AIS NL Biofouling Species Fisheries and Oceans Canada's (DFO) National Marine Biofouling Monitoring Program conducts annual field surveys to monitor the introduction, establishment, spread, species richness, and relative abundance of native and some non-native species in Newfoundland and Labrador (NL) Region since 2006. Standardized monitoring protocols employed by DFO's NL, Maritimes, Gulf, and Quebec regions include biofouling collector plates deployed from May to October at georeferenced intertidal and shallow subtidal sites, including public docks, and public and private marinas and nautical clubs. Initially, (2006-2017), the collectors consisted of three 10 cm by 10 cm PVC plates deployed in a vertical array and spaced approximately 40 cm apart, with the shallowest plate suspended at least 1 m below the surface to sample subtidal and shallow intertidal species (McKenzie et al 2016a). Three replicate arrays were deployed at least 5 m apart per site. Since 2018, collector networks have been modified to improve statistical replication, including up to 10 individual collectors deployed per site at 1 m depth and at least 5 m apart (as above) from May to October. Since 2006, seven invasive biofouling organisms have been detected in Newfoundland and Labrador harbours, marinas and coastal areas.Should be cited as follows: DFO Newfoundland and Labrador Region Aquatic Invasive Species Marine Biofouling Monitoring Program. Published March 2024. Coastal and Freshwater Ecology, Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John’s, Newfoundland and Labrador.Reference:TunicatesViolet tunicate (Botrylloides violaceus) 2007The violet tunicate was first detected in NL waters in 2007 in Belleoram, Fortune Bay on wharf structures and vessels (McKenzie et al. 2016b). This colonial tunicate forms irregular shaped colonies usually of a solid color (orange, purple, yellow or cream). It is currently found in relatively small colonies in four harbours in NL; Placentia Bay (1), Fortune Bay (1), Conception Bay (1) and the west coast of NL (2). The data provided here indicates the detections of this AIS in coastal NL.From 2018-2022, the Coastal Environmental Baseline Program provided additional support to enhance sampling efforts in Placentia Bay.

AIS NL Biofouling Species Fisheries and Oceans Canada's (DFO) National Marine Biofouling Monitoring Program conducts annual field surveys to monitor the introduction, establishment, spread, species richness, and relative abundance of native and some non-native species in Newfoundland and Labrador (NL) Region since 2006. Standardized monitoring protocols employed by DFO's NL, Maritimes, Gulf, and Quebec regions include biofouling collector plates deployed from May to October at georeferenced intertidal and shallow subtidal sites, including public docks, and public and private marinas and nautical clubs. Initially, (2006-2017), the collectors consisted of three 10 cm by 10 cm PVC plates deployed in a vertical array and spaced approximately 40 cm apart, with the shallowest plate suspended at least 1 m below the surface to sample subtidal and shallow intertidal species (McKenzie et al 2016a). Three replicate arrays were deployed at least 5 m apart per site. Since 2018, collector networks have been modified to improve statistical replication, including up to 10 individual collectors deployed per site at 1 m depth and at least 5 m apart (as above) from May to October. Since 2006, seven invasive biofouling organisms have been detected in Newfoundland and Labrador harbours, marinas and coastal areas.Should be cited as follows: DFO Newfoundland and Labrador Region Aquatic Invasive Species Marine Biofouling Monitoring Program. Published March 2024. Coastal and Freshwater Ecology, Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John’s, Newfoundland and Labrador.Reference:TunicatesGolden star tunicate (Botryllus schlosseri) 2006 The Golden star tunicate was the first invasive tunicate detected in NL waters. It was reported in Argentia by the US Navy around 1945. It was found in 2006 on wharf structures in Argentia, Placentia Bay during the first AIS survey (Callahan et al 2010). This colonial tunicate is recognized by it star shaped grouping of individuals within the colony. It is currently found in Placentia Bay, Fortune Bay, St. Mary’s Bay, Conception Bay and the west coast of NL. The data provided here indicates the detections of this AIS in coastal NL.From 2018-2022, the Coastal Environmental Baseline Program provided additional support to enhance sampling efforts in Placentia Bay.

