Post-disturbance forest recovery data for Canada's forested ecosystems, representing a total area of ~650 million ha, captures the return of forests following wildfire and harvest that occurred between 1986 and 2012. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). These spatially-explicit outputs represent the rate of spectral recovery: the rate at which a pixel returns to 80% of its pre-disturbance value (White et al. 2017) within the observation period (1985-2017) using the Y2R or Years-to-Recovery metric derived from Landsat times series data. Baseline rates of spectral recovery (Y2R) were defined for each of Canada's 12 forested ecozones. These baselines were then used to identify spatial clusters of recovering pixels on the landscape where Y2R were either significantly faster or slower than their ecozonal baseline. Finally, areas that were disturbed by wildfire and harvest (1986-2012), but which had not recovered by the end of the observation period (2017) are also provided. Note that these areas are still recovering, but they had not yet recovered according to our metric of spectral recovery, by the end of the time series in 2017. For an overview of the methods, the validation of the Y2R metric, and interpretation of the derived trends, see White et al. (2022) and White et al. (2017).White, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., 2022. Mapping, validating, and interpreting spatio-temporal trends in post-disturbance forest recovery. Remote Sensing of Environment, 271, 112904. https://doi.org/10.1016/j.rse.2022.112904 ( White et al. 2022)White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C., Hobart, G.W. 2017. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment, 194, pp. 303-321. DOI: https://doi.org/10.1016/j.rse.2017.03.035 .( White et al. 2017)

Results from temperature preference experiments demonstrated that individual personality was consistent and repeatability. Individual preferred and maximum avoidance temperatures were significantly reduced in hypoxia compared to normoxia. Standard metabolic rate increased with temperature and body mass. Patterns of projected habitat change suggest the spatial extent of the current distribution of Carmine shiner would shift north with global warming. The understanding of habitat requirements and responses to climate will aid management and recovery efforts for this threatened species.Cite this dataset as: Enders, Eva. Data of: Carmine Shiner Conservation Physiology. Arctic and Aquatic Research Division, Fisheries and Oceans Canada, Winnipeg Manitoba. https://open.canada.ca/data/en/dataset/a6a606a4-8cdc-48e9-812c-7bdcd84840e7

The Species at Risk (SAR) Program is responsible for carrying out DFO’s mandate under the Species at Risk Act (SARA) to protect, recover and conserve all listed aquatic SAR in Canada. As part of this mandate, this spatial database has been developed to identify areas in which aquatic species listed under SARA may be found.Distribution and range information are identified for species listed as Endangered, Threatened or Special Concern under SARA.Distribution (range) polygons and lines were assembled by regional SARA biologists using the best available information, including COSEWIC status reports, recovery potential assessments, academic literature, and expert opinion. These spatial data support the protection, recovery and conservation of species listed as Endangered, Threatened or Special Concern under SARA. Species distributions are also described and displayed in Recovery Strategies, Action Plans and/or Management Plans. Discrepancies may exist between the distribution data shown in a species’ SARA recovery document and the current spatial data. Please contact DFO for more information on any data discrepancies.

The Species at Risk (SAR) Program is responsible for carrying out DFO’s mandate under the Species at Risk Act (SARA) to protect, recover and conserve all listed aquatic SAR in Canada. Critical habitat is identified for species listed as Endangered or Threatened under the Species at Risk Act (SARA).This mapping tool is for general guidance only. “Mapped” representations of waterbodies and watercourses are based on authoritative provincial geospatial products, guidance and standards. Due to the nature of dynamic systems and the resolution/accuracy of these data sets, areas within which critical habitat is found as displayed on the mapping tool may not align exactly with natural watercourses. If discrepancies occur, refer to the relevant species recovery strategy and/or action plan for additional information on critical habitat. If additional guidance is required, please contact the Fish and Fish Habitat Protection Program: https://www.dfo-mpo.gc.ca/pnw-ppe/contact-eng.htmlCritical habitat is defined under section 2 of SARA as: "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 in an action plan for the species". Section 49(1)(a) of SARA requires that a species' Recovery Strategy/Action Plan include an identification of the species' critical habitat to the extent possible, based on the best available information, including information provided by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC). SARA makes it illegal to destroy any part of the critical habitat of SAR and may impose restrictions on development and construction. Critical habitats were assembled by SARA regional biologists and recovery teams. They are designed to support the protection and recovery of species listed as Endangered or Threatened under the Species at Risk Act. They are also described and displayed in species' Recovery Documents and Action Plans.

