Towfish (sidescan and video) and echo sounder surveys were utilized to examine bottom type and macrophyte cover within the area of two coastal marine finfish aquaculture sites, one in New Brunswick (Welch Cove) and one in Nova Scotia (Jordan Bay). Both towfish and echo sounder data could be used independently of one another. However, the towfish data were very useful for ground truthing echo sounder based classifications. All survey data were placed into a GIS which could be used to answer management questions such as the placement of cages at sites, benthic impacts and baseline conditions to determine long term changes. Cite this data as: Vandermeulen H. Data of: Exploratory Video-Sidescan and Echosounder Survey of Welch Cove. Published: June 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/0083e317-8bb5-492a-8348-c021e183f307

The National Ecological Framework for Canada's "Surficial Geology by Ecoprovince” dataset contains tables that provide surficial geology information with the ecoprovince framework polygons. It provides codes that characterize surficial geology (unconsolidated geologic materials) and their English and French-language descriptions as well as information about the area and percentage of the polygon that the material occupies.

The “Biomass Inventory Cartographic Layer” dataset provides the information that is used with the Biomass Report Framework to generate a visual representation of the availability of agricultural and forestry biomass and municipal solid waste in Canada. In addition to yield and production information for biomass produced by the agricultural and forestry industries, this dataset also provides information about the demand for agricultural residues for cattle feed and bedding, tillage systems currently in use on agricultural lands, and land suitability for hybrid poplar and willow plantations that are grown specifically to produce biomass. Agricultural information includes the median annual residue yield and available residue amounts. Residue yields were calculated using crop-to-residue ratios. The available residue information includes the amount that is available after adjusting for the estimated demand of straw used for cattle feed and bedding. Forestry estimates include average residue production, based on forestry activities including permitted amounts of harvesting, mills in operation and mill production. Municipal Solid Waste information includes organic waste (food and yard), paper waste and total residential municipal solid waste (which includes organic and paper waste, among others).

The Ontario Raw Point Cloud (Imagery-Derived) is elevation point cloud data created from aerial photography from the Geospatial Ontario (GEO) imagery program. It was created using a pixel-autocorrelation process based on aerial photography collected by the imagery contractor for the GEO imagery program. The dataset consists of overlapping tiles in LAZ format and is 6.29 terabytes in size. Tiles are overlapping because the pixel-autocorrelation process extracts elevation values from overlapping stereo photo strips. No classification has been applied to the point cloud, however they are encoded with colour (RGB) values from the source photography. This data is for geospatial tech specialists, and is used by government, municipalities, conservation authorities and the private sector for land use planning and environmental analysis. __Related data__ For a product in non-overlapping tiles with a ground classification applied, see the [Ontario Classified Point Cloud (Imagery-Derived)](https://geohub.lio.gov.on.ca/datasets/febf17330adb4100a22738e1684b5feb). Raster derivatives have been created from the point clouds for some imagery projects. These products may meet your needs and are available for direct download. For a representation of bare earth, see [Ontario Digital Elevation Model (Imagery-Derived)](https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-elevation-model-imagery-derived/about). For a model representing all surface features, see the [Ontario Digital Surface Model (Imagery-Derived)](https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-surface-model-imagery-derived/about).

Effective fisheries and habitat management processes require knowledge of the distribution of areas of high ecological or biological significance. On the Scotian Shelf and Slope, a number of benthic ecologically or biologically significant areas consisting of habitat-forming species such as sponges and deep-water corals have been identified. However, knowledge of their spatial distribution is largely based on targeted surveys that are limited in their spatial extent. We used a species distribution modelling approach called random forest (RF) to predict the probability of occurrence and biomass of sponges, sea pens, and large and small gorgonian corals across the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. We also modelled the rare sponge Vazella pourtalesi, which forms the largest known aggregation of its kind on the Scotian Shelf. We utilized a number of data sources including DFO multispecies trawl catch data and in situ benthic imagery observations. Most models had excellent predictive capacity with cross-validated Area Under the Receiver Operating Characteristic Curve (AUC) values ranging from 0.760 to 0.977. Areas of suitable habitat were identified for each taxon and were contrasted against their known distribution and when applicable, the location of closure areas designated for their protection. Generalized additive models (GAMs) were developed to predict the biomass distribution of each taxonomic group and serve as a comparison to the RF models. The RF and GAM models provided comparable results, although GAMs provided superior predictions of biomass along the continental slope for some taxonomic groups. In the absence of data observations, the results of this study could be used to identify the potential distribution of sensitive benthic taxa for use in fisheries and habitat management applications. These results could also be used to refine significant concentrations of these taxa as identified through the kernel density analyses. Cite this data as: Beazley, Lindsay; Kenchington, Ellen; Murillo-Perez, Javier; Lirette, Camille; Guijarro-Sabaniel, Javier; McMillan, Andrew; Knudby, Anders (2019). Species Distribution Modelling of Corals and Sponges in the Maritimes Region for Use in the Identification of Significant Benthic Areas. Published July 2023. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/356e92f3-5bf3-4810-98b1-3e10cd7742aa

