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]. https://doi.org/10.5061/dryad.xpnvx0kp2

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.

An exploratory project on the taxonomic and genetic diversity of decapods in three ocean subregions (Northeast Pacific, Canadian Arctic, and Northwest Atlantic), which were sampled in 2022, was undertaken by the Arctic Working Group under the Canada-U.S. Fisheries and Climate Collaboration between Fisheries and Oceans Canada (DFO) and the National Marine Fisheries Service (NMFS) of the National Oceanic and Atmospheric Administration (NOAA). This collaboration framework aims to pool Canadian and U.S. data to explore the impacts of broad-scale climate change on marine biodiversity. In early summer 2022, a sampling protocol with the selection of targeted decapods was provided to DFO and NOAA collaborators. Targeted genera were collected from a total of 10 research programs across three ocean subregions and four marine regions. The Northeast Pacific samples were collected in the Bering Sea during the Northern Bering Sea Ecosystem and Surface Trawl Survey, and the Eastern and Northern Bering Sea Continental Shelf Bottom Trawl Survey of Groundfish and Invertebrate Fauna onboard the F/V Northwest Explorer, F/V Alaska Knight and F/V Vesteraalen. In the Western Canadian Arctic (mainly from Beaufort Sea and Amundsen Gulf), specimens were collected during DFO’s Canadian Beaufort Sea – Marine Ecosystem Assessment (CBS-MEA) survey onboard the F/V Frosti. In Eastern Canadian Arctic (mainly from Baffin Bay and Davis Strait), specimens were collected during DFO’s Knowledge and Ecosystem-Based Approach in Baffin Bay (KEBABB) survey onboard the CCGS Amundsen and DFO’s North Atlantic Fisheries Organization (NAFO) Subarea 0B survey onboard the R/V Tarajoq. In the Estuary and Gulf of St. Lawrence (EGSL), specimens were collected from coastal surveys (scallops, sea cucumber, snow crab, and whelk surveys) onboard the CCGS Leim and offshore during the Ecosystemic Survey onboard the CCGS Teleost. Decapods were collected from various sampling gears (benthic beam trawl, modified Atlantic Western IIA otter trawl, Bacalao trawl, shrimp trawl, Digby scallop dredge, or modified sea cucumber dredge) and identified to the lowest possible taxonomic level and photographed, when possible. All specimens were frozen at sea (n = 995). In the lab, the identifications were validated or refined with the photos and the frozen specimens. DNA was extracted for 87 specimens and a section of COI gene was amplified in order to be sequenced using Sanger method. Sequences were compared with existing data using The Basic Local Alignment Search Tool (BLAST) in the National Center for Bio-technology Information Nucleotide database (NCBI-nt, including the GenBank database) to compare scientific names, where available.The present dataset includes 391 decapod species occurrences. DNA was extracted for a subset of 87 specimens (COI gene); sequences are publicly available on BOLD data portal under project code DDAO (see supporting document "citations_references.csv" for more information).The data are presented in Darwin Core format and are separated in three files:The "Activité_décapodes_DDAO_decapods_event_en" file contains information about missions, stations and deployments, which are presented under a hierarchical activity structure.The "Occurrence_décapodes_DDAO_decapods_en" file contains the taxonomic occurrences.The "ADN_décapodes_DDAO_decapods_DNA_en" file contains the DNA derived data.For further details, please refer to the technical report available in the supporting document named "citations_references.csv". USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

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.

