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.

This 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 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.

Description: Data on recreational boating are needed for marine spatial planning initiatives in British Columbia (BC). Vessel traffic data are typically obtained by analyzing automatic identification system (AIS) vessel tracking data, but recreational vessels are often omitted or underrepresented in AIS data because they are not required to carry AIS tracking devices. Transport Canada’s National Aerial Surveillance Program (NASP) conducted aerial surveys to collect information on recreational vessels along several sections of the BC coast between 2018 and 2022. Recreational vessel sightings were modeled against predictor variables (e.g., distance to shore, water depth, distance to, and density of marinas) to predict the number of recreational vessels along coastal waters of BC. The files included here are: --A Geodatabase (‘Recreational_Boating_Data_Model’), which includes: (1) recreational vessel sightings data collected by NASP in BC and used in the recreational vessel traffic model (‘Recreational_Vessels_PointData_BC’); (2) aerial survey effort (or number of aerial surveys) raster dataset (‘surveyeffort’); and (3) a vector grid dataset (2.5 km resolution) containing the predicted number of recreational vessels per cell and predictor variables (‘Recreational_Boating_Model_Results_BC). --Scripts folder which includes R Markdown file with R code to run the modelling analysis (‘Recreational_Boating_Model_R_Script’) and data used to run the code. Methods: Data on recreational vessels were collected by NASP during planned aerial surveys along pre-determined routes along the BC coast from 2018 to 2022. Data on non-AIS recreational vessels were collected using video cameras onboard the aircraft, and data on AIS recreational vessels using an AIS receiver also onboard the aircraft. Recreational boating predictors explored were: water depth, distance to shore, distance to marinas, density of marinas, latitude, and longitude. Recreational vessel traffic models were fitted using Generalized Linear Models (GLM) R packages and libraries used here include: AED (Roman Lustrik, 2021) and MASS (Venables, W. N., Ripley, 2002), pscl package (Zeileis, Kleiber, and Jackman, 2008) for zeroinfl() and hurdle() function. Final model was selected based on the Akaike’s information criterion (AIC) and the Bayes’ information criterion (BIC). An R Markdown file with code use to run this analysis is included in the data package in a folder called Script. Spatial Predictive Model: The selected model, ZINB, consist of two parts: one with a binomial process that predicts the probability of encountering a recreational vessel, and a second part that predicts the number of recreational vessels via a count model. The closer to shore and to marinas, and the higher the density of marinas, the higher the predicted number of recreational vessels. The probability of encountering recreational vessels is driven by water depth and distance to shore. For more information on methodology, consult metadata pdf available with the Open Data record. References: Serra-Sogas, N. et al. 2021. Using aerial surveys to fill gaps in AIS vessel traffic data to inform threat assessments, vessel management and planning. Marine Policy 133: 104765. https://doi.org/10.1016/j.marpol.2021.104765 Data Sources: Recreational vessel sightings and survey effort: Data collected by NASP and analyzed by Norma Serra to extract vessel information and survey effort (more information on how this data was analyzed see SerraSogas et al, 2021). Bathymetry data for the whole BC coast and only waters within the Canadian EEZ was provided by DFO – Science (Selina Agbayani). The data layer was presented as a raster file of 100 meters resolution. Coastline dataset used to estimate distance to shore and to clip grid was provided by DFO – Science (Selina Agbayani), created by David Williams and Yuriko Hashimoto (DFO – Oceans). Marinas dataset was provided by DFO – Science (Selina Agbayani), created by Josie Iacarella (DFO – Science). This dataset includes large and medium size marinas and fishing lodges. The data can be downloaded from here: Floating Structures in the Pacific Northwest - Open Government Portal (https://open.canada.ca/data/en/dataset/049770ef-6cb3-44ee-afc8-5d77d6200a12) Uncertainties: Model results are based on recreational vessels sighted by NASP and their related predictor variables and not always might reflect real-world vessel distributions. Any biases caused by the opportunistic nature of the NASP surveys were minimized by using survey effort as an offset variable.

The water level data comes from the groundwater monitoring network of Prince Edward Island (Canadian province). Each well in the observation network is equipped with a hydrostatic pressure transducer and a temperature sensor connected to a data logger. A second pressure transducer located above the water surface allows for adjusting the water level according to atmospheric pressure variations. The time series refers to the level below which the soil is saturated with water at the site and at the time indicated. The water level is expressed in meters above sea level (MASL). The dataset consists of a general description of the observation site including; the identifier, the name, the location, the elevation and a series of numerical values designating the water levels at a defined date and time of measurement.

The Atlantic 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 estuarine 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 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.