This dataset contains measurements of water (chemistry and algal pigments) and sediment (chemistry and size fraction) quality in nearshore areas of Lake Huron surrounding cage aquaculture operations including North Channel, Manitoulin Island and Georgian Bay. Seasonal ice-free monitoring and sampling occurred in Ontario nearshore areas between 1998-2016. The dataset also contains the limits of detection and quantification for the parameters measured, GPS coordinates and depths (sample, Secchi, composite and maximum) for the lake sampling locations.

Description: Spatial information on ecologically important species is needed to support marine spatial planning initiatives in British Columbia’s (BC) marine environment. For data deficient taxa, such as shark species, species distribution models that integrate presence-absence data from different sources can be used to predict their coastwide distributions. Here we provide spatial estimates of the distribution of Blue Shark (Prionace glauca), Salmon Shark (Lamna ditropis), Pacific Sleeper Shark (Somniosus pacificus) and Bluntnose Sixgill Shark (Hexanchus griseus). These estimates were generated using spatial generalized linear mixed effects models and are based on data from two scientific surveys and the commercial hook and line, midwater trawl and bottom trawl fisheries. For each species, we provide predicted probability of occurrence and prediction uncertainty at a 3 km resolution for the British Columbia coast, and parameter estimates for model covariates (depth, slope, year, data source). Results show variable predicted distributions across species, with Blue Shark and Pacific Sleeper Shark showing higher probability of presence along the continental slope, while Salmon Shark show low probability of occurrence coastwide and Bluntnose Sixgill Shark show the highest probability of occurrence in the Strait of Georgia. The results from this study can support ongoing marine spatial planning initiatives in the BC and support the conservation and management of these important species. Methods: Data Sources The species distribution models (SDMs) are based on data from two fishery independent scientific surveys and from the commercial hook and line fishery, which are all conducted within Canadian Pacific waters. The scientific surveys include the Fisheries and Oceans Canada (DFO) hard bottom longline surveys and the International Pacific Halibut Commission (IPHC) fishery-independent setline survey. The study area is bound by the outer convex hull of these three data sources. Other DFO research surveys, such as the groundfish synoptic bottom trawl surveys, midwater trawl surveys and sablefish trap surveys were investigated as potential data sources, but were found to have insufficient presence observations for the species of interest to warrant their inclusion in the analysis. For more information on the details of the source data please refer to Proudfoot et al. 2024. Modelling Approach and Comparison For each species, we fit a suite of generalized linear mixed effects models (GLMMs) using the sdmTMB package (Anderson et al. 2022). For each species, we fit four models, each with a different set of fixed effects/environmental predictors. Additionally, we compared the predictive power of four models for each species, with each model having a different combination of environmental predictors (i.e., slope, depth, slope + depth, none). A summary of the candidate models is provided in Table 2 of Proudfoot et al. 2024. For each species, we selected the model with the highest predictive accuracy (assessed using the predicted log likelihood based on the cross-validation) as the best fit. Spatial Species Distribution Predictions We made predictions of species occurrence using the selected model and a 3 km resolution spatial prediction grid. Our predictions were made for the entire BC coast, and species distribution predictions were made using models fit to the full dataset, as opposed to models fit using cross-validation. We made predictions with year set to 2014 (the approximate midpoint of the dataset) and type set to IPHC (the dataset with the most even spatial distribution of data points). Uncertainties: Because limited survey and commercial catch data exists for deep areas off the continental shelf, predictions in these areas are likely more uncertain than predictions on the shelf. To illustrate this, uncertainty (standard deviation derived from the 500 simulated values from the joint precision matrix of selected models) was mapped across the full study area for each species. Additionally, because these models are based on data that likely do not span the full spatiotemporal extent of the species’ habitat (i.e., mid depths, surface waters, and data across all seasons may not be captured), these results illustrate a snapshot of occurrence but do not account for more complex migration and movement patterns undertaken by these species.

