Boundaries identifying similar behavioural ecotypes and sub-populations of Grizzly bears. This dataset contains versions from multiple years. From 2018 on, NatureServe conservation concern ranking categories (e.g., Very Low, Low, Moderate, High, Extreme Concern) supersede the pre-2018 population status categories (e.g., Viable, Threatened, Extirpated) contained in the field STATUS. NatureServe conservation concern ranking categories reflect population size and trend, genetic and demographic isolation, as well as threats to bears and their habitats. The NatureServe conservation concern ranking fields are named CONSERVATION_CONCERN_RANK and CONSERVATION_CONCERN_DESC. Please view the attached PDF file for a summary of changes to this dataset from 2012 onward. To download only the 2018 units, in the link below, select the "Export" tab, then select the "Provincial Layer Download" button: https://maps.gov.bc.ca/ess/hm/imap4m/?catalogLayers=7744,7745 Grizzly Bear Conservation Ranking results table is available here: https://catalogue.data.gov.bc.ca/dataset/e08876a1-3f9c-46bf-b69a-3d88de1da725 Grizzly Bear population estimates from various years are available here: https://catalogue.data.gov.bc.ca/dataset/2bf91935-9158-4f77-9c2c-4310480e6c29 Grizzly Bear reports are available here: https://www2.gov.bc.ca/gov/content/environment/plants-animals-ecosystems/wildlife/wildlife-conservation/grizzly-bear

An Element Occurrence (EO) is an area of land and/or water in which a species or ecological community is, or was, present. An Element is either a species (or subspecies taxa) or an ecological community, the Occurrence is the documented location. The EO concept is part of NatureServe methodology. This methodology is used throughout the NatureServe network. EOs are created based on the Element Occurrence Data Standard and are a derived product developed from submitted observations. An EO should have practical conservation value for the Element as evidenced by potential continued (or historical) presence and/or regular recurrence at a given location. For Species Elements, the EO often corresponds with the local population, but when appropriate may be a portion of a population (e.g., for long distance dispersers) or may be a group of nearby populations (e.g., metapopulation). For Ecological Community Elements, the EO may represent a stand or patch of a natural community, or a cluster of stands or patches of a natural community. This dataset contains Non-sensitive EOs. Non-Sensitive EOs are locations (i.e. occurrences) of species or communities that are rare (or of conservation concern for some other reason) and for which there are no restrictions regarding public access to location data (beyond agreeing to the Terms and Conditions detailed below). This data updates on a daily basis.

An Element Occurrence (EO) is an area of land and/or water in which a species or ecological community is, or was, present. An Element is either a species (or subspecies taxa) or an ecological community, the Occurrence is the documented location. The EO concept is part of NatureServe methodology. This methodology is used throughout the NatureServe network. EOs are created based on the Element Occurrence Data Standard and are a derived product developed from submitted observations. An EO should have practical conservation value for the Element as evidenced by potential continued (or historical) presence and/or regular recurrence at a given location. For Species Elements, the EO often corresponds with the local population, but when appropriate may be a portion of a population (e.g., for long distance dispersers) or may be a group of nearby populations (e.g., metapopulation). For Ecological Community Elements, the EO may represent a stand or patch of a natural community, or a cluster of stands or patches of a natural community. This dataset contains Sensitive EOs. Sensitive EOs are occurrences of species that are rare (or of conservation concern) and in these cases the precise location details cannot be distributed without due cause. In most cases these locations are not freely available because the species are legally listed (for example, under Schedule 1 of the Species at Risk Act) or are of particular concern to the Alberta government, thus Sensitive EO data in this layer is hazed (generalized) to the Alberta Township System Township (ATS) polygons (v4.1). This data updates on a daily basis.

Ecological Reserves are part of a network of Designated Areas. The goal of the network is to create and maintain a comprehensive, dynamic and accessible data set (digital map) that accurately defines land areas in Saskatchewan that have various levelUnique ecological reserves that are designed to protect representative areas of natural landscapes and to conserve biological diversity.

Wall-to-wall map of water bodies across Canada's forested ecosystems for the year 2022, derived from the "water" class of the annual Virtual Land Cover of Engine (VLCE) product. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The VLCE maps are based on Landsat image time-series composites and represent annual land cover classifications from 1984 to 2022 at a spatial resolution of 30 m. The classification process integrates forest change information and ancillary topographic and hydrologic variables, applying a regional modeling framework based on a 150x150 km tiling system ( Hermosilla et al., 2022). Training data are drawn from multiple land cover sources and selected proportionally to land cover distributions using a distance-weighted approach. Classifications are refined over time using a Hidden Markov Model to ensure consistency and reduce classification noise between years.Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C. 2022. Land cover classification in an era of big and open data: Optimizing localized implementation and training data selection to improve mapping outcomes. Remote Sensing of Environment. 268, 112780. https://doi.org/10.1016/j.rse.2021.112780. ( Hermosilla et al., 2022)Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W. 2018. Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series. Canadian Journal of Remote Sensing. 44(1) 67-87. https://doi.org/10.1080/07038992.2018.1437719.( Hermosilla et al., 2018)

