The B.C. Conservation Data Centre’s spatial view of publicly available, known locations of species and ecological communities at risk. This spatial view is split into the "Publicly Available Occurrences" layer and "(Extirpated and Historical) Publicly Available Occurrences" layer. The Extirpated and Historical layer includes element occurrences that have a last observation date greater than 40 years ago and element occurrences that are extirpated due to general habitat loss or degradation of the environment in the area. Use the field ‘Rank Description’ to differentiate between Historical and Extirpated element occurrences in this layer. All element occurrences are polygons: the size of the polygon usually reflects the locational uncertainty associated with the source data, represented with varying sized circles. Some polygons may be larger to reflect the actual area covered by the element occurrence. The field "Representational Accuracy" is used to communicate how accurately the polygon reflects the actual area covered by the element. If you do not find an element occurrence in your area of interest, this means there are none currently mapped in the CDC database. The best way to verify whether an area contains a species or ecosystem at risk is to have do a detailed assessment of the property during the appropriate season.

Marine Protected Areas require comprehensive monitoring to ensure objectives are achieved; however, monitoring natural ecosystems at scale is challenged by the biodiversity it aims to measure. Environmental DNA (eDNA) metabarcoding holds promise to address this monitoring challenge. We conducted paired sampling at 54 sites for fish and invertebrate assemblages in the Northwest Atlantic using groundfish trawls and eDNA metabarcoding of benthic seawater using four genetic markers (12S rRNA, 16S rRNA, 18S rRNA, and CO1). Compared to trawling, eDNA detected similar patterns of species turnover, larger estimates of gamma diversity, and smaller estimates of alpha diversity. A total of 63.6% (42/66) of fish species captured by trawling were detected by eDNA, along with an additional 26 species. Of the 24 missed detections by eDNA, 12 were inevitable as they lacked reference sequences. Excluding taxa assigned to higher than species level and those without a species name, 23.6% (17/72) of invertebrate species captured by trawling were detected by CO1, which detected an additional 98 species. We demonstrate that eDNA is capable of detecting patterns of community assemblage and species turnover in an offshore environment, emphasizing its strong potential for a non-invasive, comprehensive, and scalable tool for biodiversity monitoring supporting marine conservation programmes.Cite this data as: Jeffery, N., Rubidge, E., Abbott, C., Westfall, K., Stanley, R. (2024): Data of: eDNA metabarcoding enriches traditional trawl survey data for monitoring biodiversity in the marine environment.Published: August 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/43a91ba7-8025-4330-88db-db14022d729d

Ecologically and Biologically Significant Areas (EBSAs) are areas within Canada's oceans that have been identified through formal scientific assessments as having special biological or ecological significance when compared with the surrounding marine ecosystem.Failure to define an area as an EBSA does not mean that it is unimportant ecologically. All areas serve ecological functions to some extent and require sustainable management. Rather, areas identified as EBSAs should be viewed as the most important areas where, with existing knowledge, regulators and marine users should be particularly risk averse to ensure ecosystems remain healthy and productive.Why are EBSAs identified?EBSA information is used to inform marine planning, including environmental assessment and the siting of marine-based activities, by:- Informing and guiding project-specific or regional environmental assessments;- Informing and guiding industries and regulators in their planning and operations, for example: EBSAs have been acknowledged and referred to (often as "Special Areas" or "Potentially Sensitive Areas") in oil and gas related assessments;- EBSA information has been provided to proponents of submarine cable projects to be used for route planning purposes;- Informing and guiding Integrated Oceans Management (IOM) process within five Large Ocean Management Areas (LOMAs) and twelve marine bioregions;- Serving as a basis for the identification of Areas of Interest (AOIs) and of Marine Protected Areas (MPAs) (individually and in the context of planning bioregional networks of MPAs).How are EBSAs identified?The process used to identify EBSAs is generally comprised of two phases. The first phase involves compiling scientific data and knowledge of a marine area's ecosystems - notably fish species, marine mammals, sea birds, marine flora, marine productivity, physical and chemical conditions and geology. "Knowledge" includes experiential knowledge of long-time uses of the areas. In some cases (e.g., in the Arctic), substantial efforts are taken to collect traditional knowledge on ecosystems and environmental conditions from community members, fish harvests, hunters and individuals whose knowledge of the study area complement often helps fill scientific data gaps.In the second phase, the available information for a marine area (e.g. a bioregion) is assessed against five nationally-established science-based criteria including:- Uniqueness: How distinct is the ecosystem of an area compared to surrounding ones?- Aggregation: Whether or not species populate or convene to the study area?- Fitness consequence: How critical the area is to the life history of the species that use it (e.g. is it a spawning or feeding ground)?- Naturalness: How pristine or disturbed by human activities is the study area?- Resilience: What is the ability of the ecosystem to bounce back if it is disturbed?Progress to date and next stepsEBSAs have been identified for large portions of Canada's Atlantic and Pacific Oceans as well as most of the Arctic oceans. EBSAs will continue to be identified in priority areas as resources become available to carry out the process. The boundaries or locations of existing EBSAs may be modified to reflect both new knowledge and changing environmental conditions.

