Parks Canada’s National Program for Ecological Corridors was initiated to strengthen the network of protected areas across Canada through the creation of ecological corridors. To achieve this goal, Parks Canada sought out to develop tools for a common approach on the scientific and governance aspects of corridor creation and management. The National Priority Areas for Ecological Corridors (NPAECs) were developed using a scientific framework for national-scale prioritization of where ecological corridors are most urgently needed. Improving or maintaining ecological connectivity in these areas will greatly benefit biodiversity conservation and climate change adaptation. The NPAECs were identified based on a methodology that is multivariate, data driven, national in scale, and spatially explicit at a coarse resolution. The Criteria for Ecological Corridors in Canada provide a common approach to ensure ecological corridors are managed and stewarded to maintain or restore effective ecological connectivity, while upholding Indigenous stewardship values. They are derived from the internationally recognized International Union for Conservation of Nature’s Guidelines on Connectivity and adapted to the Canadian context. The NPAECs geographic data layer, the list of datasets used to identify them, the Criteria and their accompanying guidance can be found below. More details and context about both program elements are available on the Program’s webpage (https://parks.canada.ca/nature/science/conservation/corridors-ecologiques-ecological-corridors).

Geometric and conventional representation of the hydrographic network. The 3D hydrographic layer is represented by several natural or physical elements associated with the presence of water. These elements form part of the layers in the digital cartographic compilation.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The Ontario Raw Point Cloud (Imagery-Derived) is elevation point cloud data created from aerial photography from the Geospatial Ontario (GEO) imagery program. It was created using a pixel-autocorrelation process based on aerial photography collected by the imagery contractor for the GEO imagery program. The dataset consists of overlapping tiles in LAZ format and is 6.29 terabytes in size. Tiles are overlapping because the pixel-autocorrelation process extracts elevation values from overlapping stereo photo strips. No classification has been applied to the point cloud, however they are encoded with colour (RGB) values from the source photography. This data is for geospatial tech specialists, and is used by government, municipalities, conservation authorities and the private sector for land use planning and environmental analysis. __Related data__ For a product in non-overlapping tiles with a ground classification applied, see the [Ontario Classified Point Cloud (Imagery-Derived)](https://geohub.lio.gov.on.ca/datasets/febf17330adb4100a22738e1684b5feb). Raster derivatives have been created from the point clouds for some imagery projects. These products may meet your needs and are available for direct download. For a representation of bare earth, see [Ontario Digital Elevation Model (Imagery-Derived)](https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-elevation-model-imagery-derived/about). For a model representing all surface features, see the [Ontario Digital Surface Model (Imagery-Derived)](https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-surface-model-imagery-derived/about).

Krill is a generic name for crustaceans of the order Euphausiids, most of which are known to be Thysanoessa raschii and Meganyctiphanes norvegica in eastern Canada. Krill is an important food resource for many marine mammals, in particular the blue whale. The maps show the points of high krill concentration per month from April to November. Each point gives the number of years of high aggregation probability (6 to 10 years). The data were produced from a mathematical model developed in Plourde et al. 2016. The model has allowed to calculate the probability of meeting a strong aggregation of krill over a period of 10 years. High krill aggregations are defined as the 95th percentile of predicted biomass in 10 x 10 km cells covering the Estuary and Gulf of St. Lawrence. Additional Information Plourde, S., Lehoux, C., McQuinn, I.H., and Lesage, V. (2016). Describing krill distribution in the western North Atlantic using statistical habitat models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/nnn. vi + xx p. Plourde, S., McQuinn, I.H., Lesage, V., Lehoux, C., Joly, P., Bourassa, M-N. in prep. Spatial distribution of krill in eastern Canadian waters: a climatological approach based on historical plankton net and acoustic data. The data are incomplete upstream of Pointe-des-Monts because of the lack of water height anomalies in the area (variable being used to predict aggregations of krill). A less number of years with a high aggregation of krill is thus represented but that should not be interpreted as a less favorable zone compared to areas East of Pointe-des-Monts.

