The Maritimes Region is divided into seven Clam Harvesting Areas (CHA).CLAM HARVESTING AREA 1 is described as follows:The inland and tidal waters of the counties of Colchester, Cumberland and Hants that border and flow into the Bay of Fundy.CLAM HARVESTING AREA 2 is described as follows:The inland and tidal waters of the counties of Annapolis, Digby and Kings.CLAM HARVESTING AREA 3 is described as follows:The inland and tidal waters of Yarmouth County.Time restrictions for Clam Harvesting Area 3: No person shall fish for clams from sunset each Saturday until sunrise on the following Monday (closed Sundays) in the boundaries of Clam Harvesting Area 3.CLAM HARVESTING AREA 4 is described as follows:The inland and tidal waters of the counties of Shelburne, Queens and Lunenburg and that portion of Halifax County west of Pennant Point (as defined in the Territorial Sea Geographical Coordinates Order (C.R.C., c. 1550), Schedule I, Area 4).CLAM HARVESTING AREA 5 is described as follows:The inland and tidal waters of Guysborough County and that portion of Halifax County east of Pennant Point (as defined in the Territorial Sea Geographical Coordinates Order (C.R.C., c. 1550), Schedule I, Area 4).CLAM HARVESTING AREA 6 is described as follows:The inland and tidal waters of the counties of Richmond and Cape Breton, all of Victoria County except that portion between Cape North and Inverness County and that portion of Inverness County that borders on the Bras d'Or Lakes.NEW BRUNSWICK - BAY OF FUNDY CLAM HARVESTING AREA 7 is described as follows:The inland and tidal waters of the counties of Charlotte, Saint John and Albert that flow into the Bay of Fundy.

The Coastal Environmental Baseline Program is a multi-year Fisheries and Oceans Canada initiative designed to work with Indigenous and local communities and other key parties to collect coastal environmental data at six unique sites across Canada, including the Port of Saint John (New Brunswick). The overall purpose of the Program is to collect localized ecological data in these areas to build a better baseline understanding of marine ecological conditions. The Maritimes region has developed a physical oceanography project to align with the interests and data needs of local communities and stakeholders. Starting in 2020, data describing the depth and temperature of tidal flood waters have been collected at a series of intertidal locations in the Port of Saint John vicinity, to characterize high marsh flood tides and water level fluctuations near the Courtenay Bay causeway. Inundation by marine waters in high marsh areas is typically limited to spring tides, while the water level in Courtenay Bay is influenced by anthropogenic infrastructure (e.g. causeway, tide gates). The resulting data can enhance studies ranging from coastal vulnerability and resilience to salt marsh morphodynamics, by quantifying the frequency, amplitude and duration of tidal inundation. Data were collected using Hobo U20-001-02 water level loggers, which were deployed inside stilling wells constructed from 15-inch lengths of perforated ABS pipe (2¼” diameter). The stilling wells were sunk to a depth of 6 inches below ground, with the water level logger suspended inside the well from a bolt near the top. The logger was positioned with a rigid wire such that the measurement volume was equal to ground level, while allowing the logger to be easily removed for downloading and precisely replaced at the measurement location. Loggers were accessed 2-3 times per year to download, and were removed during the winter months. Data have been compensated for changing atmospheric pressure using the Barometric Compensation Tool in HobowarePro (version 3.7.21) and barometric pressure data collected from a dry location during the study period. The resulting water level is reported in meters, and is relative to the elevation of the water level logger (e.g. above ground level).Citation: Port of Saint John intertidal water level and temperature (2020-2022). Coastal Environmental Baseline Program. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. XX-XX-2024

A tidal resource assessment dataset for the Quatsino Sound region, British Columbia, was developed, including temporal maximum, mean, and minimum velocity magnitudes, standard deviations, and power density. The dataset was generated using a high-resolution 2D depth-averaged hydrodynamic model based on the Telemac-Mascaret solver, with Natural Neighbor interpolation applied for raster creation. This newly published dataset is the first in a series of regional tidal energy maps for Canada. Developed by CanmetENERGY Ottawa in collaboration with partners, these maps aim to support effective project planning and development by providing comprehensive tidal resource data across the country.Disclaimer:Potential errors in the model results may arise from inherent limitations in the topo-bathymetric data accuracy, assumptions in boundary conditions, approximations within the numerical methods, and the input data used in the numerical modeling. These factors introduce uncertainties that can affect the overall model outcomes. The model is subject to the following conditions:• Topo-bathymetric data: Obtained from electronic navigational charts and the Canadian Hydrographic Service’s (CHS) NONNA-10 Bathymetric Data packages, consolidating CHS-managed digital bathymetric sources with a maximum resolution of 10 m.• Tidal and current harmonic components: Used as boundary conditions from the TPXO9 global tidal model.• Model calibration and validation: Performed using data from Acoustic Doppler Current Profilers (ADCP), surface elevations recorded at CHS tidal stations, and Lagrangian drifter measurements.• Interpolation method: Dataset outputs were generated with Natural Neighbor interpolation, which assumes smoothly varying data and may not capture sharp local gradients or features.• Modeled estimates: All values for velocity magnitudes, velocity standard deviations, and power density are modeled estimates and not direct field measurements.This dataset is intended for preliminary assessment of tidal projects only. It should not be the sole basis for making critical decisions or investments. We strongly recommend further validation and in-depth analysis. Users are responsible for conducting their own due diligence and additional research to verify the data's accuracy and relevance for specific applications.By accessing and using this dataset, users acknowledge and accept these disclaimers. The providers of this dataset explicitly absolve themselves of any responsibility or liability for any consequences arising from the use, reliance upon, or interpretation of this dataset. Users are advised that their use of the dataset is at their own risk, and they assume full responsibility for any actions or decisions made based on the information contained therein. This disclaimer is in accordance with applicable laws and regulations, and by accessing or utilizing the dataset, users agree to release the providers of this dataset from any legal claims, damages, or liabilities that may arise from such use.

