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    The land division system used for describing the extent of oil and gas interests located in the Northwest Territories, Nunavut or in Canada's offshore area is defined in the Canada Oil and Gas Land Regulations. This land division system consists of a grid system divided into Grid Areas, Sections, and Units – all referenced to the North American Datum of 1927 (NAD27). This data provides the geo-spatial representation of the NAD27 Oil and Gas Grid Areas referenced to NAD83 Datum. The creation of the Oil and Gas Grid Areas geo-spatial file covers areas that are situated in the Northwest Territories, Nunavut or Sable Island as well as submarine areas, not within a province, in the internal waters of Canada, the territorial sea of Canada or the continental shelf of Canada beyond 200 nm zone. The NAD83 grid area boundaries are defined by geodesics joining the four grid area corners. For sections and units, the eastern and western grid area geodesic boundaries are partitioned into 40 equal segments. The northern and southern grid area geodesic boundaries are partitioned into 40, 32 or 24 equal segments, depending on latitude. All internal corners at the section and unit level are defined by the intersections of north-south and east-west geodesics joining corresponding partition points along the northern and southern, and eastern and western, grid area geodesic boundaries.

  • 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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    Quebec's tourist routes and circuits each represent a path to follow along a picturesque path, focused on a distinctive theme and which connects a number of evocative tourist sites open to visitors. They are clearly marked with blue signs.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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    This collection is a legacy product that is no longer supported. It may not meet current Government standards. The National Topographic Data Base (NTDB) comprises digital vector data sets that cover the entire Canadian landmass. The NTDB includes features such as watercourses, urban areas, railways, roads, vegetation, and relief. The organizational unit for the NTDB is the National Topographic System (NTS), based on the North American Datum of 1983 (NAD83). Each file (data set) consists of one NTS unit at either the 1:50,000 or 1:250,000 scale. Related Products: [NTDB Correction Matrices, 2003-2009](https://ouvert.canada.ca/data/en/dataset/b6d0c19c-27e3-4392-b21f-49b1eec95653)

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    This dataset is a contribution to the development of a kelp distribution vector dataset. Bull kelp (Nereocystis leutkeana) and giant kelp (Macrocystis pyrifera) are important canopy-forming kelp species found in marine nearshore habitats on the West coast of Canada. Often referred to as a foundation species, beds of kelp form structural underwater forests that offer habitat for fishes and invertebrates. Despite its far-ranging importance, kelp has experienced a decline in the west coast of North America. The losses have been in response to direct harvest, increase in herbivores through the removal of predators by fisheries or diseases, increase in water turbidity from shoreline development as well as sea temperature change, ocean acidification, and increased storm activates. Understanding these impacts and the level of resilience of different kelp populations requires spatiotemporal baselines of kelp distribution. The area covered by this dataset includes the BC coast and extends to portions of the Washington and Alaska coasts. This dataset was created using 137 British Admiralty (BA) charts, including insets, with scales ranging from 1:6,080 to 1:500,000, created between 1858 and 1956. All surveys were based on triangulation, in which a sextant or theodolite was used to determine latitude and angles, while a chronometer was used to help determine longitude. First, each BA chart was scanned by the Canadian Hydrographic Service (CHS) using the CHS Colortrac large format scanner, and saved as a Tagged Image Format at 200 DPI, which was deemed sufficient resolution to properly visualize all the features of interest. Subsequently, the scanned charts were imported into ESRI ArcMap and georeferenced directly to WGS84 using CHS georeferencing standards and principles (charts.gc.ca). In order to minimize error, a hierarchy of control points was used, ranging from high survey order control points to comparing conspicuous stable rock features apparent in satellite imagery. The georeferencing result was further validated against satellite imagery, CHS charts and fieldsheets, the CHS-Pacific High Water Line (charts.gc.ca), and adjacent and overlapping BA charts. Finally, the kelp features were digitized, and corresponding chart information (scale, chart number, title, survey start year, survey end year, and comments) was added as attributes to each feature. Given the observed differences in kelp feature representation at different scales, when digitizing kelp features, polygons were used to represent the discrete observations, and as such, they represent presence of kelp and not kelp area. Polygons were created by tracing around the kelp feature, aiming to keep the outline close to the stipe and blades. The accuracy of the location of the digitized kelp features was defined using a reliability criterion, which considers the location of the digitized kelp feature (polygon) in relation to the local depth in which the feature occurs. For this, we defined a depth threshold of 40 m to represent a low likelihood of kelp habitat in areas deeper than the threshold. An accuracy assessment of the digitized kelp features concluded that 99% of the kelp features occurred in expected areas within a depth of less than 40 m, and only about 1% of the features occurred completely outside of this depth.