To support the surveillance of key macroalgae and non-indigenous species in Nova Scotia and New Brunswick, five quantitative PCR (qPCR) assays were designed and tested at 111 sites in 2022-2023 targeting the following non-indigenous macroalgal species: Antithamnion sparsum, Bonnemaisonia hamifera, Codium fragile, Dasysiphonia japonica, Fucus serratus. All assays were developed in 2022 by the Center for Environmental Genomics Applications (CEGA, Newfoundland, Canada) except Antithamnion sparsum, for which an assay was developed in 2023 by the Aquatic Biotechnology Laboratory (ABL) at the Bedford Institute of Oceanography. All amplification was performed by the ABL in 2022-2023. The assay developed for Fucus serratus was later determined to be non-specific, and amplifies both F. serratus and Fucus distichus.Cite this data as: Krumhansl K, Brooks C, Lowen B, DiBacco C, (2025). Quantitative PCR (qPCR) of Key Macroalgal Non-Indigenous Species in Nova Scotia and New Brunswick Waters. Version 1.5. Fisheries and Oceans Canada. Samplingevent dataset. https://ipt.iobis.org/obiscanada/resource?r=quantitative_qpcr_macroalgal_nonindigenous_species_novascotia_newbrunswick_2022_2023&v=1.5For additional information please see:LeBlanc F., Belliveau V., Watson E., Coomber C., Simard N., DiBacco C., Bernier R., Gagné N. 2020. Environment DNA (eDNA) detection of marine aquatic invasive species (AIS) in Eastern Canada using a targeted species-specific qPCR approach. Management of Biological Invasions 11(2):201-217Krumhansl K.A., Brooks C.M., Lowen B., O’Brien J., Wong M., DiBacco C. Loss, resilience and recovery of kelp forests in a region of rapid ocean warming. Annals of Botany 2024 Mar 8; 133(1):73-92Brooks C.M., Krumhansl K.A. 2023. First record of the Asian Antithamnion sparsum Tokida, 1932 (Ceramiales, Rhodophyta) in Nova Scotia, Canada. BioInvasions Records 12(3):745-725.

This dataset displays the Canadian geographic ranges of the priority species identified under the Pan-Canadian Approach for Transforming Species at Risk Conservation in Canada (“Pan-Canadian Approach”). These species include Barren-ground Caribou (including the Dolphin and Union population); Greater Sage-Grouse; Peary Caribou; Wood Bison; Caribou, Boreal population (“Boreal Caribou”); and Woodland Caribou, Southern Mountain population (“Southern Mountain Caribou”). The priority species were chosen following a number of criteria and considerations in collaboration with federal, provincial, and territorial partners. These include, but were not limited to, the species' ecological role on a regional or national scale, their conservation status and achievability of conservation outcomes, their social and cultural value (particularly to Indigenous peoples), and the leadership/partnership opportunities that they present. Delivering conservation outcomes for targeted priority species can have significant co-benefits for other species at risk, and wildlife in general. For more information on the Pan-Canadian Approach and the priority species, see https://www.canada.ca/en/services/environment/wildlife-plants-species/species-risk/pan-canadian-approach.html.This dataset includes: 1) the range for the Boreal Caribou (see https://species-registry.canada.ca/index-en.html#/consultations/2253); 2) the local populations for the Southern Mountain Caribou (see https://species-registry.canada.ca/index-en.html#/consultations/1309); 3) the range for the Greater Sage-Grouse (see https://species-registry.canada.ca/index-en.html#/consultations/1458); 4) local populations for the Peary Caribou (see https://species-registry.canada.ca/index-en.html#/consultations/3657); 5) range for the Barren-ground Caribou (see https://www.maps.geomatics.gov.nt.ca/Html5Viewer/index.html?viewer=NWT_SHV English only); 6) range for the Barren-ground Caribou, Dolphin and Union population (https://www.maps.geomatics.gov.nt.ca/Html5Viewer/index.html?viewer=NWT_SHV English only); 7) range for the Wood Bison (see https://species-registry.canada.ca/index-en.html#/consultations/2914).

In this dataset, we share maps of annual dominant tree species (also known as leading tree species) from 1984-2022 covering the entirety of Canada's 650 Mha forested ecosystems using Landsat time-series imagery at a 30-m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Classifications are based on regionally representative Random Forests model using local training samples from Canada's National Forest Inventory (Hermosilla et al., 2024). Descriptive metrics provide information on spectral, geographic, climatic, and topographic characteristics. Initial annual tree species classifications were subjected to a time series post-classification process using the forward-backward Hidden Markov Model to improve the temporal consistency of tree species transitions within the time series. Assessment of the annual species maps using independent validation data resulted in an overall accuracy of 86.1% ± 0.14% (95%-confidence interval). These data allow consistent comparison of trends and rates of change in tree species composition nationally and across regions using a common time frame, spatial resolution, and analytical approach.Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Bater, C.W., Hobart, G.W., 2024. Characterizing long-term tree species dynamics in Canada's forested ecosystems using annual time series remote sensing data. Forest Ecology and Management, 122313. https://doi.org/10.1016/j.foreco.2024.122313 (Hermosilla et al. 2024)