The locations of the 2 specialty crop areas in the Greenbelt Plan: * the Holland Marsh * Niagara Peninsula Tender Fruit and Grape Lands

Canadian tides and water level station information, benchmarks, observed water level data, and tidal predictions.The Canadian tide and water level data archive presently holds water level observations reported from over a thousand stations, with the earliest dating back to 1848. The number of observations spans on average 6 years per station, with 60 stations measuring water levels for over 50 years.Over 800 stations are subjected to appreciable effect of tides, and for most of these stations, the Canadian Hydrographic Service (CHS) calculates and publishes predictions of the water levels associated with the vertical movement of the tide.Observations from the CHS Permanent Water Level Network are added on a daily to monthly basis. Data are also exchanged annually with the Water Survey of Canada.Each point in the map represents a station with links to observations, tidal predictions, and benchmark information, where available.

This dataset was designed for Environment and Climate Change Canada's (ECCC) National Environmental Emergencies Center (NEEC) for oil spill preparedness and response. The polygons from this layer come from the coastal ecosystems geodatabase as part of the Mapping of coastal ecosystems of the Estuary and Gulf of St. Lawrence project. This layer represents semi-vegetated (25-75%) and vegetated (75-100%) zones of which marsh vegetation is the dominant. The study area includes all of the estuarine and maritime coasts of Quebec, with the exception of certain sectors, including most of the Lower North Shore and Anticosti Island, with the exception of villages of Kegaska, la Romaine, Chevery, Blanc-Sablon and Port-Menier. Some islands off the estuary and gulf coasts are part of the region covered, such as Île d'Orléans, Isle-aux-Coudres, Île Verte and Île Bonaventure.The mapping of coastal ecosystems was carried out jointly by the Laboratory for Dynamics and Integrated Coastal Zone Management (LDGIZC) of the University of Quebec at Rimouski as part of the Coastal Resilience Project (https: //ldgizc.uqar.ca/Web/projets/projet-resilience-cotiere) funded by the MELCC; and by the Fisheries and Oceans Canada team, as part of its Integrated marine response planning (IMRP) component of the Oceans Protection Plan (OPP), with the objective of updating the Marine Oil Spill Preparedness and Response Regime of Canada. The master geodatabase of coastal ecosystems is hosted and distributed by UQAR on their SIGEC-Web mapping platform: https://ldgizc.uqar.ca/Web/sigecwebThe characterization of marshes was mainly carried out using photo-interpretation of RVBI aerial photos acquired by DFO (2015-2020) and oblique photos taken by helicopter acquired by UQAR in 2017. This dataset also includes the information from validation stations visited by UQAR (2018-2020), used to validate and refine the photo-interpretation.

A geospatial database involving 130 descriptors was created describing the pelagic and benthic habitats of the 0–30 m surface layer in the estuary and Gulf of St. Lawrence.A grid made of 6.25 km² cells (2.5 x 2.5 km) was used to aggregate the data. Each of the 39,337 cells overlapping the marine environment was characterized using landscape, hydrographic, and oceanographic parameters determined from observations (including satellite imagery), a 3D circulation model, and published and unpublished material available at local and regional scales.PurposeThe dataset provides useful information on the spatial extent of major coastal epipelagic habitats in the study area and can be used for mapping purposes and for analyses of species-habitat relationships.Additional InformationThe low tide limit was taken as the upper (0 m) boundary, but neighbouring landscape features, such as the proximity to freshwater inflows, surface area of the tidal zone, and characteristics of the shoreline, were also taken into consideration.Also, each cell was classified as being marine, intertidal, or terrestrial using the high and low tide marks. Those marks were determined using NRCan CANVEC topographic map products (1:50,000). The high tide mark was determined as the limit between the land and water layers. The low tide mark (0 m depth) was determined as the lower limit of the tidal zone in areas with a tidal zone, and as the limit between the land and water layers elsewhere.See the report mentioned below for a more detailed description of the treatments for each variable:Dutil, J.-D., S. Proulx, P. Galbraith, J. Chassé and N. Lambert 2012. Coastal and epipelagic habitats of the St. Lawrence estuary and Gulf. Can. Tech. Rep. Fish. Aquat. Sci. 3009 : ix +87 pp.

This Web Map Service depicts the location of clean electricity generating facilities by type of clean energy source and power generation capacity. Clean energy sources shown on the map include biomass, hydro, nuclear, solar, tidal and wind. The data comes from the provinces and territories, other federal departments and clean energy associations in Canada. The service is one of many themes mapped in the web mapping application Map of Clean Energy Resources and Projects (CERP) in Canada.

These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.