Multi-scale habitat modeling for woodland caribou in the Itcha, Ilgachuz, and Rainbow mountains of west-central British Columbia.Wildlife Section, Ministry of Water, Land and Air Protection, Williams Lake, British Columbia, Canada_. See also: https://catalogue.data.gov.bc.ca/dataset/caribou-habitat-model-for-the-western-cariboo-region-2017-. __Note: The 2017 habitat model covers a similar area, but does not supersede the 2001 habitat model.__

The Scotian Shelf population of northern bottlenose whales (Hyperoodon ampullatus) is listed as Endangered under Canada’s Species at Risk Act. Partial critical habitat was identified for this population in the Recovery Strategy first published in 2010 (Fisheries and Oceans Canada 2016), and three critical habitat areas were designated along the eastern Scotian Shelf, encompassing the Gully, Shortland Canyon, and Haldimand Canyon (shapefile available online: https://open.canada.ca/data/en/dataset/db177a8c-5d7d-49eb-8290-31e6a45d786c). However, the Recovery Strategy recognized that additional areas may constitute critical habitat for the population and recommended further studies based on acoustic and visual monitoring to assess the importance of inter-canyon areas as foraging habitat and transit corridors for northern bottlenose whales.In a subsequent study of the distribution, movements, and habitat use of northern bottlenose whales on the eastern Scotian Shelf (Stanistreet et al. in press), several sources of data were assessed and additional important habitat was identified in the inter-canyon areas located between the Gully, Shortland Canyon, and Haldimand Canyon (DFO 2020). A summary of the data inputs, analyses, and limitations is provided below.Year-round passive acoustic monitoring conducted with bottom-mounted recorders at two inter-canyon sites from 2012-2014 revealed the presence and foraging activity of northern bottlenose whales in these areas throughout much of the year, with a seasonal peak in acoustic detections during the spring. Detections from acoustic recordings collected during vessel-based surveys provided additional evidence of species occurrence in inter-canyon areas during the summer months. Photo-identification data collected in the Gully, Shortland, and Haldimand canyons between 2001 and 2017 were used to model the residency and movement patterns of northern bottlenose whales within and between the canyons, and demonstrated that individuals regularly moved between the three canyons as well as to and from outside areas. Together, these results indicated a strong degree of connectivity between the Gully, Shortland, and Haldimand canyons, and provided evidence that the inter-canyon areas function as important foraging habitat and movement corridors for Scotian Shelf northern bottlenose whales. The inter-canyon habitat area polygon was delineated using the 500 m depth contour and straight lines connecting the southeast corners of the existing critical habitat areas, but these boundaries are based on limited spatial information on the presence of northern bottlenose whales in deeper waters. More data are needed to determine whether this area fully encompasses important inter-canyon habitat, particularly in regard to the deeper southeastern boundary. Similarly, the full extent of important habitat for Scotian Shelf northern bottlenose whales remains unknown, and potential critical habitat areas outside the canyons and inter-canyon areas on the eastern Scotian Shelf have not been fully assessed. See DFO (2020) for further information.References:DFO. 2020. Assessment of the Distribution, Movements, and Habitat Use of Northern Bottlenose Whales on the Scotian Shelf to Support the Identification of Important Habitat. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2020/008. https://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2020/2020_008-eng.html Fisheries and Oceans Canada. 2016. Recovery Strategy for the Northern Bottlenose Whale, (Hyperoodan ampullatus), Scotian Shelf population, in Atlantic Canadian Waters [Final]. Species at Risk Act Recovery Strategy Series. Fisheries and Oceans Canada, Ottawa. vii + 70 pp. https://www.canada.ca/en/environment-climate-change/services/species-risk-public-registry/recovery-strategies/northern-bottlenose-whale-scotian-shelf.html Stanistreet, J.E., Feyrer, L.J., and Moors-Murphy, H.B. In press. Distribution, movements, and habitat use of northern bottlenose whales (Hyperoodon ampullatus) on the Scotian Shelf. DFO Can. Sci. Advis. Sec. Res. Doc. [https://publications.gc.ca/collections/collection_2022/mpo-dfo/fs70-5/Fs70-5-2021-074-eng.pdf]Cite this data as: Stanistreet, J.E., Feyrer, L.J., and Moors-Murphy, H.B. Data of: Northern bottlenose whale important habitat in inter-canyon areas on the eastern Scotian Shelf. Published: June 2021. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/9fd7d004-970c-11eb-a2f3-1860247f53e3

The purpose of the survey is to document and record habitat types and associated algae and marine invertebrate species in a variety of habitat types. Transect locations are randomly selected throughout the study area, which rotates between the north and south coasts of British Columbia on a biannual basis. Transects are laid perpendicular to the shoreline. A team of two divers swim the transect with data sheets to collect habitat, algae and marine invertebrate data as detailed below in the methods section. Data is keypunched in an MS Access database that can be queried for species observations and environmental information.This dataset includes three tables pulled from the original database containing observations by species, observations by quadrat, and additional header information for each observation. All three tables can be linked by the field HKey. Three lookup tables are included as well, one for algae, one for invertebrates, and one for substrates.

