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

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.

This collection is a legacy product that is no longer supported. It may not meet current government standards. The North American Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. The North American Atlas data are intended for geographic display and analysis at the national and continental level. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data.

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)

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 marks left in the seabed by the commercial anchoring process can be seen as linear features in high-resolution multibeam bathymetry data. These features have been digitized to polylines for individual marks and polygons for anchor scour zones for British Columbia's (BC) commercial anchorages. They are made available via the Federal Geospatial Platform (FGP) for use in a Geographical Information System (GIS). This feature dataset is complete for published BC commercial anchorages and the multibeam bathymetry data available in 2021. It does not represent features produced since the collection of each multibeam bathymetry survey nor any features infilled since. The data are intended to be used for scientific research to better understand the cumulative impacts to the seabed from commercial anchoring at a 1:5000 scale or greater.