A Conservation Unit (CU) is a group of wild Pacific salmon sufficiently isolated from other groups that, if extirpated, is very unlikely to recolonize naturally within an acceptable timeframe, such as a human lifetime or a specified number of salmon generations.Holtby and Ciruna (2007) provided a framework for aggregating the five species of salmon (genus Oncorhynchus) found on Canada’s Pacific coast into species-specific CUs based on three primary characteristics: ecotypology, life history and genetics. The first stage in the description of the Conservation Units is based solely on ecology. The ecotypologies used in this framework include a combined characterization of both freshwater and near-shore marine environments, and is termed “joint adaptive zone”. The second stage of the description involves the use of life history, molecular genetics, and further ecological characterizations to group and partition the first stage units into the final Conservation Units. The result is CUs that are described through the joint application of all three axes. It is important to note that CUs are distinct from other aggregates of Pacific salmon, such as designatable units (DUs) under the Species at Risk Act or management units (MUs).CU Counting Sites:Salmon spawner enumeration data in the Pacific Region is stored and managed in the New Salmon Escapement Database (NuSEDS). The term “escapement” is used to refer to the group of mature salmon that have ‘escaped’ from various sources of exploitation, and returned to freshwater to spawn and reproduce. This data is assigned to a “Counting Site”, which may be a complete watercourse with a marine terminus, a tributary to a larger watercourse, or a defined reach within a watercourse that may or may not encompass the entire population but represents an index of the abundance of that population. CU Status:CUs form the basic unit for assessment under Canada’s Policy for the Conservation of Wild Salmon Policy (WSP) (DFO 2005). The biological status of a CU is evaluated using a number of metrics (Holt et al. 2009; Holt 2009), which indicate a WSP status zone: Red (poor status), Amber (marginal status), or Green (healthy status). A final step then incorporates all metric and status-related information into a final integrated status for each CU, along with expert commentary to support the final status determination (e.g., DFO 2012; DFO 2016). This information is used as inputs to fisheries management processes to help prioritize assessment activities and management actions.Note: CU boundaries were reviewed in 2020-2021 and have been updated from the BC Freshwater Atlas 1:50,000 scale to the BC Freshwater Atlas 1:20,000 scale. The CU boundaries were last updated in March 2023. Please be aware that CUs may be reviewed and are subject to change without notice.Please refer to Conservation Unit Review Requests-Form and Summary for a list of CU review requests that are ongoing or have been finalized.

This spatial data identifies breeding zones used by forest managers and forest genetic associations to manage provincial forest genetic assets. The data: * shows the boundaries of breeding zones * identifies the primary or target species within each zone Species are associated with certain breeding programs, seed orchards and progeny (descendant) testing installations.

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.

A Conservation Unit (CU) is a group of wild Pacific salmon sufficiently isolated from other groups that, if extirpated, is very unlikely to recolonize naturally within an acceptable timeframe, such as a human lifetime or a specified number of salmon generations.Holtby and Ciruna (2007) provided a framework for aggregating the five species of salmon (genus Oncorhynchus) found on Canada’s Pacific coast into species-specific CUs based on three primary characteristics: ecotypology, life history and genetics. The first stage in the description of the Conservation Units is based solely on ecology. The ecotypologies used in this framework include a combined characterization of both freshwater and near-shore marine environments, and is termed “joint adaptive zone”. The second stage of the description involves the use of life history, molecular genetics, and further ecological characterizations to group and partition the first stage units into the final Conservation Units. The result is CUs that are described through the joint application of all three axes. It is important to note that CUs are distinct from other aggregates of Pacific salmon, such as designatable units (DUs) under the Species at Risk Act or management units (MUs).CU Counting Sites:Salmon spawner enumeration data in the Pacific Region is stored and managed in the New Salmon Escapement Database (NuSEDS). The term “escapement” is used to refer to the group of mature salmon that have ‘escaped’ from various sources of exploitation, and returned to freshwater to spawn and reproduce. This data is assigned to a “Counting Site”, which may be a complete watercourse with a marine terminus, a tributary to a larger watercourse, or a defined reach within a watercourse that may or may not encompass the entire population but represents an index of the abundance of that population. CU Status:CUs form the basic unit for assessment under Canada’s Policy for the Conservation of Wild Salmon Policy (WSP) (DFO 2005). The biological status of a CU is evaluated using a number of metrics (Holt et al. 2009; Holt 2009), which indicate a WSP status zone: Red (poor status), Amber (marginal status), or Green (healthy status). A final step then incorporates all metric and status-related information into a final integrated status for each CU, along with expert commentary to support the final status determination (e.g., DFO 2012; DFO 2016). This information is used as inputs to fisheries management processes to help prioritize assessment activities and management actions.Note: CU boundaries were reviewed in 2020-2021 and have been updated from the BC Freshwater Atlas 1:50,000 scale to the BC Freshwater Atlas 1:20,000 scale. The CU boundaries were last updated in March 2023. Please be aware that CUs may be reviewed and are subject to change without notice.Please refer to Conservation Unit Review Requests-Form and Summary for a list of CU review requests that are ongoing or have been finalized.

