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    This project was completed by the Coastal Environmental Baseline Program (Coastal and Freshwater Ecology Section) in the Newfoundland and Labrador Science Branch of Fisheries and Oceans Canada (DFO). From 2018 to 2022 baseline biological and physical data were collected in Placentia Bay using Atlantic Zone Monitoring Program (AZMP) and Cold Ocean Productivity Experiment (COPE) protocols. Complementary data were collected in the bay using moored CTDs. Where possible, sampling was conducted monthly at 4 sites between May and November to capture broad scale spatial and temporal trends. Additionally, data were collected bi-weekly in April and May, and monthly from June to September at one of these sites to capture finer scale temporal trends, such as spring blooms, in collaboration with Dr. C. McKenzie. Phytoplankton were collected using vertical net tows and niskins. Zooplankton were collected using vertical net tows. CTDs were used to collect physical and biogeochemical water column data including temperature, pressure, salinity, depth, chlorophyll-a, turbidity, dissolved oxygen, pH, photosynthetic active radiation (PAR), fluorescent dissolved organic matter (FDOM), and conductivity. Water biogeochemistry data were obtained by collecting water samples with niskins at depths of 5, 10, 20, 30, 40m, and 10m above bottom to measure nutrients, chlorophyll-a, carbonates, and particulate organic carbon and nitrogen (POC/PON). Additionally, eDNA samples were taken at each of the 4 sampling sites. This record contains the geographic locations of the sites, and information on the timing and type of data collected at each site.

  • CanCoast is a geospatial database of the physical characteristics of Canada's marine coasts. It includes both feature classes that are not expected to change through time, and feature classes that are expected to change as climate changes. CanCoast includes: wave-height change with sea ice (early and late 21st century); sea-level change (early and late century); ground ice content; coastal materials; tidal range; and backshore slope. These are mapped to a common high-resolution shoreline and used to calculate indices that show the coastal sensitivity of Canada's marine coasts in modelled early and late 21st century climates.

  • CanCoast is a geospatial database of the physical characteristics of Canada's marine coasts. It includes both feature classes that are not expected to change through time, and feature classes that are expected to change as climate changes. CanCoast includes: wave-height change with sea ice (early and late 21st century); sea-level change (early and late century); ground ice content; coastal materials; tidal range; and backshore slope. These are mapped to a common high-resolution shoreline and used to calculate indices that show the coastal sensitivity of Canada's marine coasts in modelled early and late 21st century climates.

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    The data in this dataset represent an amalgamation of sea turtle sighting, stranding, and entrapment events, mainly near Newfoundland and Labrador (NL), Canada. This document summarises the detection events data for Leatherback (Dermochelys coriacea), Loggerhead (Caretta caretta), and Green (Chelonia mydas) Turtles that has been collected from opportunistic and systematic survey sources, plus stranding and entrapment records, in the waters of NL from 1946 to 2023. To a much lesser extent there are also detection records for the southern Gulf of St. Lawrence. Scotian Shelf, and northeastern U.S. waters. These detection records are mostly derived from opportunistic reports, so there are rarely data for a report that includes measures of the observer effort expended to make the detection, and rarely associated imagery. During DFO aerial surveys there are measures of effort in most cases, enabling the turtle sightings reports to be used in habitat modelling (e.g., Mosnier et al. 2018). Most of the information variables (such as “Date”, “Latitude”, “Longitude”, “Number of Animals”) have been obtained from the detection report. In some cases data for variables such as “Location Reliability”, “ID Reliability”, “Platform”, and “Strand or Entrapment Outcome” were derived from interpretation of the comments associated with the report, if available. For description of the variables in the dataset see the Data Dictionary. References: Mosnier, A., Gosselin, J.-F., Lawson, J., Plourde, S., and Lesage, V. 2018. Predicting seasonal occurrence of leatherback turtles (Dermochelys coriacea) in eastern Canadian waters from turtle and sunfish (Mola mola) sighting data and habitat characteristics. Can. J. Zool. 97: 464-478. https://doi.org/10.1139/cjz-2018-0167

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    Línurnar sýna friðunarsvæði, þar sem eldi laxfiska (fam. salmonidae) í sjókvíum er óheimilt skv. auglýsingu nr. 460/2004.