The Brier Island/Digby Neck area has been identified as an Ecologically and Biologically Significant Area (EBSA) by Fisheries and Oceans Canada and is one of four marine areas within the Bay of Fundy recognised by Parks Canada as of national significance for marine conservation planning. The area is representative of important outer Bay of Fundy features with significant marine mammal, bird, and benthic diversity including potentially important aggregations of sensitive benthic species such as horse mussel and sponge. Much of the information used for this recognition is now over 40 years old and should be re-validated using standardised georeferenced survey methods. As a first phase, a diver-based survey of the sublittoral habitats and associated species was conducted in August and September of 2017 for the Brier Island area. This report summarises the major sublittoral habitat types, species assemblages, and oceanographic conditions observed at 20 locations including Northwest and Southwest Ledges, Gull Rock, Peter’s Island, and Grand Passage. A total of 962 records were made of 178 taxa, consisting of 43 algae and 135 animals. Comparison with historical records largely confirmed the continued presence of unique habitats and species assemblages for which this area was initially recognised as an EBSA. Differences in species richness observed for cryptic and less known taxonomic groups such as sponges and bryozoans were attributable to changes in survey methods and knowledge. Based on these findings, additional surveys of inshore and offshore Brier Island using more quantitative methods developed for other Bay of Fundy EBSAs would further support regional MPA network planning and provide relative scales of species diversity and habitat coverage for this area.

Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Wagmatcook 2007 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Wagmatcook 2007. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

The National Ecological Framework for Canada's "Landform by Ecoregion” series contains tables that provide regional landform information for components within the ecoregion framework polygon. It provides landform codes and their English and French-language descriptions as well as information about the percentage of the polygon that the component occupies. Regional landforms generally describe a region and include the various shapes of the land surface resulting from a variety of actions such as deposition or sedimentation (eskers, lacustrine basins), erosion (gullies, canyons), and earth crust movements (mountains). The regional landform classes are: plateau or tableland, hill and mountain, organic wetland, plain, scarp or valley.

This is a legacy product that is no longer supported. It may not meet current government standards. Canada3D is a digital elevation model (DEM) produced by the Canadian Forestry Service, Ontario region. The DEM consists of an ordered array of ground elevations providing coverage of the Canadian landmass. It has been derived from the cells of the Canadian Digital Elevation Data (CDED) at the 1:250 000 scale. Canada3D is available in two levels of detail: grids regularly spaced at 30 or 300 arc seconds. Canada3D 30 and 300 are recorded separately in ASCII format. The elevation values are expressed in metres with respect to mean sea level (MSL), in accordance with the North American Datum of 1983 (NAD83).

The “Biomass Agriculture Inventory 1-in-10 Probability” dataset is a table that contains the estimated 1-in-10 year low for agricultural residue yield and crop production for each Biomass Report Framework. It provides the tenth percentile values for the years 1985-2016. The table includes straw or stover information for barley, wheat, flax, oats and corn, and crop information for barley, wheat, flax, oats, corn, canola and soybean. This dataset also includes information about the type of tillage used in the area and demand for straw for cattle bedding and feed. These values are derived from Statistics Canada data. Additionally, the dataset includes the amount of agricultural residue calculated as necessary to remain on the field to prevent soil degradation. Soil degradation is determined by the type of tillage in use as well as the landscape of the area.

The “Biomass Inventory Cartographic Layer” dataset provides the information that is used with the Biomass Report Framework to generate a visual representation of the availability of agricultural and forestry biomass and municipal solid waste in Canada. In addition to yield and production information for biomass produced by the agricultural and forestry industries, this dataset also provides information about the demand for agricultural residues for cattle feed and bedding, tillage systems currently in use on agricultural lands, and land suitability for hybrid poplar and willow plantations that are grown specifically to produce biomass. Agricultural information includes the median annual residue yield and available residue amounts. Residue yields were calculated using crop-to-residue ratios. The available residue information includes the amount that is available after adjusting for the estimated demand of straw used for cattle feed and bedding. Forestry estimates include average residue production, based on forestry activities including permitted amounts of harvesting, mills in operation and mill production. Municipal Solid Waste information includes organic waste (food and yard), paper waste and total residential municipal solid waste (which includes organic and paper waste, among others).