DescriptionConservation of marine biodiversity requires understanding the joint influence of ongoing environmental change and fishing pressure. Addressing this challenge requires robust biodiversity monitoring and analyses that jointly account for potential drivers of change. Here, we ask how demersal fish biodiversity in Canadian Pacific waters has changed since 2003 and assess the degree to which these changes can be explained by environmental change and commercial fishing. Using a spatiotemporal multispecies model based on fisheries independent data, we find that species density (number of species per area) and community biomass have increased during this period. Environmental changes during this period were associated with temporal fluctuations in the biomass of species and the community as a whole. However, environmental changes were less associated with changes in species’ occurrence. Thus, the estimated increases in species density are not likely to be due to environmental change. Instead, our results are consistent with an ongoing recovery of the demersal fish community from a reduction in commercial fishing intensity from historical levels. These findings provide key insight into the drivers of biodiversity change that can inform ecosystem-based management.The layers provided represent three community metrics: 1) species density (i.e., species richness), 2) Hill-Shannon diversity, and 3) community biomass. All layers are provided at a 3 km resolution across the study domain for the period of 2003 to 2019. For each metric, we provide layers for three summary statistics: 1) the mean value in each grid cell over the temporal range, 2) the probability that the grid cell is a hotspot for that metric, and 3) the temporal coefficient of variation (i.e., standard deviation/mean) across all years.Methods:The analysis that produced these layers is presented in Thompson et al. (2022). The analysis uses data from the Groundfish Synoptic Bottom Trawl Research surveys in Queen Charlotte Sound (QCS), Hecate Strait (HS), West Coast Vancouver Island (WCVI), and West Coast Haida Gwaii (WCHG) from 2003 to 2019. Cartilaginous and bony fish species caught in DFO groundfish surveys that were present in at least 15% of all trawls over the depth range in which they were caught were included. This depth range was defined as that which included 95% of all trawls in which that species was present. The final dataset used in our analysis consisted of 57 species (Table S1 in Thompson et al. 2022).The spatiotemporal dynamics of the demersal fish community were modeled using the Hierarchical Modeling of Species Communities (HMSC) framework and package (Tikhonov et al. 2021) in R. This framework uses Bayesian inference to fit a multivariate hierarchical generalized mixed model. We modeled community dynamics using a hurdle model, which consists of two sub models: a presence-absence model and a biomass model that is conditional on presence. Our list of environmental covariates included bottom depth, bathymetric position index (BPI), mean summer tidal speed, substrate muddiness, substrate rockiness, whether the trawl was inside or outside of the ecosystem-based trawling footprint, and survey region (QCS & HS vs. WCVI & WCHG)), mean summer near-bottom temperature deviation, mean summer near-bottom dissolved oxygen deviation, mean summer cross-shore and along-shore current velocities near the seafloor, mean summer depth-integrated primary production, and local-scale commercial fishing effort.Layers are provided for three community metrics. All metrics should be interpreted as the value that would be expected in the catch from an average tow in the Groundfish Synoptic Bottom Trawl Research Surveys taken in a given 3 km grid cell. Species density (sometimes called species richness) should be interpreted as the number of the 57 species that would be caught in a trawl. Hill-Shannon diversity is a measure of diversity that gives greater weight to communities where biomass is spread equally across species. Community biomass is the total biomass across all 57 species that would be expected to be caught per square km in an average tow. Data Sources:Research data was provided by Pacific Science's Groundfish Data Unit for research surveys from the GFBio database between 2003 and 2019 that occurred in four regions: Queen Charlotte Sound, Hecate Strait, West Coast Haida Gwaii, and West Coast Vancouver Island. Our analysis excludes species that are rarely caught in the research trawls and so our estimates would not include the occurrence or biomass of these rare species.Commercial fishing data was accessed through a DFO R script detailed here: https://github.com/pbsassess/gfdata. Local scale commercial fishing effort was calculated from this data. The substrate layers were obtained from a substrate model (Gregr et al. 2021). The oceanographic layers (bottom temperature, dissolved oxygen, tidal and circulation speeds, primary production) were obtained from a hindcast simulation of the British Columbia continental margin (BCCM) model (Peña et al. 2019).Uncertainties:Species that are not well sampled by the trawl surveys may not be accurately estimated by our model. The model did not include spatiotemporal random effects, which likely underestimates spatiotemporal variability in the region. It is also important to underline covariate uncertainty and model uncertainty. The hotspot estimates provide one measure of model uncertainty/certainty.