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    AIS NL Biofouling Species Fisheries and Oceans Canada's (DFO) National Marine Biofouling Monitoring Program conducts annual field surveys to monitor the introduction, establishment, spread, species richness, and relative abundance of native and some non-native species in Newfoundland and Labrador (NL) Region since 2006. Standardized monitoring protocols employed by DFO's NL, Maritimes, Gulf, and Quebec regions include biofouling collector plates deployed from May to October at georeferenced intertidal and shallow subtidal sites, including public docks, and public and private marinas and nautical clubs. Initially, (2006-2017), the collectors consisted of three 10 cm by 10 cm PVC plates deployed in a vertical array and spaced approximately 40 cm apart, with the shallowest plate suspended at least 1 m below the surface to sample subtidal and shallow intertidal species (McKenzie et al 2016a). Three replicate arrays were deployed at least 5 m apart per site. Since 2018, collector networks have been modified to improve statistical replication, including up to 10 individual collectors deployed per site at 1 m depth and at least 5 m apart (as above) from May to October. Since 2006, seven invasive biofouling organisms have been detected in Newfoundland and Labrador harbours, marinas and coastal areas. Should be cited as follows: DFO Newfoundland and Labrador Region Aquatic Invasive Species Marine Biofouling Monitoring Program. Published March 2024. Coastal and Freshwater Ecology, Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John’s, Newfoundland and Labrador. Reference: Tunicates Golden star tunicate (Botryllus schlosseri) 2006 The Golden star tunicate was the first invasive tunicate detected in NL waters. It was reported in Argentia by the US Navy around 1945. It was found in 2006 on wharf structures in Argentia, Placentia Bay during the first AIS survey (Callahan et al 2010). This colonial tunicate is recognized by it star shaped grouping of individuals within the colony. It is currently found in Placentia Bay, Fortune Bay, St. Mary’s Bay, Conception Bay and the west coast of NL. The data provided here indicates the detections of this AIS in coastal NL. From 2018-2022, the Coastal Environmental Baseline Program provided additional support to enhance sampling efforts in Placentia Bay.

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    Many cetacean species were depleted in Canadian Pacific waters by commercial whaling, which ended in 1967. Although some populations have since shown evidence of recovery, there is limited information about the current abundance and geographic distribution of many species, particularly in difficult-to-survey offshore regions. This lack of baseline data hampers conservation status assessments, including estimating population-level impacts of anthropogenic activities. From July to early September 2018, we conducted ship-based surveys of cetaceans throughout the coastal and offshore waters of British Columbia. Density surface modelling (DSM) was used to produce spatially-explicit abundance estimates and distribution maps for four commonly-encountered cetacean species: the humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), Dall’s porpoise (Phocoenoides dalli) and harbour porpoise (Phocoena phocoena). We estimated abundances of 7,030 (95% CI = 5,733-8,620) humpback whales, 2,893 (95% CI = 2,171-3,855) fin whales, 23,692 (95% CI = 19,121-29,356) Dall’s porpoises and 5,207 (95% CI = 2,769-9,793) harbour porpoises throughout Canadian Pacific waters. Our results complement design-based abundance estimates calculated from the same survey data, and can be compared with past habitat modelling studies and historical whaling catch data to estimate the extent of recovery of previously harvested populations. The return of these predators to habitats from which they were previously extirpated will have important ecosystem-level implications. The DSM results can contribute to calculations of Potential Biological Removal estimates to inform fisheries bycatch, as well as providing spatial data that can be used to assess the risk of entanglements, ship strikes, acoustic disturbance, and other anthropogenic threats. This dataset contains model-predicted densities of four commonly-encountered cetacean species (humpback whale, fin whale, Dall's porpoise and harbour porpoise) that were estimated using ship-based, visual survey data collected during the Pacific Region International Survey of Marine Megafauna (PRISMM) in July-August of 2018. Abundance of each species (where relevant) is provided for three gridded strata (25 km2 cell size) in the Pacific Region: one for the offshore, extending to Canada’s exclusive economic zone (EEZ), and two for coastal areas (the North Coast and the Salish Sea).

