Extreme water level along the marine coastline is a result of a combination of storm surge, tides, and ocean waves. Future projections of climate change in the marine environment indicate that rising sea level and declining sea ice will cause changes in extreme water levels, which will impact Canada's coastlines and the infrastructure in these areas. Understanding these changes is essential for developing adaptation strategies that can minimize the harmful effects that may result.CAN-EWLAT is a science-based planning tool for climate change adaptation of coastal infrastructure related to future water-level extremes and changes in wave climate. The tool includes two main components: 1) vertical allowance and 2) wave climate. CAN-EWLAT was developed primarily for DFO Small Craft Harbours (SCH) locations, but it should prove useful for coastal planners dealing with infrastructure along Canada’s ocean coastlines.Cite this data as: Greenan B. Canadian Extreme Water Level Adaptation Tool (CAN-EWLAT) Published June 2022. Oceans Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

The RVI/CVI database is derived from the CanEcumene 3.0 GDB (Eddy, et. al. 2023) using a selection of socio-economic variables identified in Eddy and Dort (2011) that aim to capture the overall state of socio-economic conditions of communities as ‘human habitats’. This dataset was developed primarily for application in mapping socio-economic conditions of communities and regions for environmental and natural resource management, climate change adaptation, Impact Assessments (IAs) and Regional Assessments (RAs), and Cumulative Effects Assessment (CEA).The RVI/CVI is comprised of five sub-indicators: 1) population change, 2) age structure, 3) education levels, 4) employment levels, and 5) real estate values. Index values are based on percentile ranks of each sub-indicator, and averaged for each community, and for three ranked groups: 1) all of Canada, 2) by province, and 3) by population size. The data covers the Census periods of 2001, 2006, 2011 (NHS), 2016, and 2021.The index is mapped in two ways: 1) as ‘points’ for individual communities (CVI), and 2) as ‘rasters’ for spatial interpolation of point data (RVI). These formats provide an alternative spatial framework to conventional StatsCan CSD framework. (For more information on this approach see Eddy, et. al. 2020).============================================================================================Eddy, B.G., Muggridge, M., LeBlanc, R., Osmond, J., Kean, C., and Boyd, E. 2023. The CanEcumene 3.0 GIS Database. Federal Geospatial Platform (FGP), Natural Resources Canada. https://gcgeo.gc.ca/viz/index-en.html?keys=draft-3f599fcb-8d77-4dbb-8b1e-d3f27f932a4bEddy B.G., Muggridge M, LeBlanc R, Osmond J, Kean C, Boyd E. 2020. An Ecological Approach for Mapping Socio-Economic Data in Support of Ecosystems Analysis: Examples in Mapping Canada’s Forest Ecumene. One Ecosystem 5: e55881. https://doi.org/10.3897/oneeco.5.e55881Eddy, B.G.; Dort, A. 2011. Integrating Socio-Economic Data for Integrated Land Management (ILM): Examples from the Humber River Basin, western Newfoundland. Geomatica, Vol. 65, No. 3, p. 283-291. doi:10.5623/cig2011-044.