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    DFO’s Oceans and Coastal Management Division (OCMD) in the Maritimes Region has updated its fisheries landings maps for 2010–2014. These maps will be used for decision making in coastal and oceans management, including mitigating human use conflicts, informing environmental emergency response operations and protocols, informing Marine Stewardship Council certification processes, planning marine protected area networks, assessing ecological risks, and monitoring compliance and threats in coral and sponge closures and Marine Protected Areas. Fisheries maps were created to identify important fishing areas using aggregate landed weight (kg) per 2 x 2-minute grid cell for selected species/gear types. This dataset has been filtered to comply with the Government of Canada's privacy policy. Privacy assessments were conducted to identify NAFO unit areas containing data with less than five vessel IDs, license IDs and fisher IDs. If this threshold was not met, catch weight locations were withheld from these unit areas to protect the identity or activity of individual vessels or companies. Maps were created for the following species/gear types: 1. Atlantic Halibut 2. Bluefin Tuna 3. Bottom Longline Groundfish 4. Bottom Trawl Groundfish 5. Cod 6. Cod, Haddock, Pollock 7. Cusk 8. Dogfish 9. Flatfish 10. Gillnet Groundfish 11. Greenland Halibut 12. Groundfish 13. Groundfish (quarterly composites Q1, Q2, Q3, Q4) 14. Hagfish 15. Herring 16. Large Pelagics 17. Mackerel 18. Monkfish 19. Offshore Clam 20. Offshore Lobster 21. Grey Zone Lobster 22. Other Crab 23. Other Tuna 24. Pollock 25. Porbeagle, Mako and Blue Shark 26. Red Hake 27. Redfish 28. Scallop 29. Scallop (quarterly composites Q1, Q2, Q3, Q4) 30. Sculpin 31. Sea Urchin 32. Shrimp 33. Silver Hake 34. Skate 35. Snow Crab 36. Squid 37. Swordfish 38. White Hake 39. Wolffish

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    The map displays bedrock formations at or near the surface of the land, on the sea floor above the continental crust that forms the Canadian landmass, and oceanic crust surrounding the landmass. The bedrock units are grouped and coloured according to geological age and composition. The colours of offshore units and oceanic crust are paler and more generalized than those on land, although the constituent units offshore are still easily discernible from their dashed boundaries. This colour design, coupled with the use of a white buffer zone at the coast allows the coastline of Canada to be readily distinguished and still show the grand geological architecture of the Canadian landmass. The map also shows major faults that have disrupted the Earth's crust, onshore and offshore, and a variety of special geological features such as kimberlite pipes, which locally contain diamonds, impact structures suspected to have been caused by meteorites, and extinct and active spreading centres in the surrounding oceans.

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    A vector representation of stream networks is a crucial dataset for the modelling the surface water and groundwater components of the hydrologic cycle. For many usages a crucial attribute of the drainage network is a digital topology and hierarchal stream order attribute (e.g., Strahler stream order). In Canada jurisdictional stream networks are available for the provinces and territories and nationally for Canada in the National Hydrological Network (NHN) dataset. Unfortunately, the NHN data lacks the same topological and attribute information that is available for numerous provinces due to standardization for the entire country. For Canada1Water it was also necessary to have a harmonized dataset with the United States, for both the southern transboundary watersheds and the Alaskan watersheds. This report documents the processes completed to upgrade the topological and graph network support for NHN and provide continuous connectivity with US datasets. It also highlights and corrects a number of stream density and stream order issues that occur within Canada across provincial and territorial borders and NTS tiles. All vector processing was completed in RivEX software extension for ArcMap. Following complete topological correction stream classification was assigned and a table of the node graph network developed. Additional work was then completed to normalize stream density particularly amongst low-order streams between British Columbia and the Yukon and amongst local NTS tiles in Quebec and Ontario. Corrected NHN Strahler stream order assignment was validated against a number of provincial and watershed datasets, all of which already have Strahler stream order attributed. These datasets are the same underlying digitized vector data, so there are no differences in node or polyline positions. Strahler stream order assignment validation was only done by visual comparison as due to differences in vector segments a statistical comparison is complicated. The transboundary integrated C1W stream network with complete classification provides a seamless national dataset to support transdisciplinary studies (fisheries, wildlife, health, pesticide and nutrient issues, mining impact, ecosystem restoration, numeric modelling) that involve a knowledge of stream distribution and ranking.