Land cover imagery for the moist mixed grassland ecoregion of Saskatchewan with a resolution of 10m. Classification was based on machine learning analysis and remote sensing data of Sentinel-1 and Sentinel-2 imagery in Google Earth Engine platform. The goal of this land cover was to distinguish native from tame grasslands, and is classified into several classes: native grassland, tame grassland, mixed grassland, cropland, woody plants, water, and urban area.Download: Here The Prairie Landscape Inventory (PLI) working team of Habitat Unit in the Fish and Wildlife Branch, Ministry of Environment aims to develop improved methods of assessing land cover and land use for conservation. Native grassland, in particular, has been one of the most hard to map at risk ecosystems because of difficulty for imagery classification methods to distinguish native from tame grasslands. Improved classification methods will provide valuable information for habitat suitability, identifying high biodiversity potential and invasion risk potential.  The classification map has seven (7) classes:  1.  Cropland This class represents all cultivated areas with crop commodities: corn, pulse, soybeans, canola, grains, summer-fallow. 2. Native grassland This class represents the native grassland areas of the Moist Mixed Grassland ecoregion, which are composed of at least 75% native grass species, such as the needle grasses, wheatgrasses along with June grass and blue grama grass. Also includes additional sedge species, forbs, and some non-vascular species. Unbroken grassland that is invaded by species like Kentucky bluegrass, crested wheatgrass or smooth brome, such that native cover is less than 75%, is not considered native for the purpose of this project.  3. Mixed grassland This class represent a heterogenic grassland with a mix of less than 75% native grass species or less than 75% tame species.  4. Tame grassland This class represents the tame grassland areas of the Moist Mixed Grassland ecoregion, which are composed of at least 75% seeded or planted species with introduced grasses and forb species such as crested wheatgrass, smooth brome, alfalfa, sweet clover. 5. Water This class represents permanent water locations such as lakes and rivers. 8. Woody plants This class represents the sites dominated by woody vegetation including shrubs and trees with typically more than 20% canopy cover. 9. Urban area This class was masked using urban/developed area class of the Annual Crop Inventory 2020 (Agriculture Agri-Food Canada), and limited within the urban municipality polygons. Colour Classes: Value Label Red Green Blue 1 Cropland 255 255 190 2 Native grassland 168 168 0 3 Mixed grassland 199 215 158 4 Tame grassland 245 202 122 5 Water 190 232 255 8 Woody plants 137 205 102 9 Urban area 128 128 128 Accuracy metrics This model has an overall accuracy of 70.3 per cent. The table below summarizes the user’s accuracy, producer’s accuracy, and F1-score of the model on the validation dataset. Class User’s accuracy (%) Producer’s accuracy (%) F1-score Cropland 74.7 87.1 0.81 Native grassland 61.7 78.3 0.69 Mixed grassland 57.7 26.1 0.36 Tame grassland 66.9 69.8 0.68 Water 96.3 84.4 0.90 Woody plants 81.1 73.2 0.77

The Native Prairie Vegetation Inventory (NPVI) Polygons is a quarter section-based vegetation inventory that covers the southern part of Alberta. The native prairie is defined in the Native Prairie Conservation Action Plan as an area of unbroken grassland or parkland dominated by non-introduced species, and an area of previously broken grassland that has reverted back to natural vegetation (30 to 60 years). The Native Prairie Vegetation Inventory extends beyond the Grasslands Natural Region to include data for adjacent areas, such as the Cypress Hills. In addition to the Grassland Natural Region, the Native Prairie Vegetation Inventory (NPVI) Polygons include areas that belong to the Foothills Parkland, Central Parkland, Montane, Dry Mixedwood Boreal and Lower Foothills Natural Subregions.

Special Management Areas are part of a network of protected lands in Saskatchewan. The following dataset accurately defines SMA land areas in Saskatchewan that have various levels of developmental restrictions.The Minister of Environment wishes to identify “Special Management Areas” to be managed for the following purposes:a) the protection, enhancement or restoration of natural ecosystems, wildlife habitat or habitat of rare, threatened or endangered plant or animal species;b) the retention of significant botanical, zoological, morphological, historical archaeological features respecting the land;c) the conservation of soil, air and water quality; and the opportunity for scientific research and study related to the ecological health of the area.

The Fish and Wildlife Development Fund (FWDF) was developed to manage, preserve and enhance fish and wildlife habitat in Saskatchewan. The fund has three fish and wildlife management goals: Maintain natural habitat through conservation, biodiversity, land management and awareness of rare species; Maintain and grow sustainable fish populations and fish habitat; and Maintain game populations and ensure accessible hunting.Thirty per cent of the revenue from all hunting, angling and trapping licence sales is contributed to the fund. Additionally, monetary contributions to the fund can be made through your Hunting, Angling and Trapping Licence (HAL) system account. You can also help support the sustainable management and use of fish and wildlife resources by:Supporting programs that conserve wildlife and fisheries habitat;Joining or supporting your local conservation group or wildlife federation;Planting shelterbelts (using native fruit-bearing species), protecting wetlands, including their riparian areas;Maintaining large or small natural areas; andEnsuring your activities on the landscape do not contribute to the introduction or spread of invasive species. landscape do not contribute to the introduction or spread of invasive species.