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.

The data represents an assessment of biodiversity risk for the agricultural area of Alberta in 2002. Biodiversity risk refers to the loss of biological diversity, or the variety of plant and animal life in agricultural landscapes. This map, created in ArcGIS, tries to show where biodiversity could be threatened, such as in areas with significant habitat that coincide with areas of greater agricultural economic activity. Biodiversity is believed to affect the overall health of the environment.

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.

Forest ecosystems located on the domain of the State and of particular interest for the conservation of biological diversity, because of their rare or ancient nature, or because they are home to one or more threatened or vulnerable plant species. Their management is under the responsibility of the Ministry of Natural Resources and Forests (MNRF) and they may be classified under the Sustainable Forest Development Act (LADTF, chapter A-18.1). Forest management activities are prohibited on the territory of an exceptional forest ecosystem, with few exceptions.Currently, there are 256 classified EFEs. This data comes from the MRNF STF system, which is the __official source__ of this geographic information.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Effective conservation planning relies on understanding population connectivity which can be informed by genomic data. This is particularly important for sessile species like the horse mussel (Modiolus modiolus), a key habitat-forming species and conservation priority in Atlantic Canada), yet little genomic information is available to describe horse mussel connectivity patterns. We used more than 8000 restriction-site associated DNA sequencing-derived single nucleotide polymorphisms and a panel of 8 microsatellites to examine genomic connectivity among horse mussel populations in the Bay of Fundy, along the Scotian Shelf, and in the broader northwestern Atlantic extending to Newfoundland. Despite phenotypic differences between sampling locations, we found an overall lack of genetic diversity and population structure in horse mussels in the Northwest Atlantic Ocean. All sampled locations had low heterozygosity, very low FST, elevated inbreeding coefficients, and deviated from Hardy-Weinberg Equilibrium, highlighting generally low genetic diversity across all metrics. Principal components analysis, Admixture analysis, pairwise FST calculations, and analysis of outlier loci (potentially under selection) all showed no independent genomic clusters within the data, and an analysis of molecular variance showed that less than 1% of the variation within the SNP dataset was found between sampling locations. Our results suggest that connectivity is high among horse mussel populations in the Northwest Atlantic, and coupled with large effective population sizes, this has resulted in minimal genomic divergence across the region. These results can inform conservation design considerations in the Bay of Fundy and support further integration into the broader regional conservation network.Cite this data as: Van Wyngaarden, Mallory et al. (2024). Widespread genetic similarity between Northwest Atlantic populations of the horse mussel, Modiolus modiolus. Published: May 2025. Coastal Ecosystem Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth, NS.

A global decline in seagrass populations has led to renewed calls for their conservation as important providers of biogenic and foraging habitat, shoreline stabilization, and carbon storage. Eelgrass (Zostera marina) occupies the largest geographic range among seagrass species spanning a commensurately broad spectrum of environmental conditions. In Canada, eelgrass is managed as a single phylogroup despite occurring across three oceans and a range of ocean temperatures and salinity gradients. Previous research has focused on applying relatively few markers to reveal population structure of eelgrass, whereas a whole genome approach is warranted to investigate cryptic structure among populations inhabiting different ocean basins and localized environmental conditions. We used a pooled whole-genome re-sequencing approach to characterize population structure, gene flow, and environmental associations of 23 eelgrass populations ranging from the Northeast United States, to Atlantic, subarctic, and Pacific Canada. We identified over 500,000 SNPs, which when mapped to a chromosome-level genome assembly revealed six broad clades of eelgrass across the study area, with pairwise FST ranging from 0 among neighbouring populations to 0.54 between Pacific and Atlantic coasts. Genetic diversity was highest in the Pacific and lowest in the subarctic, consistent with colonization of the Arctic and Atlantic oceans from the Pacific less than 300 kya. Using redundancy analyses and two climate change projection scenarios, we found that subarctic populations are predicted to be more vulnerable to climate change through genomic offset predictions. Conservation planning in Canada should thus ensure that representative populations from each identified clade are included within a national network so that latent genetic diversity is protected, and gene flow is maintained. Northern populations, in particular, may require additional mitigation measures given their potential susceptibility to a rapidly changing climate.Cite this data as: Jeffery, Nicholas et al. (2024). Data from: Variation in genomic vulnerability to climate change across temperate populations of eelgrass (Zostera marina) [Dataset]. Dryad. https://doi.org/10.5061/dryad.xpnvx0kp2

