This polygon layer provides medium-range (up to 10 days) accumulated precipitation forecasts from the Global Deterministic Prediction System (GDPS), a worldwide numerical weather model run by Environment and Climate Change Canada. It addresses broad-scale weather systems and supplies boundary conditions for nested regional models.Global Scope: The GDPS covers the entire planet at ~15 km resolution, projecting large-scale atmospheric developments over a 240-hour window. Coupled Model: Integrates atmospheric and oceanic interactions, improving forecast accuracy for cyclones, frontal systems, and long-traveling storm patterns. Operational Backbone: Frequently used as a reference for regional or local models (e.g., RDPS) and for medium-range planning in water resource management or agriculture. Forecast Frequency: Runs twice daily, producing deterministic outputs that guide meteorologists, hydrologists, and emergency preparedness teams.

This polygon layer presents 7‑day and 10‑day accumulated precipitation forecasts from the Global Deterministic Prediction System (GDPS), aggregated by sub-basin. It is designed to help hydrologists, water resource managers, and emergency planners pinpoint watersheds facing higher rainfall or snowfall totals in the medium-to-long range, enabling proactive flood risk assessment, drought monitoring, and resource allocation.Developed by Environment and Climate Change Canada (ECCC), the GDPS is a global numerical weather prediction model running at approximately 15km resolution, updated twice daily (00Z and 12Z). This layer integrates 168-hour (7‑day) and 240-hour (10‑day) precipitation forecasts into sub-basin polygons, offering a comprehensive view of expected cumulative precipitation. By focusing on watershed boundaries, decision-makers can quickly gauge regional vulnerabilities to prolonged rainfall or snowfall events.Key highlights: Global Model Insight: Captures large-scale, multi-day weather systems (e.g., atmospheric rivers, persistent low-pressure systems). Sub-Basin Aggregation: Delivers averaged precip values per basin, simplifying hydrological analysis for flood or drought outlooks. Extended Outlook: Spanning from day 0 to day 10, covers both medium- and longer-term forecast horizons, essential for strategic planning and mitigation efforts. Typical Uses:Flood Forecasting – Identifying basins prone to heavy or prolonged precipitation. Water Resource Management – Adjusting reservoir release schedules or irrigation planning based on expected accumulations. Emergency Preparedness – Deploying resources or issuing advisories in vulnerable watersheds.

This polygon layer displays ensemble-based, medium-range precipitation forecasts from the Global Ensemble Prediction System (GEPS), offering a probabilistic view of future rainfall or snowfall over a 16‑day horizon. It aids in uncertainty analysis, risk assessment, and strategic resource planning.Ensemble Approach: GEPS runs multiple perturbed members of ECCC’s GEM model, capturing a range of atmospheric evolutions and yielding probability distributions for precipitation. Global Domain: Similar coverage to the GDPS but focuses on ensemble mean, spreads, and probabilities rather than a single deterministic outcome. Longer-Range Outlook: Extends up to 16 days, supporting risk-based planning for potential floods, extended rainfall events, or dryness. Data Utility: Allows decision-makers to weigh confidence levels in precipitation scenarios, vital for water management, agriculture, and emergency contingency strategies.

This file summarizes several indicators for the tourism industry. It contains annual information for key economic indicators of the tourism industry such as establishments by development region, size and tourism region. Tourism spending, revenue, GDP, price index, employment and wages.

This interactive map is a collaborative project by Natural Resources Canada and the federal, provincial and territorial members of the Geographical Names Board of Canada. The map illustrates a sample of close to 500 places in Canada named for women from a range of backgrounds who have been remembered for many different reasons. Each point on the map is categorized by a theme, and contains a short description of the person behind that place name. The descriptions reveal that information about these women and the places named for them varies widely; some are well-known and well-documented figures, while little is known about others.

2020 DATABASE (Excel): The joint federal-provincial Regional Geochemical Surveys (RGS) have been carried out in British Columbia since 1976 as part of the National Geochemical Reconnaissance (NGR) program to aid exploration and development of mineral resources. The British Columbia Geological Survey (BCGS) maintains provincial geochemical databases capturing information from multi-media surveys. This 2020 release of the most current and complete province-wide geochemical data set collected under the (RGS) program. The database was compiled from 116 original sources with 65,429 samples and about 5 million determinations analyzed using 18 methods in 18 laboratories. This release augments the database with new RGS data compiled from BCGS and Geoscience BC publications between 2016 and 2019. Compared with the data in the last release, data in this release have been given further quality control treatment and revision. For the ease of use and consistency with previously published data, the data set was generated from the RGS database in a flat tabular format. The 2020 data set, released as BCGS GeoGile 2020-08, is presented in two MS Excel files, ‘RGS2020_ data.xlsx’ and ‘RGS2020_metadata.xlsx’. The data tables capture locations, field observations, analytical results and laboratories, and geology underlying sample sites for stream-, lake- and moss-sediment, water and lake samples, heavy mineral concentrates, tree twig, and needle ash. The analytical determinations include up to 63 analytes from sediment samples and up to 78 analytes from water samples. These samples, collected at an average density of about 1 site per 7–13 km2, provide representative geochemical data for the catchment basin upstream from the sample site. The RGS currently covers approximately 80 percent of the province.