This dataset provides marine bacteriological water quality data for bivalve shellfish harvest areas in Canada (British Columbia, New Brunswick, Newfoundland and Labrador, Nova Scotia, Prince Edward Island and Quebec). Shellfish harvest area water temperature and salinity data are also provided as adjuncts to the interpretation of fecal coliform concentration data. The latter is the indicator of fecal contamination monitored by Environment and Climate Change Canada (ECCC) within the framework of the Canadian Shellfish Sanitation Program (CSSP). The geospatial positions of the sampling sites are also provided. These data are collected by ECCC for the purpose of making recommendations on the classification of shellfish harvest area waters. ECCC recommendations are reviewed and adopted by Regional Interdepartmental Shellfish Committees prior to regulatory implementation by Fisheries and Oceans Canada (DFO).

This dataset contains results from an eelgrass classification in Shippagan Harbour, New Brunswick. Derived from a Quickbird satellite image collected on July 27, 2007 at as close to low-tide as possible. Classification was objected-oriented using Definiens software. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence.

GIS compilation of data used to perform the stacked cumulative chance of success (resource potential map) in Open file 8556. Natural Resources Canada (NRCan) has been tasked, under the Marine Conservation Targets (MCT) initiative announced in Budget 2016, with evaluating the petroleum resource potential for areas identified for possible protection as part of the Government of Canada's commitment to conserve 10% of its marine areas by 2020. As part of this initiative, NRCan's Geological Survey of Canada (GSC) conducted a broad regional study of the petroleum potential over the majority of the Magdalen Basin, which is the principal geological basin in the southern Gulf of St. Lawrence. The GSC resource assessment is visually represented by a qualitative petroleum potential map. Disclaimer: A simplified colored version of the map is displayed on the Web Mapping Service (WMS). The correct version is available for download through the Federal Geospatial Platform (FGP) and GEOSCAN.

This dataset provides geospatial polygon boundaries for marine bivalve shellfish harvest area classification in Prince Edward Island, Canada. These data represent the five classification categories of marine bivalve shellfish harvest areas (Approved; Conditionally Approved; Restricted; Conditionally Restricted; and Prohibited) under the Canadian Shellfish Sanitation Program (CSSP). Data are collected by Environment and Climate Change Canada (ECCC) for the purpose of making applicable classification recommendations on the basis of sanitary and water quality survey results. ECCC recommendations are reviewed and adopted by Regional Interdepartmental Shellfish Committees prior to regulatory implementation by Fisheries and Oceans Canada (DFO). These geographic data are for illustrative purposes only; they show shellfish harvest area classifications when in Open Status. The classification may be superseded at any time by regulatory orders issued by DFO, which place areas in Closed Status, due to conditions such as sewage overflows or elevated biotoxin levels. For further information about the current status and boundary coordinates for areas under Prohibition Order, please contact your local DFO office. This dataset is 'Deprecated'. Please use updated source here. https://open.canada.ca/data/en/dataset/7aef69b5-3aaf-4d50-bb86-083031e6dc47

A revised qualitative assessment of the hydrocarbon resource potential is presented for the Hudson Bay sedimentary basin that underlies Hudson Bay and adjacent onshore areas of Ontario, Manitoba, and Nunavut. The Hudson Basin is a large intracratonic sedimentary basin thatpreserves dominantly Ordovician to Devonian aged limestone and evaporite strata. Maximum preserved sediment thickness is about 2.5 km. Source rock is the petroleum system element that has the lowest chance of success; the potential source rock is thin, may be discontinuous, and the thin sedimentarycover may not have been sufficient to achieve the temperatures required to generate and expel oil from a source rock over much of the basin. The highest potential is in the center of the basin, where the hydrocarbon potential is considered amp;lt;'Mediumamp;gt;'. Hydrocarbon potential decreasestowards the edges of the basin due to fewer plays being present, and thinner strata reduce the chance of oil generation and expulsion. Quantitative hydrocarbon assessment considers seven plays. Input parameters for field size and field density (per unit area) are based on analog Michigan, Williston,and Illinois intracratonic sedimentary basins that are about the same age and that had similar depositional settings to Hudson Basin. Basin-wide play and local prospect chances of success were assigned based on local geological conditions in Hudson Bay. Each of the seven plays were analyzed in Roseand Associates PlayRA software, which performs a Monte Carlo simulation using the local chance of success matrix and field size and prospect numbers estimated from analog basins. Hudson sedimentary basin has a mean estimate of 67.3 million recoverable barrels of oil equivalent and a 10% chance ofhaving 202.2 or more million barrels of recoverable oil equivalent. The mean chance for the largest expected pool is about 15 million recoverable barrels of oil equivalent (MMBOE), and there is only a 10% chance of there being a field larger than 23.2 MMBOE recoverable. The small expected fieldsizes are based on the large analog data set from Michigan, Williston and Illinois basins, and are due to the geological conditions that create the traps. The small size of the largest expected field, the low chance of exploration success, and the small overall resource make it unlikely that there are any economically recoverable hydrocarbons in the Hudson Basin in the foreseeable future. The Southampton Island area of interest includes 93 087 km2 of nearshore waters around Southampton Island and Chesterfield Inlet in the Kivalliq Region of Nunavut. Of the total resource estimated for Hudson Bay, 14 million barrels are apportioned to the Southampton Island Area of Interest.