This geodatabase includes hotspot maps of 1) nearshore habitat richness, 2) diversity (fish and invertebrates), and 3) biomass (using catch per unit effort of fish and invertebrates), as well as two layers showing the spatial extent of the diversity and biomass hotspot analyses. Full details and methods can be found in the Rubidge et al. 2018 CSAS Research Document 2018/053 available here or at https://waves-vagues.dfo-mpo.gc.ca/Library/40759842.pdf. These data were reviewed as part of a Canadian Science Advisory Secretariat (CSAS) regional peer review process on Nov 1-2, 2017.Habitat Richness Hotspots: Because there are no systematic surveys of nearshore species that span the entire coastline of Northern Shelf Bioregion, the nearshore habitat richness hotspots were developed as a proxy for species diversity in nearshore areas. Habitat richness was calculated from eight habitat features: eelgrass, surfgrass, canopy-forming kelp, estuaries, areas of high rugosity, and hard, mixed, and soft substrate. The number of features within 1 km x 1 km planning units was counted, and hotspots were identified using the Getis-Ord G* tool in ArcGIS. Planning units with Gi_Bin values of 3 (99% confidence) were classified as habitat richness hotspots.Diversity and Biomass Hotspots: Hotspots of fish and invertebrate diversity and biomass were developed as proxies for spatial patterns of productivity in the Northern Shelf Bioregion. Diversity (Shannon diversity) and biomass (kg/hour or count/hook/hour) were calculated from DFO synoptic trawl and outside hard-bottom longline (HBLL) survey catch records. The outside HBLL survey was previously referred to as Pacific Halibut Management Area (PHMA) survey. The synoptic trawl and HBLL surveys have complementary spatial coverage, with the HBLL surveys occurring in more coastal areas (20–260 m) and the synoptic trawl surveys occurring on deeper shelf areas (50–1300 m). Hotspots were identified using the Getis-Ord G* tool in ArcGIS for five separate analyses: fish biomass (trawl), fish diversity (trawl), fish diversity (longline), invertebrate biomass (trawl), and invertebrate diversity (trawl). Using the Minimum Bounding Geometry Tool, convex hull polygons were drawn around groups of hotspot points (Gi_Bin values of 1, 2, or 3; confidence ≥90%) containing 10 or more points. The resulting polygons were then buffered by 1 km and manually edited where needed to exclude any large areas of the polygons that did not include hotspot points.

PURPOSE:The Department of Fisheries and Oceans (DFO) conducted a baseline survey of biological communities and habitat parameters in the offshore Canadian Beaufort Sea between 2012 and 2014, as part of the federally administered Beaufort Regional Environmental Assessment. The BREA-Marine Fishes Project (BREA-MFP) was the first comprehensive baseline study of offshore marine fish diversity and associated habitats in the Canadian Beaufort Sea. Knowledge gained during the BREA-MFP supports regulatory processes pertaining to offshore development and Oceans Management in the Inuvialuit Settlement Region, and provides baseline context for studies of the effects of climate change and variability. The Canadian Beaufort Sea – Marine Ecosystem Assessment (CBS-MEA, 2017-2019 and 2021-2024) is building on system baselines and ecological knowledge derived from the BREA-MFP to develop a comprehensive research and monitoring approach for the offshore Canadian Beaufort Sea. This approach will enable us to better understand the relationship between oceanographic drivers and ecosystem responses. The CBS-MEA focuses on integrating oceanography, food web linkages, physical-biological couplings and spatial and inter-annual variabilities, while also expanding baseline coverage of species diversity, abundances, and habitat associations to areas of the Beaufort Sea and Canadian Archipelago that are previously unstudied in this context.DESCRIPTION:Between 2017 and 2019, and between 2021 and 2024, Fisheries and Oceans Canada conducted a baseline survey of marine fishes and their habitats on the Canadian Beaufort Shelf and slope in August and early September each year. Sampling was conducted from the F/V Frosti at over 150 stations along ten multi-year transects, and over 50 non-transect stations. Standardized sampling was conducted at pre-determined depth stations (20-40, 75, 200, 350, 500, 750, and 1000 m) using a variety of sampling equipment including benthic fishing trawls, plankton nets, sediment cores, and CTD and water sample profiles. Presented here is the information on the sampling locations, and the sampling gear deployed at each station.

