A Priority Place is an area of high biodiversity value that is seen as a distinct place with a common ecological theme by the people who live and work there. As part of the Pan-Canadian approach to transforming species at risk conservation in Canada, a total of 11 Priority Places were affirmed by federal, provincial, and territorial governments in December 2018. One additional priority place was affirmed in 2024. The places selected have significant biodiversity, concentrations of species at risk, and opportunities to advance conservation efforts. In each Priority Place, the federal and provincial or territorial governments are working with Indigenous Peoples, partners, and stakeholders to develop conservation implementation plans. This dataset captures a small sample of the projects that are underway in these Priority Places. Over time, it will be expanded to include more projects. Some projects span various areas of a Priority Place but are reflected in this dataset as a single center point. This dataset is not to be used for legal purposes.

This dataset contains results from an eelgrass classification for Tracadie Bay, New Brunswick. True colour aerial photography at 57 centimetre resolution was collected on September 2, 2009 by Nortek Resources of Thorburn, Nova Scotia (https://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 101 sites. Approximately two-thirds of these sites were used to assist in image classification, while the remainder was used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 79.3% of the time in a fuzzy accuracy assessment technique, whereby those classes that were ‘off’ by one class, e.g. Good Quality eelgrass classed as Medium Quality, were given half credit towards the overall accuracy. Of 29 sites that were within the classification area, 18 were correct, 10 were "one-off", and 1 was incorrect [(18 + (10/2))/ 29 = 0.793].

The Water Survey of Canada (WSC) is the national authority responsible for the collection, interpretation and dissemination of standardized water resource data and information in Canada. In partnership with the provinces, territories and other agencies, WSC operates over 2800 active hydrometric gauges across the country. WSC maintains and provides real-time and historic hydrometric data for some 8000 active and discontinued stations. This dataset consists of a set of polygons that represent the drainage areas of both active and discontinued discharge stations. Users are encouraged to report any errors using the “Contact Us” webpage at: https://weather.gc.ca/mainmenu/contact_us_e.html?site=water

The Department of National Defence has designated Firing Practice and Exercise Areas off the coasts of Canada. Activities in these areas may include bombing practice from aircraft, air-to-air, air-to-sea or ground firing, and anti-aircraft firing, etc. In Atlantic Canada, the Nova Scotia Area includes sea area employments for sub-surface operations and firing exercises (FIREX). The Gulf of St. Lawrence Area, excluding the French territorial waters of Saint-Pierre et Miquelon, includes sea area employments for sub-surface operations and underwater demolition training. For full details, see the Notices to Mariners, Section F, National Defence Military Notices, available online: https://www.notmar.gc.ca/publications/annual-annuel/section-f/f35-en.pdf. Legal Constraints: Users should be aware that the polygons depicting firing practice and exercise areas are intended for illustration only and should not be used for navigational or legal purposes.

Points, polylines and polygons where species and features have been found, harvested or detailed. Community Based Coastal Resource Inventory (CCRI) – Fisheries and Oceans Canada in conjunction with several Federal and Provincial agencies created, implemented, and managed a program which set out to develop a coastal resource inventory based on the traditional knowledge of local residents. Through partnerships with the province of Newfoundland and Labrador’s Regional Economic Development (RED) Boards and other community based groups the project assembled a database containing several decade’s worth of local knowledge. The value of the information collected came through individual interviews with people who had extensive knowledge of the immediate geography and resource, having lived, worked and harvested the regions over a lifetime. This project ran from 1996 to 2007.

Proxied dataset of inshore lobster commercial fishing for 2012 - 2021 in the Newfoundland and Labrador region. Only lobster harvested from the Newfoundland and Labrador region are included, based on species sought. Commercial data for the inshore lobster fishery does not require a set of coordinates be provided for catch records. With zero georeferenced inshore lobster records, the inshore lobster fishery leaves a major data gap in one of Newfoundland and Labradors largest fisheries. The Gulf region created a lobster proxy mapping tool, which associated each commercial lobster record with the most likely 10km2 hexagon grid cell based on a number of weighted variables. The tool was adopted by the Newfoundland and Labrador region and altered to work with its own variables which include human use, habitat, accessibility, area/location, home port distance, traditional ecological knowledge and depth. Each hexagon represents the summed total weight of all records associated with a particular hexagon. The best available commercial data used in this model is derived from landings data and may not include catches that have resulted in cash/wharf sales. As a result, there are some areas of Newfoundland and Labrador that may be under represented in this dataset where wharf sales may be high. Therefore, this dataset should be viewed as a general estimation on lobster harvesting patterns within Newfoundland and Labrador.