Fetch is a proxy for wind-wave action and exposure. Estimates of fetch over a total of 39,938 km of the BC coastline were calculated at 50 m intervals, yielding 799,220 near shore fetch points. Fetch was calculated for five regions in Pacific Canada: Haida Gwaii (HG), North and Central Coast (NCC), Queen Charlotte and Johnstone Straits (QCS), Salish Sea (SoG), and West Coast Vancouver Island (WCVI). For all regions, a bearing interval of 5 degrees was used to generate fetch lines for each point along the shoreline, resulting in 72 fetch lines per point. A maximum fetch distance of 200 km was used to ensure the barrier effect of Haida Gwaii was captured.Supplementary information provided includes the fetch geometry calculator script and user guide (Gregr 2014) and a report on the fetch processing objectives, process, and results (Gregr 2015).

The data layer (.shp) presented is the result of an unsupervised classification method for classifying seafloor habitat in the Bay of Fundy (Northwest Atlantic, Canada). This method involves separating environmental variables derived from multibeam bathymetry (slope, bathymetric position index), backscatter, and oceanographic information (wave-shear current velocity) into spatial units (i.e. image objects) and classifying the acoustically and oceanographically separated units into 7 habitat classes (Bedrock and Boulders, Mixed Sediments, Gravelly Sand, Sand, Silty Gravel with Anemones, Silt, and Tidal Scoured Mixed Sediments) using in-situ data (imagery). Benthoscape classes (synonymous to landscape classifications in terrestrial ecology) describe the geomorphology and biology of the seafloor and are derived from elements of the seafloor that were acoustically and oceanographically distinguishable. Reference:Wilson, B.R., Brown, C.J., Sameoto, J.A., Lacharite, M., Redden, A. (2021). Mapping seafloor habitats in the Bay of Fundy to assess macrofaunal assemblages associated with Modiolus modiolus beds. Estuarine, Coastal and Shelf Science, 252. https://doi.org/10.1016/j.ecss.2021.107294Cite this data as: Wilson, B.R., Brown, C.J., Sameoto, J.A., Lacharite, M., Redden, A. Bay of Fundy Benthoscape. Published May 2023. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/dbabd17a-a2c7-4b3f-9bd8-a77a9c7f9c1c

DFO Maritimes Region has conducted a cumulative human impact mapping analysis for the Scotian Shelf-Bay of Fundy management area to support ongoing Marine Spatial Planning initiatives (Murphy et al. 2024). Cumulative human impact mapping (CIM) combines spatial information on human activities and habitats with a matrix of vulnerability weights, into an intuitive relative ‘cumulative impact score’ that shows where cumulative human impacts are greatest and least. To map cumulative impacts in DFO’s Maritimes Region, a recently developed ecosystem vulnerability assessment for Atlantic Canadian waters (Murray et al. 2022) was combined with spatial information on 21 different habitat types and 45 human activities across five different sectors (climate change, land-based, marine-based, coastal, commercial fishing) following the methodology from Halpern et al. (2008). An uncertainty analysis of the cumulative impact map was conducted to assess the robustness of results and identify hot and cold spots of cumulative impacts. This dataset provides: 1) cumulative impact maps for the DFO Maritimes Region at 1 km2 resolution: a total cumulative impact map (i.e. including all 45 human activities), as well as cumulative impact maps for each of the five sectors, 2) a layer that identifies which grid cells are considered hot and cold spots of cumulative human impacts, and 3) the habitat layers included in the CIM.For further information concerning specifics of the maps and methods see Murphy et al. (2024) or contact the data provider. References:Halpern, B.S., Walbridge, S., Selkoe, K.A., Kappel, C.V., Micheli, F., D'Agrosa, C., Bruno, J.F., Casey, K.S., Ebert, C., Fox, H.E., Fujita, R., Heinemann, D., Lenihan, H.S., Madin, E.M.P., Perry, M.T., Selig, E.R., Spalding, M., Steneck, R., and Watson, R. 2008. A Global Map of Human Impact on Marine Ecosystems. Science. 319(5865): 948-952. doi:10.1126/science.1149345.Murray, C.C., Kelly, N.E., Nelson, J.C., Murphy, G.E.P., and Agbayani, S. 2022. Cumulative impact mapping and vulnerability of Canadian marine ecosystems to anthropogenic activities and stressors. DFO Can. Sci. Advis. Sec. Res. Doc. 2022/XXX. vi. + 52 p.Murphy, G.E.P., Stock, A., and Kelly, N.E. 2024 (in press). From land to deep sea: A continuum of cumulative human impacts on marine habitats in Atlantic Canada. Ecosphere.Cite this data as: Murphy, Grace; Kelly, Noreen (2023) Cumulative human impact maps for the Bay of Fundy and Scotian Shelf. Published September 2023. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/37b59b8b-1c1c-4869-802f-c09571cc984b

The current and most detailed version of the approved corporate provincial digital Biogeoclimatic Ecosystem Classification (BEC) Zone/Subzone/Variant/Phase map (version 12, September 2, 2021). Use this version when performing GIS analysis regardless of scale. This mapping is deliberately extended across the ocean, lakes, glaciers, etc to facilitate intersection with a terrestrial landcover layer of your choice