A Conservation Unit (CU) is a group of wild Pacific salmon sufficiently isolated from other groups that, if extirpated, is very unlikely to recolonize naturally within an acceptable timeframe, such as a human lifetime or a specified number of salmon generations.Holtby and Ciruna (2007) provided a framework for aggregating the five species of salmon (genus Oncorhynchus) found on Canada’s Pacific coast into species-specific CUs based on three primary characteristics: ecotypology, life history and genetics. The first stage in the description of the Conservation Units is based solely on ecology. The ecotypologies used in this framework include a combined characterization of both freshwater and near-shore marine environments, and is termed “joint adaptive zone”. The second stage of the description involves the use of life history, molecular genetics, and further ecological characterizations to group and partition the first stage units into the final Conservation Units. The result is CUs that are described through the joint application of all three axes. It is important to note that CUs are distinct from other aggregates of Pacific salmon, such as designatable units (DUs) under the Species at Risk Act or management units (MUs).CU Counting Sites:Salmon spawner enumeration data in the Pacific Region is stored and managed in the New Salmon Escapement Database (NuSEDS). The term “escapement” is used to refer to the group of mature salmon that have ‘escaped’ from various sources of exploitation, and returned to freshwater to spawn and reproduce. This data is assigned to a “Counting Site”, which may be a complete watercourse with a marine terminus, a tributary to a larger watercourse, or a defined reach within a watercourse that may or may not encompass the entire population but represents an index of the abundance of that population. CU Status:CUs form the basic unit for assessment under Canada’s Policy for the Conservation of Wild Salmon Policy (WSP) (DFO 2005). The biological status of a CU is evaluated using a number of metrics (Holt et al. 2009; Holt 2009), which indicate a WSP status zone: Red (poor status), Amber (marginal status), or Green (healthy status). A final step then incorporates all metric and status-related information into a final integrated status for each CU, along with expert commentary to support the final status determination (e.g., DFO 2012; DFO 2016). This information is used as inputs to fisheries management processes to help prioritize assessment activities and management actions.Note: CU boundaries were reviewed in 2020-2021 and have been updated from the BC Freshwater Atlas 1:50,000 scale to the BC Freshwater Atlas 1:20,000 scale. The CU boundaries were last updated in March 2023. Please be aware that CUs may be reviewed and are subject to change without notice. Please refer to Conservation Unit Review Requests-Form and Summary for a list of CU review requests that are ongoing or have been finalized.

A Conservation Unit (CU) is a group of wild Pacific salmon sufficiently isolated from other groups that, if extirpated, is very unlikely to recolonize naturally within an acceptable timeframe, such as a human lifetime or a specified number of salmon generations.Holtby and Ciruna (2007) provided a framework for aggregating the five species of salmon (genus Oncorhynchus) found on Canada’s Pacific coast into species-specific CUs based on three primary characteristics: ecotypology, life history and genetics. The first stage in the description of the Conservation Units is based solely on ecology. The ecotypologies used in this framework include a combined characterization of both freshwater and near-shore marine environments, and is termed “joint adaptive zone”. The second stage of the description involves the use of life history, molecular genetics, and further ecological characterizations to group and partition the first stage units into the final Conservation Units. The result is CUs that are described through the joint application of all three axes. It is important to note that CUs are distinct from other aggregates of Pacific salmon, such as designatable units (DUs) under the Species at Risk Act or management units (MUs).CU Counting Sites:Salmon spawner enumeration data in the Pacific Region is stored and managed in the New Salmon Escapement Database (NuSEDS). The term “escapement” is used to refer to the group of mature salmon that have ‘escaped’ from various sources of exploitation, and returned to freshwater to spawn and reproduce. This data is assigned to a “Counting Site”, which may be a complete watercourse with a marine terminus, a tributary to a larger watercourse, or a defined reach within a watercourse that may or may not encompass the entire population but represents an index of the abundance of that population. CU Status:CUs form the basic unit for assessment under Canada’s Policy for the Conservation of Wild Salmon Policy (WSP) (DFO 2005). The biological status of a CU is evaluated using a number of metrics (Holt et al. 2009; Holt 2009), which indicate a WSP status zone: Red (poor status), Amber (marginal status), or Green (healthy status). A final step then incorporates all metric and status-related information into a final integrated status for each CU, along with expert commentary to support the final status determination (e.g., DFO 2012; DFO 2016). This information is used as inputs to fisheries management processes to help prioritize assessment activities and management actions.Note: CU boundaries were reviewed in 2020-2021 and have been updated from the BC Freshwater Atlas 1:50,000 scale to the BC Freshwater Atlas 1:20,000 scale. The CU boundaries were last updated in March 2023. Please be aware that CUs may be reviewed and are subject to change without notice.Please refer to Conservation Unit Review Requests-Form and Summary for a list of CU review requests that are ongoing or have been finalized.