These datasets show the general spatial distribution of commercial fishing harvest and landed values by fishery on a 1km x 1km planning grid. They aggregate key statistics around fleet specific fishing activity and catch in British Columbia (BC) within the exclusive economic zone (EEZ). These gridded data describe the annual average landed weight (Rounded KGs), and landed catch values (CAD $2016) of the subject fishery over the period. The data represented were created from logbook records and matched to prices from fish slips submitted to DFO by participants of BC’s commercial fishing fleets. The dataset is comprised of an aggregate of all species over 10, 9, or 5 years of fishing seasons, depending on the fishery. To preserve potentially proprietary information, a privacy filtering Rule of Five has been applied to each planning unit (each 1km x 1km planning unit). If any planning units do not meet this minimum of 5 unique vessels/unique identifiers during the time span then they are flagged as being filtered and an average of all filtered planning units is applied. The accompanying GeoDB contains two data layers, “all_fisheries_filtered_gridded “, which includes all of the commercial fisheries data in 1km x 1km grids, and “DFO_marine_bioregions_NSB_subregions”, which includes polygon feature boundaries for the federal marine bioregions and Northern Shelf bioregion sub-regions. This dataset contains data for the following fisheries: - Bottom trawl (2012-2016) - Midwater trawl (2012-2016) - Shrimp by trawl (2007-2016) - Prawn trap (2007-2016) - Rockfish (2012-2016) - Sablefish (2007-2016) - Halibut (2007-2016) - Combo trips - halibut/sablefish (2007-2016) - Lingcod (2007-2016) - Green sea urchin (2006-2015) - Red sea urchin (2007-2015) - Sea cucumber (2008-2016) - Geoduck (2007-2015)

As part of the International Polar Year (IPY) 2007'08 and 2008'09 activities, and related objectives of the Commission for the Geological Map of the World (CGMW), nations of the circumpolar Arctic have co-operated to produce a new bedrock geology map and related digital map database at a scale of 1:5 000 000. The map, released in north polar stereographic projection using the World Geodetic System (WGS) 84 datum, includes complete geological and physiographic coverage of all onshore and offshore bedrock areas north of latitude 60° north.

The Quebec—Saint-Lawrence River dataset is part of Environment and Climate Change Canada’s Shoreline Classification and Pre-Spill database. Shoreline classification data has been developed for use by the Environmental Emergencies Program of Environment and Climate Change Canada for environmental protection purposes. Marine and freshwater shorelines are classified according to the character (substrate and form) of the upper intertidal (foreshore) or upper swash zone (Sergy, 2008). This is the area where oil from a spill usually becomes stranded and where the treatment or cleanup activities take place. The basic parameter that defines the shoreline type is the material that is present in the intertidal zone. The presence or absence of sediments is a key factor in determining whether oil is stranded on the surface of a substrate or can penetrate and/or be buried. This dataset contains thousands of linear shoreline segments ranging in length from 200 m and 2 km long. The entities represent the location of the segments and their geomorphological description. There exist further fields in the attribute table for this dataset. We are currently working on standardizing our shoreline segmentation datasets and the updated data will soon be uploaded to the catalog. Sergy, G. (2008). The Shoreline Classification Scheme for SCAT and Oil Spill Response in Canada. Proceedings of the 31stArctic and Marine Oil Spill Program Technical Seminar.Environment Canada, Ottawa, ON, Pp. 811-819.

As part of a scientific assessment of critical habitat for boreal woodland caribou (Environment Canada 2011, see full reference in accompanying documentation), Environment Canada's Landscape Science and Technology Division was tasked with providing detailed anthropogenic disturbance mapping, across known caribou ranges, as of 2015. This data comprises a 5-year update to the mapping of 2008-2010 disturbances, and allows researchers to better understand the attributes that have a known effect on caribou population persistence. The original disturbance mapping was based on 30-metre resolution Landsat-5 imagery from 2008 -2010. The mapping process used in 2010 was repeated using 2015 Landsat imagery to create a nationally consistent, reliable and repeatable geospatial dataset that followed a common methodology. The methods developed were focused on mapping disturbances at a specific point of time, and were not designed to identify the age of disturbances, which can be of particular interest for disturbances that can be considered non-permanent, for example cutblocks. The resultant datasets were used for a caribou resource selection function (habitat modeling) and to assess overall disturbance levels on each caribou ranges. Anthropogenic disturbances within 51 caribou ranges across Canada were mapped. The ranges were defined by individual provinces and territories across Canada. Disturbances were remapped across these ranges using 2015 Landsat-8 satellite imagery to provide the most up-to-date data possible. As with the 2010 mapping project, anthropogenic disturbance was defined as any human-caused disturbance to the natural landscape that could be visually identified from Landsat imagery with 30-metre multi-band imagery at a viewing scale of 1:50,000. A minimum mapping unit MMU of 2 ha (approximately 22 contiguous 30-metre pixels) was selected. Each disturbance feature type was represented in the database by a line or polygon depending on their geometric description. Polygonal disturbances included: cutblocks, mines, reservoirs, built-up areas, well sites, agriculture, oil and gas facilities, as well as unknown features. Linear disturbances included: roads, railways, powerlines, seismic exploration lines, pipelines, dams, air strips, as well as unknown features. For each type of anthropogenic disturbance, a clear description was established (see Appendix 7.2 of the science assessment) to maintain consistency in identifying the various disturbances in the imagery by the different interpreters. Features were only digitized if they were visible in the Landsat imagery at the prescribed viewing scale. A 2nd interpreter quality-control phase was carried out to ensure high quality, complete and consistent data collection. For this 2015 update an additional, separate higher-resolution database was created by repeating the process using 15-metre panchromatic imagery. For the 30-metre database only, the line and poly data were buffered by a 500-metre radius, representing their extended zone of impact upon boreal caribou herds. Additionally, forest fire polygons were merged into the anthropogenic footprint in order to create an overall disturbance footprint. These buffered datasets were used in the calculation of range disturbance levels and for integrated risk assessment analysis.