Broad Ecosystem Units were mapped using predictive modeling methods from various data sources (ranging from 1:50,000 to 1:250,000 in scale) and are referenced to the CanVec digital spatial framework (1:50,000). Broad Ecosystem Units (BEU) are a level in the Yukon bioclimate ecosystem classification system that represents areas with similar broad vegetation communities, terrain type (soils and topography) within bioclimate zones. Broad Ecosystem Units are described in the accompanying report "Regional Ecosystems of West-Central Yukon, Part 1: Ecosystem descriptions ".The intended application for mapped broad ecosystem units is 1:100,000 or smaller (1:100,000 - 1:250,000 scale) - interpretations derived from the map products should not be applied at more detailed scales, even though the resultant 30m raster map allows users to view results at more detailed resolutions. With new information, boundaries and designations of Broad Ecosystem Units can change. Updates to Broad Ecosystem Units occur only periodically. For the most current information, or if you have questions, please contact the Ecological and Landscape Classification Program (ELC@yukon.ca).Distributed 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)

SEI_Polygons contains Sensitive Ecosystems Inventory polygons with key and amalgamated (concatenated) attributes derived from the RISC (Resource Inventory Standards Committee) standard attributes. SEI identifies and maps rare and fragile terrestrial ecosystems. Ecosystems mapped may include (but are not limited to) older forests, woodlands, coastal bluffs, herbaceous and sparsely vegetated ecosystems, grasslands, riparian ecosystems and wetlands. SEI methods include manual air photo interpretation or theming of other Ecosystem Mapping, each supported by selective field checking. This layer is derived from the STE_TEI_ATTRIBUTE_POLYS_SP layer by filtering on the PROJECT_TYPE attribute. Project types include: SEI, TEMSEI, TEMSET, and SEIWHR. Current version: v11 (published on 2024-10-03) Previous versions: v10 (published on 2023-11-14), v9 (published on 2023-03-01), v8 (published on 2016-09-01)

Sensitive Ecosystems Inventory (SEI) project boundaries (study areas) contains attributes describing each project (project level metadata), and includes links to the locations of other data associated with the project (e.g. reports, polygon datasets, plot files). SEI identifies and maps rare and fragile terrestrial ecosystems in a given area for the purpose of encouraging land-use decisions that will ensure the continued integrity of these ecosystems. This layer is derived from the STE_TEI_PROJECT_BOUNDARIES_SP layer by filtering on the PROJECT_TYPE attribute. Project types include: SEI, TEMSEI, TEMSET, TEMSEW and SEIWHR. Current version: v11 (published on 2024-10-03) Previous versions: v10 (published on 2023-11-14), v9 (published on 2023-03-01), v8 (published on 2016-09-01)

STE_TEI_ATTRIBUTE_POLYS_SP contains Terrestrial Ecosystem Information (TEI) polygons with key and amalgamated (concatenated) attributes derived from the RISC (Resource Inventory Standards Committee) standard attributes. These describe the physical and biological characteristics of ecosystems at a landscape level. TEI currently includes Terrestrial Ecosystem Mapping (TEM), Predictive Ecosystem Mapping (PEM), Sensitive Ecosystems Inventory (SEI), Terrain Mapping (TER) and Soil Mapping (SOIL). Mapping methods include manual air photo interpretation and modeling supported by limited field checking. Current version: v11 (published on 2024-10-03) Previous versions: v10 (published on 2023-11-14), v9 (published on 2023-03-01), v8 (published on 2016-09-01)

The dataset has been used for the Great Lakes Conservation Blueprint Project for Aquatic Biodiversity. It can be used for: * research and aquatic species inventories * environmental impact and monitoring * watershed based resource planning and management * fisheries and other aquatic analysis Official GEO title: Aquatic Ecosystems Classification: Great Lakes Basin - Coast, Streams, Lakes and Wetlands

Bivalve aquaculture has direct and indirect effects on plankton communities, which are highly sensitive to short-term (seasonal, interannual) and long-term climate changes, although how these dynamics alter aquaculture ecosystem interactions is poorly understood. Here, we investigate seasonal patterns in plankton abundance and community structure spanning several size fractions from 0.2 µm up to 5 mm, in a deep aquaculture embayment in northeast Newfoundland, Canada. Using flow cytometry and FlowCam imaging, we observed a clear seasonal relationship between fraction sizes driven by water column stratification (freshwater input, nutrient availability, light availability, water temperature). Plankton abundance decreased proportionally with increasing size fraction, aligning with size spectra theory. Within the bay, greater mesozooplankton abundance, and a greater relative abundance of copepods, was observed closest to the aquaculture lease. No significant spatial effect was observed for phytoplankton composition. While the months of August to October showed statistically similar plankton composition and size spectra slopes (i.e., food chain efficiency) and could be used for interannual variability comparisons of plankton composition, sampling for longer periods could capture long-term phenological shifts in plankton abundance and composition related to various processes, including climate change. Conclusions provide guidance on optimal sampling to monitor and assess aquaculture pathways of effects.Cite this data as: Sharpe H, Lacoursière-Roussel A, Gallardi D (2024). Ecological insight of seasonal plankton succession to monitor shellfish aquaculture ecosystem interactions. Version 3.2. Fisheries and Oceans Canada. Sampling event dataset. https://doi.org/10.25607/2ujdvh

Woods and forest corridor of interest, exceptional forest complex and protected area under the revised urban and development plan of the City of Laval.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**