This dataset reports on lobster abundance and individual biological characteristics (size, sex, shell hardness, egg status), along with seabed substrate information, collected at various coastal sites in the Bay of Fundy, Canada. Surveys were conducted over a 40-year period between 1982 and 2021. Survey areas and SCUBA dive sites were located around Grand Manan Island, Deer Island, Campobello Island, and along the Bay of Fundy’s New Brunswick shore stretching from Passamaquoddy Bay, east to Maces Bay. One survey area was located on the Bay of Fundy’s southern shore (Nova Scotia) in the Annapolis Basin (Lawton et al. 1995). The data represent a compilation of SCUBA diving surveys (1003 belt transects) conducted directly by Fisheries and Oceans Canada (DFO) scientific SCUBA divers (1982-2019), or by contracted commercial divers funded in association with outside collaborating organizations; Department of Fisheries and Agriculture (DFA; 1990 – 1993), the Grand Manan Fishermen’s Association (GMFA; 2013-2015), and the University of New Brunswick (UNB; 2019-2021).Cite this data as: Lawton P, Dinning K, Rochette R, Teed L. American lobster (Homarus americanus) abundance and biological characteristics collected from SCUBA dive surveys in the Bay of Fundy from 1982-2021. Published August 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B.For additional information please see:Campbell, A. 1990. Aggregations of berried lobsters (Homarus americanus) in shallow waters off Grand Manan, eastern Canada. DFO Can. J. Fish. Aquat. Sci. 47: 520-523.Denton, C.M. 2020. Maritimes Region Inshore Lobster Trawl Survey Technical Description. DFO Can. Tech. Rep. Fish. Aquat. Sci. 3376: v + 52 p.Lawton, P. 1993. Salmon aquaculture and the traditional invertebrate fisheries of the Fundy Isles region: habitat mapping and impact definition: Cooperation Agreement on Fisheries and Aquaculture Development. Submitted by Peter Lawton to the New Brunswick Department of Fisheries and Aquaculture, 84 p. Unpublished monograph. Available from Fisheries and Oceans Canada Library, Dartmouth, NS (Monographs: SH 380.2 .C2 .L39 1992).https://science-catalogue.canada.ca/record=3943769~S6Lawton, P., Robichaud, D.A., and Moisan, M. 1995. Characteristics of the Annapolis Basin, Nova Scotia, lobster fishery in relation to proposed marine aquaculture development. DFO Can. Tech. Rep. Fish. Aquat. Sci. 2035: iii + 26 p.Lawton, P., Robichaud, D.A., Rangeley, R.W., and Strong, M.B. 2001. American Lobster, Homarus americanus, population characteristics in the lower Bay of Fundy (Lobster Fishing Areas 36 and 38) based on fishery independent sampling. DFO Can. Sci. Advis. Sec. Res. Doc. 2001/093.Wentworth, C.K. 1922. A Scale of Grade and Class Terms for Clastic Sediments. The Journal of Geology 30(5): 377-392.Dinning, K.M., Lawton, P., and Rochette, R. 2025. Increased use of mud bottom by juvenile American lobsters (Homarus americanus) in Maces Bay and Seal Cove, Bay of Fundy, after three decades of population increases and predator declines. Canadian Journal of Fisheries & Aquatic Sciences 82; https://doi.org/10.1139/cjfas-2023-0312

Marine classification schemes based on abiotic surrogates often inform regional marine conservation planning in lieu of detailed biological data. However, theses chemes may poorly represent ecologically relevant biological patterns required for effective design and management strategies. We used a community-level modeling approach to characterize and delineate representative mesoscale (tens to thousands of kilometers) assemblages of demersal fish and benthic invertebrates in the North-west Atlantic. Hierarchical clustering of species occurrence data from four regional annual multispecies trawl surveys revealed three to six groupings (predominant assemblage types) in each survey region, broadly associated with geomorphic and oceanographic features. Indicator analyses identified 3–34 emblematic taxa of each assemblage type. Random forest classifications accurately predicted assemblage dis-tributions from environmental covariates (AUC > 0.95) and identified thermal limits (annual minimum and maximum bottom temperatures) as important pre-dictors of distribution in each region. Using forecasted oceanographic conditions for the year 2075 and a regional classification model, we projected assemblage dis-tributions in the southernmost bioregion (Scotian Shelf-Bay of Fundy) under ahigh emissions climate scenario (RCP 8.5). Range expansions to the north eastare projected for assemblages associated with warmer and shallower waters of the Western Scotian Shelf over the 21st century as thermal habitat on the rela-tively cooler Eastern Scotian Shelf becomes more favorable. Community-level modeling provides a biotic-informed approach for identifying broadscale ecolog-ical structure required for the design and management of ecologically coherent, representative, well-connected networks of Marine Protected Areas. When com-bined with oceanographic forecasts, this modeling approach provides a spatial tool for assessing sensitivity and resilience to climate change, which can improve conservation planning, monitoring, and adaptive management.Cite this data as: O'Brien, J.M., Stanley, R.R.E., Jeffery, N.W., Heaslip, S.W., DiBacco, C., and Wang, Z. Demersal fish and benthic invertebrate assemblages in the Northwest Atlantic.Published: December 2024. Coastal Ecosystems Science Division, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS.https://open.canada.ca/data/en/dataset/14d55ea5-b17d-478c-b9ee-6a7c04439d2b