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RI_542

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    In 2018 and 2019 Fisheries and Oceans Canada conducted a project to relocate American Eel (Anguilla rostrata) from Port Dalhousie Harbour to mitigate potential impacts of in-water construction prior to and during an essential harbour revitalization project. American Eel are designated as Endangered under the Province of Ontario’s Endangered Species Act and were confirmed to be present in the area during initial sampling efforts of this project. While a combination of passive eel traps and boat electrofishing were used to capture eels, this dataset includes passive capture data only. A total of four eels were captured using eel traps and all individuals were relocated to Hamilton Harbour. Only two of the four eels captured were large enough to be tagged with acoustic transmitters, both of which eventually returned to Port Dalhousie from Hamilton Harbour. All other fish species captured in the traps were identified, counted and released at Port Dalhousie.

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    The National Ecological Framework for Canada's "Surficial Geology by Ecozone” dataset contains tables that provide surficial geology information with the ecozone 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.

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    This dataset includes the extent of the boreal forest as well as the extent of managed boreal forest worldwide. The extent of boreal forest was produced from Brandt et al. (2013) and a modified version of Goudilin (1987). Managed forest was defined as suggested by IPCC (2003) using data from FAFS (2009), Gauthier et al. (2014), See et al. (2015) and AICC maps. The extent of managed forest mostly includes areas managed for wood production, areas protected from large-scale disturbances as well as formal protected areas. Both boreal forest extent and managed boreal forest extent are available in raster and vector data. Please cite this data product as: Boucher, D., D.G. Schepaschenko, S. Gauthier, P. Bernier, T. Kuuluvainen, A. Z. Shvidenko. 2024. World boreal forest and managed boreal forest extent. DOI: 10.23687/88d70716-2600-4995-8d5f-86f96e383abf These data were presented in the following article: Gauthier, S., P. Bernier, T. Kuuluvainen, A. Z. Shvidenko, D. G. Schepaschenko. 2015. Boreal forest health and global change. Science 349:819-822. DOI: 10.1126/science.aaa9092 References: J. P. Brandt, M. D. Flannigan, D. G. Maynard, I. D. Thompson, W. J. A. Volney, Environ. Rev. 21, 207–226 (2013) I. S. Goudilin, Landscape map of the USSR. Legend to the landscape map of the USSR. Scale 1:2 500 000. Moscow, Ministry of Geology of the USSR (1987) [in Russian]. Inter-governmental panel on climate change (IPCC). J. Penman, M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, et al., Eds., Good practice guidance for land use, land-use change and forestry (IPCC/NGGIP/IGES, Kanawaga, 2003) Federal Agency of Forest Service (FAFS), Forest Fund of the Russian Federation (state by 1 January 2009) (Federal Agency of Forest Service, Moscow, 2009) [in Russian] S. Gauthier et al., Environ. Rev. 22, 256–285 (2014). See et al., Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki. Technological Forecasting and Social Change. (2015). doi:10.1016/j.techfore.2015.03.002 Alaska Interagency Coordination Center (AICC). Fire Information. https://fire.ak.blm.gov/content/maps/aicc/Large%20Maps/Alaska_Fire_Management_Options.pdf (the version of 2014 was used)

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    The National Ecological Framework for Canada's "Land Cover by Ecodistrict” dataset provides land cover information within the ecodistrict framework polygon. It provides landcover codes and their English and French language description as well as information about the percentage of the polygon that the component occupies.

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    This dataset was collected in support of a Competitive Science and Research Fund project (21-CC-05-06 Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop: larval supply, recruitment and adaptive capacity to multiple global change drivers) lead by Fisheries and Oceans Canada (DFO). The objective of this research is to characterize coastal environmental conditions associated with scallop spawning and larval drift in Passamaquoddy Bay, New Brunswick. This dataset includes temperature, conductivity, salinity, sigma-theta, sea pressure, and depth information taken at weekly intervals at the sampling stations. In total, this dataset represents a total of 62 CTD profiles collected across 3 sampling stations over 22 sampling days from June to October 2022. Sampling stations were selected to compare scallop recruitment signals from Chamcook Harbour, a decommissioned scallop aquaculture site in Big Bay (MS-1077) and in the middle of Passamaquoddy Bay. Data were processed in accordance with instrumentation manufacturer guidelines and DFO Ocean Data and Information Section QAQC procedures. Cite this data as: Miller, E., Quinn, B., Azetsu-Scott, K., Childs, D., Gabriel, C-E., Newhook, M. 2025. Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop. Published October 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B

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    The “Terrestrial Ecoregions of Canada” dataset provides representations of ecoregions. An ecoregion is a subdivision of an ecoprovince and is characterized by distinctive regional ecological factors, including climate, physiography, vegetation, soil, water, and fauna. For example, the Maritime Barrens ecoregion (no. 114) is one of nine ecoregions within the Newfoundland ecoprovince.

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    The Prairie Soil Zones file shows the general distribution of major soil zones across the Prairie region of Canada. Soil zones (based on the Canadian System of Soil Classification) are named based on the dominant soil classification of the soils in each zone. Data extent is limited to the Agricultural Zone as defined in Soil Landscapes of Canada v 3.0 (Lefebvre et al. 2005).

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    Funded through DFO's Strategic Program for Ecosystem-based Research and Advice (SPERA), this benthic survey covers several seabed areas adjacent to Deer Island and Campobello Island, the Wolves Islands, and Grand Manan (NB) over a two-year study period (2016-2017). One hundred and fifty drift camera transects were completed within the ~91 sq-km study region collecting continuous high-definition video with periodic 4K resolution video (provided by a downward facing Blackmagic Production Camera 4K equipped with video lights). A Nikon D800 36.1 megapixel digital still imagery camera (equipped with a studio strobe light) captured seafloor images at ~30s intervals over a maximum 25-minute drift survey period. The camera was triggered by lowering the camera frame within 1 m of the seabed, releasing tension on a trigger weight suspended below the frame. Camera location was tracked using an ultra-short baseline acoustic positioning system (Tracklink 1500HA transceiver with 1505B transponder on the camera frame). Species presence/absence, abundance, and bottom type was recorded manually using PhotoQuad v1.4 software. An average field of view of 0.7 x 0.5 m was determined from a subset of digital still images within which the 10 cm diameter trigger weight was fully in view. Thirty-eight key and common species were described using explicit taxonomic identifiers, while other species were recorded within broader general categories (e.g. unidentified Cnidaria). Identification was made to the lowest possible taxonomic level. Primary bottom-type was defined as the grain size with the most percent coverage for each image/video interval. Grain size limits were determined using the Wentworth scale. Cite this data as: Lawton P. Benthic Species Presence/Absence in the Lower Bay of Fundy Derived From High Resolution Video and Still Imagery. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

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    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

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    In 2021, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Sentinel-2), and radar (RCM) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincial crop insurance companies in Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change; Ontario Ministry of Agriculture, Food and Rural Affairs; University of Guelph - Ridgetown campus; British Columbia Ministry of Agriculture; and data collection supported by our regional AAFC Research and Development Centres in St. John's, Charlottetown, Kentville, Fredericton, Guelph and Summerland. Due to COVID-19 travel restrictions and forest fires, complete sampling coverages in BC was not possible, as a result the general agriculture class (120) is found in this province in areas where there was no ground data collected.