Species characterization by environmental DNA (eDNA) is a method that allows the use of DNA released into the environment by organisms from various sources (secretions, faeces, gametes, tissues, etc.). It is a complementary tool to standard sampling methods for the identification of biodiversity. This project provides a list of invertebrates species whose DNA has been detected in water samples collected at 2018 using the marker COI.The surveys were carried out in the summer of 2018 from August 11 to 14, between Forestville and Godbout (Haute-Côte-Nord). Sampling was carried out between 9-52 meters depth in 40 stations with one sample par station. Two liters of water were filtered through a 1.2 µm fiberglass filter. DNA extractions were performed with the DNeasy Blood and Tissue extraction kit (Qiagen). Negative field, extraction and PCR controls were added at the different stages of the protocol. Libraries at the COI locus were prepared by Genome Quebec and sequenced on an Illumina MiSeq PE250 system. The bioinformatics analysis of the sequences obtained was carried out using an in-house analysis pipeline as reported in Bourret et al. 2022. A first step made it possible to obtain a molecular operational taxonomic unit table (MOTU) using the cutadapt software for the removal of the adapters and the DADA2 R package for the filtration, fusion, chimera removal and data compilation. The MOTUs table was subsequently corrected by taking into account the negative controls, where the number of observations in the latter was removed from the linked samples. Singleton MOTUs have also been removed. Finally, the taxonomic assignments were carried out on the MOTUs using the IDTAXA classifier (present in the DECIPHIER R package) using a training set trained on the COI reference bank for Golf St-Laurent (GSL-rl v1.0, https://github.com/GenomicsMLI-DFO/MLI_GSL-rl) and a threshold of 40. Detections with an “Unreliable due to gaps” category were reported at the genus level only.The file provided includes generic activity information, including site, station name, date, marker type, assignment types used for taxa identification, and a list of taxa or species. The list of taxa has been verified by a biodiversity expert from the Maurice-Lamontagne Institute.This project was funded by Fisheries and Oceans Canada's Coastal Environmental Baseline Data Program under the Oceans Protection Plan. This initiative aims to acquire baseline environmental data that contributes to the characterization of significant coastal areas and supports evidence-based assessments and management decisions to preserve marine ecosystems.Data are also available on SLGO platform : https://doi.org/10.26071/ogsl-cd4c205b-f63b

DFO has committed to establishing a representative network of Marine Conservation Areas collectively comprising 30% of the EEZ by 2030. The MCT 2.0 program was established in 2021 to help achieve this target and establish long-term monitoring within Canadian conservation areas. Information on the distribution of species within a protected area is essential for the management and monitoring of a site. Decisions made on zoning, risk assessment, activity approvals and management effectiveness all require information on the distribution and status of species. The Scotian Shelf-Bay of Fundy Bioregion spans the domain of the Maritimes Region, and within it there are 8 Marine Refuges (MR), 3 Marine Protected Areas (MPA), and 2 Areas of Interest (AOI). Environmental DNA (eDNA) offers a promising approach for biodiversity monitoring that has been gaining increased attention in the marine realm. Through sampling relatively small volumes of water (~3L), eDNA can capture of millions of fragments of eDNA on specialized filters that can then be sequenced to identify the species composition of an area. eDNA metabarcoding is based on the foundations of DNA barcoding, where species are identified solely by their unique DNA sequences. This method is relatively simple, efficient (with the ability to characterize both fish and invertebrate diversity), and non-invasive, meaning there is no disruption of sensitive benthic habitats or need to dissect tissue samples from captured fish and invertebrates. eDNA has been shown to be comparable to other biodiversity censusing techniques and has the potential to rapidly conduct biodiversity surveys over a relatively large area, such as the Eastern Shore Islands AOI. The DFO Maritimes summer multispecies trawl survey is one of the longest-running data series with applications in fisheries stock assessment, and one of the only sources of data for offshore MPA design and monitoring. In this project we pair eDNA samples collected within current and proposed conservation areas with trawl catch data to create a biodiversity and animal community monitoring time series for these areas. We use eDNA and trawl catch data as complementary tools, where trawl-based catch provides information on fish abundance, size distributions and sex, and eDNA provides information on genetic diversity and can detect cryptic and rare species. Cite this data as: Jeffery, N.W. Monitoring regional conservation areas using paired environmental DNA and research trawl surveys. Published: May 2026. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS.

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.

A compendium of reports that provide information about aquatic and terrestrial animals and plants, soils, surface water, groundwater and their accompanying data files and maps

Understanding the state and trends in agriculture production is essential to combat both short-term and long-term threats to stable and reliable access to food for all, and to ensure a profitable agricultural sector. Starting in 2009, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop type digital maps. Focusing on the Prairie Provinces in 2009 and 2010, a Decision Tree (DT) based methodology was applied using optical (Landsat-5, AWiFS, DMC) and radar (Radarsat-2) based satellite images. Beginning with the 2011 growing season, this activity has been extended to other provinces in support of a national crop inventory. To date this approach can consistently deliver a crop inventory that meets the overall target accuracy of at least 85% at a final spatial resolution of 30m (56m in 2009 and 2010).