The Planning for an Environmental Response (PIER) initiative falls under the umbrella of the Government of Canada’s Oceans Protection Plan (OPP), whose goal is preserving marine ecosystems vulnerable to increased transportation and the development of the marine industry. The PIERs’ main mandate is to acquire and update biological sensitivity data under its jurisdiction for preparation and response purposes in the event of an oil spill.This dataset contains all observations of marine organisms noted during the analysis of 2959 underwater images sampled over a large extent of the coastal zone (≤10 m) of the Estuary and the Gulf of St. Lawrence (Quebec region). The dataset includes 21 490 occurrences of 150 taxa and informal categories including macroalgae, invertebrates and fish. Underwater images were collected between 2017 and 2021 according to a directed sampling protocol whose primary goal was to map large seaweed and eelgrass beds. Images were normally recorded as videos using a GoPro Hero camera installed on a pole and placed near the seabed from a small boat. The collected data served primarily as ground-truth data to validate coasting zone mapping based on aerial photographs within the framework of the PIER's initiative.The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event_information" file includes generic event information, including date and location. The "taxon_occurrence" file includes the original identifiers of the observed organisms (verbatimIdentification field), identification remarks and their taxonomy.Taxonomic names were verified on the World Register of Marine Species (WoRMS) to match recognized standards. The WoRMS match has been put in the scientificNameID field in the occurrence file. Data quality control was performed using the R packages obistools and worrms. All sampling locations were plotted on a map to perform a visual check confirming that the latitude and longitude coordinates were within the described sampling area.A visual dictionary was developed as an identification aid and accompanies this dataset (unilingual french only, the English version will be published soon). More data, including a visibility index, estimated macroalgae and eelgrass cover, substrate type and dominant macroalgae and animals were recorded but not included in this dataset. These data may be made available upon request.CreditsProvencher-Nolet, L., Paquette, L., Pitre, L.D., Grégoire, B. and Desjardins, C. 2024. Cartographie des macrophytes estuariens et marins du Québec. Rapp. Tech. Can. Sci. halieut. Aquat. 3617 : v + 99 p.Grégoire, B., Pitre, L.D., Provencher-Nolet, L., Paquette, L. and Desjardins, C. 2024. Distribution d’organismes marins de la zone côtière peu profonde du Québec recensés par imagerie sous-marine de 2017 à 2021. Rapp. tech. can. sci. halieut. aquat. 3616 : v + 78 p.

ENV - Environment and conservation (environment)Environmental resources, protection, and conservation. For example, resources describing pollution, waste storage and treatment, environmental impact assessment, environmental risk, and nature reserves. )

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

Environmental Monitoring Stations (EMS) spatial points coverage for the Province by LOCATION TYPES. The following spatial layers reference this as a data source: 1. Environmental Monitoring - All Stations 2. Environmental Monitoring Stations - Air Monitoring (Ambient Air Site) 3. Environmental Monitoring Stations - Air Monitoring (Air Permit) 4. Environmental Monitoring Stations - Water Sites (Water Monitoring) 5. Environmental Monitoring Stations - Water Sites (Water Permits) 6. Environmental Monitoring Stations - Water Sites (Well) 7. Environmental Monitoring Stations - Water Sites (Observation Well) 8. Environmental Monitoring Stations - Water Sites (Spring)

Bay-scale empirical demonstrations of how bivalve aquaculture alters plankton composition, and subsequently ecological functioning and higher trophic levels, are lacking. Temporal, inter- and within-bay variation in hydrodynamic, environmental, and aquaculture pressure limit efficient plankton monitoring design to detect bay-scale changes and inform aquaculture ecosystem interactions. Here, we used flow cytometry to investigate spatio-temporal variations in bacteria and phytoplankton (< 20 µm) composition in four bivalve aquaculture embayments. We observed higher abundances of bacteria and phytoplankton in shallow embayments that experienced greater freshwater and nutrient inputs. Depleted nutrient conditions may have led to the dominance of picophytoplankton cells, which showed strong within-bay variation as a function of riverine vs freshwater influence and nutrient availability. Although environmental forcings appeared to be a strong driver of spatio-temporal trends, results showed that bivalve aquaculture may reduce near-lease phytoplankton abundance and favor bacterial growth. We discuss aquaculture pathways of effects such as grazing, benthic-pelagic coupling processes, and microbial biogeochemical cycling. Conclusions provide guidance on optimal sampling considerations using flow cytometry in aquaculture sites based on embayment geomorphology and hydrodynamics.Cite this data as: Sharpe H, Lacoursière-Roussel A, Barrell J (2024). Monitoring bay-scale bivalve aquaculture ecosystem interactions using flow cytometry. Version 1.2. Fisheries and Oceans Canada. Samplingevent dataset. https://ipt.iobis.org/obiscanada/resource?r=monitoring_bay-scale_bivalve_aquaculture_ecosystem_interactions_using_flow_cytometry&v=1.2

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.

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.

The “Terrestrial Ecozones of Canada” dataset provides representations of ecozones. An ecozone is the top level of the four levels of ecosystems that the National Ecological Framework for Canada defines. The framework divides Canada into 15 terrestrial ecozones that define its ecological mosaic on a sub-continental scale. Ecozones represent an area of the earth’s surface as large and very generalized ecological units. These units are characterized by interactive and adjusting abiotic and biotic factors.