This dataset shows locations that contain critical habitat for certain terrestrial species at risk across Canada. It is intended to provide general guidance only, not legally authoritative boundaries.The dataset includes active critical habitat records for terrestrial species listed on Schedule 1 of the Species at Risk Act (SARA) as Endangered, Threatened, or Extirpated, as well as archived records for species whose status has been downlisted to Special Concern, and for which Environment and Climate Change Canada (ECCC) and/or Parks Canada are responsible.Under SARA, critical habitat means 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. These documents, which are published in the Species at Risk Public Registry (https://www.canada.ca/en/environment-climate-change/services/species-risk-public-registry.html), describe the critical habitat and may include maps or geographic coordinates.Because new information becomes available over time, recovery documents—and the critical habitat they identify—can be updated or revised. The Species at Risk Public Registry is the main source for the most current official information. If there is any difference between this dataset and a recovery document, the recovery strategy or action plan is the authoritative source.Some habitat locations are considered sensitive. For these species, the data may be shown in a less detailed way, or at a broader geographic scale, to avoid increasing risks to the species. For more detailed information on critical habitat, contact the Canadian Wildlife Service at scf-geocarto-cws-geomapping@ec.gc.ca.The data is current as of the date of modification.

The Canada Nature Fund for Aquatic Species at Risk (CNFASAR) is a contribution program that focuses on providing funding for recovery and threat mitigation activities in nine priority places and to address two marine threats to aquatic species at risk. The Priority Places and Marine Threats layer supports CNFASAR by delineating the location of the places and threats.The Canada Nature Fund for Aquatic Species at Risk (CNFASAR) supports applicants in the design and delivery of stewardship projects. These projects support the recovery and protection of aquatic species at risk. DFO has identified 2 priority marine threats and 9 priority places as the focus for projects funded by CNFASAR, these areas are included in this dataset.

In 2014, the Alberta Energy Regulator (AER) initiated a Play-Based Regulation (PBR) pilot project as a step towards implementation of the Unconventional Regulatory Framework. One of the goals of the PBR pilot is to encourage companies in the unconventional play area to work together on plans for surface development to minimize the numbers of facilities and surface impacts. This dataset is one of a series created using earth observation imagery to assess surface change caused by energy exploration. The PBR area extends from Twp. 52, Rge. 7, W 5th Mer. to Twp. 70, Rge. 5, W 6th Mer., covering the towns of Edson, Fox Creek, Mayerthorpe, Whitecourt, Swan Hills, and Valleyview. Landsat multispectral imagery for 2012 and 2013 and Land Use and Land Cover (LULC) classification data derived from 2013 were used to produce this dataset. The LULC changes include vegetation loss from anthropogenic disturbances, such as infrastructure related to oil and gas exploration, forestry and agriculture, and vegetation recovery from these disturbances. This digital data release contains the vegetation recovery data, classified into 6 classes: 1 - shrub land, 2 - grassland, 3 - agricultural areas, 4 - coniferous forest, 5 - broadleaf forest and 6 - mixed forest.

In 2014, the Alberta Energy Regulator (AER) initiated a Play-Based Regulation (PBR) pilot project as a step towards implementation of the Unconventional Regulatory Framework. One of the goals of the PBR pilot is to encourage companies in the unconventional play area to work together on plans for surface development to minimize the numbers of facilities and surface impacts. This dataset is one of a series created using earth observation imagery to assess surface change caused by energy exploration. The PBR area extends from Twp. 52, Rge. 7, W 5th Mer. to Twp. 70, Rge. 5, W 6th Mer., covering the towns of Edson, Fox Creek, Mayerthorpe, Whitecourt, Swan Hills, and Valleyview. Landsat multispectral imagery for 2006 and 2007 and Land Use and Land Cover (LULC) classification data derived from 2007 were used to produce this dataset. The LULC changes include vegetation loss from anthropogenic disturbances, such as infrastructure related to oil and gas exploration, forestry and agriculture, and vegetation recovery from these disturbances. This digital data release contains the vegetation recovery data, classified into 6 classes: 1 - shrub land, 2 - grassland, 3 - agricultural areas, 4 - coniferous forest, 5 - broadleaf forest and 6 - mixed forest.

This program summarizes long term water chemistry and chlorophyll a monitoring in north central Ontario lakes developed under Canada’s Long Range Transport of Air Pollutants (LRTAP) initiative to understand and track lake acidification caused by atmospheric deposition. Centered on the intensively studied Turkey Lakes Watershed since 1979 and complemented by broader headwater and mesoscale lake networks around Sault Ste. Marie, Ontario, as well as a few locations near Parry Sound, Ontario, the monitoring integrates catchment scale approaches to link atmospheric inputs, watershed processes, and aquatic responses. Water chemistry measurements quantify acid–base status, major ions, nutrients, and trace metals to diagnose sensitivity to acidification, episodic stress during events such as spring snowmelt, and long term chemical recovery following emission controls. Chlorophyll a is used alongside chemistry to indicate phytoplankton biomass, lake productivity, and overall water quality, providing biological context for fish habitat and ecosystem condition. Together, these coordinated datasets support both detailed process studies and regional assessments of lake sensitivity, productivity, and ecological recovery across a heterogeneous landscape.

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.