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

This dataset displays the geographic areas within which critical habitat (CH) for terrestrial species at risk, listed on Schedule 1 of the federal Species at Risk Act (SARA), occurs in Canada. Note that this includes only terrestrial species and species for which Environment and Climate Change Canada (ECCC) and Parks Canada Agency (PCA) lead.Under SARA, critical habitat is “the habitat that is necessary for the survival or recovery of a listed wildlife species and that is identified as the species’ critical habitat in the recovery strategy or action plan for the species.”To precisely define what constitutes critical habitat for a particular species it is essential that this geospatial information be considered in conjunction with complementary information provided in a species’ recovery document. Recovery documents are available from the Species at Risk (SAR) Public Registry (https://www.canada.ca/en/environment-climate-change/services/species-risk-public-registry.html) for two posting stages (proposed and final posting). The recovery documents contain important information about the interpretation of the geospatial information, especially regarding the biological and environmental features (“biophysical attributes”) that complete the definition of a species’ critical habitat. Within any defined critical habitat geospatial boundary, not all of the area is necessarily critical habitat.It is important to note that recovery planning documents (and, therefore, critical habitat) may be amended from time to time as new information becomes available, which may occur after a document has been posted as proposed or final on the SAR Public Registry. The SAR Public Registry should always be considered as the main source for critical habitat information. In cases where the data are sensitive, the geographic area within which critical habitat occurs may be represented as grids. These are coarse grids (1, 10, 50 or 100 square kilometres) that serve as indicators to locate critical habitat in the recovery planning document.More detailed information on critical habitat may be made available on a need-to-know basis by contacting Environment and Climate Change Canada – Canadian Wildlife Service at ec.planificationduretablissement-recoveryplanning.ec@canada.ca.The data is current as of the date of the most recent revision.

This data set is a generalized characterization of the offshore and inshore environments of Canada’s Pacific Ocean. Compiled from various sources to depict the biogenic habitats, pelagic habitats, and general bottom types such as offshore and inshore by depth strata.

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)

Effective fisheries and habitat management processes require knowledge of the distribution of areas of high ecological or biological significance. On the Scotian Shelf and Slope, a number of benthic ecologically or biologically significant areas consisting of habitat-forming species such as sponges and deep-water corals have been identified. However, knowledge of their spatial distribution is largely based on targeted surveys that are limited in their spatial extent. We used a species distribution modelling approach called random forest (RF) to predict the probability of occurrence and biomass of sponges, sea pens, and large and small gorgonian corals across the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. We also modelled the rare sponge Vazella pourtalesi, which forms the largest known aggregation of its kind on the Scotian Shelf. We utilized a number of data sources including DFO multispecies trawl catch data and in situ benthic imagery observations. Most models had excellent predictive capacity with cross-validated Area Under the Receiver Operating Characteristic Curve (AUC) values ranging from 0.760 to 0.977. Areas of suitable habitat were identified for each taxon and were contrasted against their known distribution and when applicable, the location of closure areas designated for their protection. Generalized additive models (GAMs) were developed to predict the biomass distribution of each taxonomic group and serve as a comparison to the RF models. The RF and GAM models provided comparable results, although GAMs provided superior predictions of biomass along the continental slope for some taxonomic groups. In the absence of data observations, the results of this study could be used to identify the potential distribution of sensitive benthic taxa for use in fisheries and habitat management applications. These results could also be used to refine significant concentrations of these taxa as identified through the kernel density analyses.Cite this data as: Beazley, Lindsay; Kenchington, Ellen; Murillo-Perez, Javier; Lirette, Camille; Guijarro-Sabaniel, Javier; McMillan, Andrew; Knudby, Anders (2019). Species Distribution Modelling of Corals and Sponges in the Maritimes Region for Use in the Identification of Significant Benthic Areas. Published July 2023. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/356e92f3-5bf3-4810-98b1-3e10cd7742aa

Biophysical or ecosystem mapping is built on the principle that vegetation composition and distribution responds in predictable ways to specific abiotic terrain conditions. Terrain (surficial geology) mapping and subsequent stratification into ecosystem units forms the basis for local-scale biophysical mapping. Biophysical mapping is therefore an integrated system of mapping which describes both terrain conditions (surficial material type, slope, landscape position, drainage and permafrost conditions) and ecological factors (vegetation community and structure, and soil moisture and nutrient regimes).The Watson Lake area was selected for a pilot biophysical mapping project because of imminent resource activities in southeastern Yukon. Local-scale (1:50 000) biophysical mapping was carried out in the 105A/2 NTS map area during 2004 in cooperation with Yukon Environment, Yukon Geological Survey and Cryogeographic Consulting. Analysis of hard copy 1:40 000-scale aerial photographs was conducted to outline preliminary terrain (surficial geology) and ecosystem units. Four weeks of summer field work was then conducted to ground truth the preliminary aerial photograph interpretation and develop a more detailed ecological classification system for southeast Yukon. Following the field season, the corrected mapping was digitized using stereo-georeferenced high-resolution scanned aerial photographs in Microstation Diap Viewer. Subsequent geographic information system (GIS) manipulation was performed in ArcGIS 9.0. Part of the purpose of the project was to develop a methodology for performing biophysical mapping using these technological tools.