Estimates of wind-driven upwelling of colder water on the Scotian Shelf along the Nova Scotia coastline from 1993 to 2022 (inclusive) are presented, calculated using surface and 55m-depth water temperatures from the Global Ocean Physics Reanalysis (GLORYS12v1) product, and also ERA5 surface winds. GLORYS12v1 is a 1/12o data-assimilative reanalysis modelling product from Mercator Ocean International, implemented by the Copernicus Marine Environment Monitoring Service (CMEMS; (https://doi.org/10.48670/moi-00021). ERA5 is a weather forecast produced by the European Centre for Medium-Range Weather Forecasts (ECMWF; https://doi.org/10.24381/cds.adbb2d47). Daily estimates are given of upwelling area and intensity (temperature anomaly between upwelled and non-upwelled water), calculated over the area of interest (AOI) on the Scotian Shelf. Yearly estimates are given of total upwelling duration and cumulative area for the year in question, further broken down into seasons: Spring (March-May), Summer (June-August), and Fall (September-November). Lastly, estimates of the yearly start/end dates of the cold-water upwelling season (lasting generally from March to November) are estimated. The sea surface temperature (SST) data from GLORYS were validated against in-situ buoy observations (https://www.meds-sdmm.dfo-mpo.gc.ca/alphapro/wave/waveshare/metaData/meta_c44258.csv) and satellite-derived SST produced by Canadian Meteorological Centre (https://doi.org/10.5067/GHCMC-4FM02 and https://doi.org/10.5067/GHCMC-4FM03. These products may be used to gain knowledge of interannual variability of coastal upwelling on the ScS over the past 30 years. Cite this data as: Tao, J., Casey, M., Lu, Y., and Shen, H. Upwelling indices derived from GLORYS12 Model and ERA5 surface wind on the Scotian Shelf during 1993-2022. Published: December 2024. Ecosystems and Oceans Science, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS. https://open.canada.ca/data/en/dataset/a2da6bfd-92e3-434e-b9bd-456b7fc9e92b

The annual summer scallop surveys on the principal grounds in the Bay of Fundy follow stratified-random designs. The gear comprises a ‘Digby scallop drag’ with four ‘buckets’, each of 760 mm inside width, their bags being made of 74 mm steel-wire rings linked by rubber washers. A comparative data set of three scallop grounds (Digby, Lurcher Shoal and Grand Manan) was produced comprised of 190 stations sampled in 1997 and 213 from 2007–08. Presence/absence of a common suite of 68 benthic invertebrate taxa were recorded: 43 individual species, 20 additional genera and five higher taxa, all drawn from nine phyla. Each taxon was coded for each of seven biological traits (each with associated modalities), selected for their assumed relevance to environmental drivers. A score between 0 and 3 was assigned based on the literature for the taxon’s affinity to each modality, using ‘fuzzy coding’. Non-zero scores were assigned to as many modalities as required to represent the traits of the taxon’s adult stage. The resulting taxa x traits matrix, of 68 taxa by 27 modalities, is provided here along with the metadata for each station sampled. In addition, fourteen environmental variables, deemed relevant to benthic epifauna and representing both seabed sediments and the water column, were quantified for each survey station. Seabed depth, mean grain size, mean significant wave height, mean seabed shear stress, root mean square tidal current speed 1 m above the seabed and combined averaged wave-current shear velocity were each extracted from a sediment transport model for the Bay of Fundy prepared by Li et al. (2015). Mean values for current velocities, salinity and temperature for both surface and bottom layers, plus maximum mixed layer depth and bottom shear were each drawn from the Bedford Institute of Oceanography North Atlantic Model (BNAM: Wang et al., 2018). BNAM values averaged across 1990–2015 were used when examining faunal differences among survey areas, but explorations of temporal change used annual values for 1997 and 2007 individually. The variable nomenclature in the attached spreadsheet follows those of Li et al. (2015) and Wang et al. (2018). Results of the spatial and temporal analyses of these data are found in Staniforth et al. (2023). The values for each of the environmental variables are provided in the spreadsheet below. Their interpolated surfaces are also provided. Cite this data as: MacDonald, Barry; Staniforth, Calisa; Lirette, Camille; Murillo, Francisco; Kenchington, Ellen; Kenchington, Trevor (2023). Benthic Megafaunal Assemblages on Scallop Fishing Grounds in the Bay of Fundy (1997 and 2007). Published May 2024. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/935836da-a565-4f1e-806e-d354d8db252c

In 1998, Fisheries and Oceans Canada (DFO) published an atlas called "Traditional Fisheries Knowledge for the Southern Gulf of St. Lawrence". The document is composed of a series of maps that contain useful information primarily on nearshore fisheries and fish habitat in the eastern shore of New Brunswick, Prince Edward Island and the Gulf Shore of Nova Scotia. It was used as a working tool to assist in the development of integrated coastal zone management plans, resource management plans, and more. Between 1994 and 1997, data collectors and fishery officers interviewed local fishers and industry representatives. The purpose of these interviews was primarily to gain information on local fishing activities and the location of fisheries' resources and their habitats. The data and information was vetted through a process of verification with scientists, fishers, locals, industry representatives, and government officials. Maps were then compiled for 14 commercially important fish species and made publicly available to consult. These include lobster, rock crab, scallop, snow crab, toad crab, herring, mackerel, American plaice, cod, witch flounder (grey sole), hake, halibut, winter flounder, and unspecified groundfish. This data resource also includes the other 27 species originally not included in the atlas.