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)

The Urban Atlas provides pan-European comparable land use and land cover data for Functional Urban Areas (FUA). The Urban Atlas Change layers have become available from 2012 and only for all FUAs that have been covered in both 2006 and 2012 reference years. 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.

Herring Section shapefile - used for spatial analysis/presentation of data from Herring Stock Assessment Database.

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 Land Cover/Land Use (LC/LU) change for 2012-2018. The 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 change layer 2012-2018. 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 production of the Riparian Zones products was coordinated by the European Environment Agency in the frame of the EU Copernicus programme.

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

Eldissvæði er svæði sem úthlutað er rekstarleyfishafa. Rekstrarleyfishafi hefur þá heimild til að hafa eldisbúnað til að ala fisk innan þess svæðis skv. skilyrðum rekstrarleyfisins.

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.

The Canadian Breeding Bird Census (BBC) Database contains data for 928 breeding bird plot censuses representing all known censuses of breeding birds carried out in Canada during the period 1929–1993. The 928 records in the database represent 640 unique census plots located in all provinces and territories, except Prince Edward Island. The BBC, which was replaced by the current Breeding Bird Survey, is one of the longest-running surveys of bird populations in North America, and was designed to help determine abundance and distribution patterns of bird species. An important feature of the BBC Database is the habitat data associated with each census plot. The most prevalent vegetation species in different layers (canopy, shrub and ground cover) were recorded to reflect the assumption that birds respond principally to vegetative structure.

Data Sources: Banque informatisée des oiseaux de mer au Québec (BIOMQ: ECCC-CWS Quebec Region) Atlantic Colonial Waterbird Database (ACWD: ECCC-CWS Atlantic Region).. Both the BIOMQ and ACWD contain records of individual colony counts, by species, for known colonies located in Eastern Canada. Although some colonies are censused annually, most are visited much less frequently. Methods used to derive colony population estimates vary markedly among colonies and among species. For example, census methods devised for burrow-nesting alcids typically rely on ground survey techniques. As such, they tend to be restricted to relatively few colonies. In contrast, censuses of large gull or tern colonies, which are geographically widespread, more appropriately rely on a combination of broad-scale aerial surveys, and ground surveys at a subset of these colonies. In some instances, ground surveys of certain species are not available throughout the study area. In such cases, consideration of other sources, including aerial surveys, may be appropriate. For example,data stemming from a 2006 aerial survey of Common Eiders during nesting, conducted by ECCC-CWS in Labrador, though not yet incorporated in the ACWD, were used in this report. It is important to note that colony data for some species, such as herons, are not well represented in these ECCC-CWS databases at present. Analysis of ACWD and BIOMQ data (ECCC-CWS Quebec and Atlantic Regions): Data were merged as temporal coverage, survey methods and geospatial information were comparable. Only in cases where total counts of individuals were not explicitly presented was it necessary to calculate proxies of total counts of breeding individuals (e.g., by doubling numbers of breeding pairs or of active nests). Though these approaches may underestimate the true number of total individuals associated with a given site by failing to include some proportion of the non-breeding population (i.e., visiting adult non-breeders, sub-adults and failed breeders), tracking numbers of breeding individuals (or pairs) is considered to be the primary focus of these colony monitoring programs.In order to represent the potential number of individuals of a given species that realistically could be and may historically have been present at a given colony location (see section 1.1), the maximum total count obtained per species per site since 1960 was used in the analyses. In the case of certain species,especially coastal piscivores (Wires et al. 2001; Cotter et al. 2012), maxima reached in the 1970s or 1980s likely resulted from considerable anthropogenic sources of food, and these levels may never be seen again. The effect may have been more pronounced in certain geographic areas. Certain sites once used as colonies may no longer be suitable for breeding due to natural and/or human causes, but others similarly may become suitable and thus merit consideration in long-term habitat conservation planning. A colony importance index (CII) was derived by dividing the latter maximum total count by the potential total Eastern Canadian breeding population of that species (the sum of maximum total counts within a species, across all known colony sites in Eastern Canada). The CII approximates the proportion of the total potential Eastern Canadian breeding population (sum of maxima) reached at each colony location and allowed for an objective comparison among colonies both within and across species. In some less-frequently visited colonies, birds (cormorants, gulls, murres and terns, in particular) were not identified to species. Due to potential biases and issues pertaining to inclusion of these data, they were not considered when calculating species’ maximum counts by colony for the CII. The IBA approach whereby maximum colony counts are divided by the size of the corresponding actual estimated population for each species (see Table 3.1.2; approximate 1% continental threshold presented) was not used because in some instances individuals were not identified to species at some sites, or population estimates were unavailable.Use of both maxima and proportions of populations (or an index thereof) presents contrasting, but complementary, approaches to identifying important colonial congregations. By examining results derived from both approaches, attention can be directed at areas that not only host large numbers of individuals, but also important proportions of populations. This dual approach avoids attributing disproportionate attention to species that by their very nature occur in very large colonies (e.g., Leach’s Storm Petrel) or conversely to colonies that host important large proportions of less-abundant species (Roseate Tern, Caspian Tern, Black-Headed Gull, etc.), but in smaller overall numbers. Point Density Analysis (ArcGIS Spatial Analyst) with kernel estimation, and a 10-km search radius,was used to generate maps illustrating the density of colony measures (i.e., maximum count by species,CII by species), modelled as a continuous field (Gatrell et al. 1996). Actual colony locations were subsequently overlaid on the resulting cluster map. Sites not identified as important should not be assumed to be unimportant.

Akkeri og baujur og áætlaðar staðsetningar fyrir búnað í sjókvíaeldi.