This model is derived from geological, geophysical and other forms of geodata. Feature extraction used deep learning. Predictive modelling made use of the deep ensemble method. Displayed is a Pan-Canadian probability map of mineral potential of graphite. This map was generated using known graphite deposits and occurrences and their associated features. Higher probability values highlight areas with an increased probability of graphite mineral systems.

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).

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.

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.

Í gögnunum er að finna upplýsingar um staðsetningu og umfang verndarsvæða í byggð sem ráðherra hefur staðfest í samræmi við lög nr. 87/2015 um verndarsvæði í byggð. Markmið laganna er að stuðla að varpveislu og vernd byggðar sem hefur sögulegt gildi.

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.

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.

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.

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.

Gögin upplýsingar um strok og tjón sem hefur átt sér stað sjókvíeldi. Hægt er að sjá hvar strokið átti sér stað, hvenær og hverskonar fiskur strauk. Einnig er hægt að sjá hvort hjón var á búnaði eða gat á kví. Fyrir frekari upplýsingar er bent á að hafa samband við matvælastofnun.