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    The Oceans Act (1997) commits Canada to maintaining biological diversity and productivity in the marine environment. A key component of this is to identify areas that are considered ecologically or biologically significant. Fisheries and Oceans Canada (DFO) Science has developed guidance on the identification of Ecologically or Biologically Significant Areas (EBSAs) (DFO 2004) and has endorsed the scientific criteria of the Convention on Biological Diversity (CBD) for identifying ecologically or biologically significant marine areas as defined in Annex I of Decision IX/20 of its 9th Conference of Parties. These criteria were applied to the Newfoundland and Labrador (NL) Shelves Bioregion in two separate data-driven processes. The first process focused on the area north of the Placentia Bay-Grand Banks (PBGB) Large Ocean Management Area (LOMA) (DFO 2013). The second process focused on the PBGB area (DFO 2019), where EBSAs had previously been identified using a more Delphic approach (Templeman 2007). In both cases, an EBSA Steering Committee, comprised of experts in oceanography, ecosystem structure and function, taxa-specific life histories and Geographic Information Systems (GIS) guided the process by advising or aiding in the identification, collection, processing and analysis of data layers, as well as participating in the final selection of candidate EBSAs (Wells et al. 2017, Ollerhead et al. 2017, Wells et al. 2019). All information was compiled in a GIS and a hierarchical approach was used to review individual data layers and groupings of data layers. Peer review meetings were held for both processes, during which candidate EBSAs were reviewed and the final EBSAs were agreed upon and delineated. In the northern study area, a total of fifteen EBSAs were identified and described; three of these areas are primarily coastal areas; seven are in offshore areas; four EBSAs straddle coastal and offshore areas; and one is a transitory EBSA that follows the southern extent of pack ice. In the PBGB study area, fourteen EBSAs were identified in two different categories: seven based on coastal data and seven based on offshore data. In comparing the new PBGB EBSAs to those identified in 2007, nine of them overlap spatially and are based on similar features; however, there were some variations in the boundaries. Two of the EBSAs that were identified in 2007 were no longer considered EBSAs in 2017, but portions of both of these areas were captured in part by other EBSAs. Five new EBSAs were identified in areas not previously considered. References: DFO, 2004. Identification of Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Ecosystem Status Rep. 2004/006. DFO. 2013. Identification of additional Ecologically and Biologically Significant Areas (EBSAs) within the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2013/048. DFO. 2019. Re-evaluation of the Placentia Bay-Grand Banks Area to Identify Ecologically and Biologically Significant Areas . DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2019/040. Ollerhead, L.M.N., Gullage, M., Trip, N., and Wells, N. 2017. Development of Spatially Referenced Data Layers for Use in the Identification and Delineation of Candidate Ecologically and Biologically Significant Areas in the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/036. v + 38 p Templeman, N.D. 2007. Placentia Bay-Grand Banks Large Ocean Management Area Ecologically and Biologically Significant Areas. Can. Sci. Advis. Sec. Res. Doc. 2007/052: iii + 15 p. Wells, N.J., Stenson, G.B., Pepin, P., and Koen-Alonso, M. 2017. Identification and Descriptions of Ecologically and Biologically Significant Areas in the Newfoundland and Labrador Shelves Bioregion. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/013. v + 87 p. Wells, N., K. Tucker, K. Allard, M. Warren, S. Olson, L. Gullage, C. Pretty, V. Sutton-Pande and K. Clarke. 2019. Re-evaluation of the Placentia Bay-Grand Banks Area of the Newfoundland and Labrador Shelves Bioregion to Identify and Describe Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Res. Doc. 2019/049. viii + 138 p.

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    The Urban Atlas provides pan-European comparable land use and land cover data for Functional Urban Areas (FUA). The Street Tree Layer (STL) is a separate layer from the Urban Atlas 2012 LU/LC layer produced within the level 1 urban mask for each FUA. It includes contiguous rows or a patches of trees covering 500 m² or more and with a minimum width of 10 meter over "Artificial surfaces" (nomenclature class 1) inside FUA (i.e. rows of trees along the road network outside urban areas or forest adjacent to urban areas should not be included). Urban Atlas is a joint initiative of the European Commission Directorate-General for Regional and Urban Policy and the Directorate-General for Enterprise and Industry in the frame of the EU Copernicus programme, with the support of the European Space Agency and the European Environment Agency.