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    Riparian zones represent transitional areas occurring between land and freshwater ecosystems, characterised by distinctive hydrology, soil and biotic conditions and strongly influenced by the stream water. They provide a wide range of riparian functions (e.g. chemical filtration, flood control, bank stabilization, aquatic life and riparian wildlife support, etc.) and ecosystem services. The Riparian Zones products support the objectives of several European legal acts and policy initiatives, such as the EU Biodiversity Strategy to 2020, the Habitats and Birds Directives and the Water Framework Directive. This metadata refers to the Riparian Zones 2012 Land Cover/Land Use (LC/LU), which LC/LU classification is tailored to the needs of biodiversity monitoring in a variable buffer zone of selected rivers (Strahler levels 2-9 derived from EU-Hydro) for the reference year 2012. LC/LU is extracted from Very High Resolution (VHR) satellite data and other available data in a buffer zone of selected rivers for supporting biodiversity monitoring and mapping and assessment of ecosystems and their services. The class definitions follow the pre-defined nomenclature on the basis of Mapping and Assessment of Ecosystems and their Services (MAES) typology of ecosystems (Level 1 to Level 4) and CORINE Land Cover. The classification provides 55 distinct thematic classes with a Minimum Mapping Unit (MMU) of 0.5 ha and a Minimum Mapping Width (MMW) of 10 m. The nomenclature has been revised in 2020 with the aim to harmonize the products of the local components (mainly Riparian Zones and NATURA 2000 products) while maintaining user requirements for both products. A revised version of the Riparian Zones 2012 has been subsequently released in December 2021, together with the reference year 2018. The production of the Riparian Zones products was coordinated by the European Environment Agency in the frame of the EU Copernicus programme.

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    Pepin et al. (2014) stated that three nested spatial scales were identified as relevant for the development of ecosystem summaries and management plans: Bioregion, Ecosystem Production Unit (EPU), and Ecoregion. A bioregion is composed by one or more EPUs, while an EPU consists of a combination of ecoregions, which represent elements with different physical and biological characteristics based on the analytical criteria applied. Pepin et al. (2014) reported on the consolidation of data and analyses of ecoregion structure for the continental shelf areas from the Labrador Sea to the mid-Atlantic Bight and provided recommendations on the definition of EPUs in the NAFO Convention Area. The results of two K-means clustering analyses (one geographically constrained and one un-constrained) and expert knowledge (including and considering location of ecoregions, knowledge of the distribution of major marine resources and fish stocks, and geographic proximity for delineation/definition of potential management units) served as guides for evaluation by NAFO’s (North Atlantic Fisheries Organization) working group on ecosystem science and assessments (WG-ESA). The final consensus from the discussions identified eight (8) major EPUs that can serve as practical candidate management units (from the 50 m isobaths, where research vessel data were available, seaward to the 1500 m isobaths) that consist of the Labrador Shelf (NAFO subareas 2GH), the northeast Newfoundland Shelf (subareas 2J3K), the Grand Banks (subareas 3LNO), Flemish Cap (subarea 3M), the Scotian Shelf (subareas 4VnsWX), Georges Bank (parts of subareas 5Ze and 5Zw), the Gulf of Maine (subarea 5Y and part of 5Ze) and the mid-Atlantic Bight (part of subarea 5Zw and subareas 6ABC). Southern Newfoundland (subarea 3Ps) was not included in the original analysis because fall survey data were unavailable. However, it was later added as an EPU after additional analysis of the fish community structure and trends using survey data from the spring, which indicated that this area is heavily influenced by the surrounding EPUs (NAFO 2015). The proposed candidate management units correspond to the EPUs that define major areas within the bioregions which contain a reasonably well defined food web/production system. The working group noted that the consensus solution represents a compromise that aims to define management units based on the boundaries of existing NAFO subareas that are appropriate for estimation of ecosystem and fishery production. References: NAFO. 2015. Report of the 8th Meeting of the NAFO Scientific Council (SC) Working Group on Ecosystem Science and Assessment (WGESA). 17-26 November 2015, Dartmouth, Canada. NAFO SCS Doc. 15/19. Pepin, P., Higdon, J., Koen-Alonso, M., Fogarty, M., and N. Ollerhead. 2014. Application of ecoregion analysis to the identification of Ecosystem Production Units (EPUs) in the NAFO Convention Area. NAFO SCR Doc. 14/069.

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    La Financière Agricole's collective corn and grain crop insurance offers protection against losses in yield and quality assessed for the entire area where the insured units are located.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**