This dataset provides geospatial polygon boundaries for marine bivalve shellfish harvest area classification in British Columbia, 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 The classification may be superseded at any time by regulatory orders issued by DFO, which place areas in Closed Status, due to conditions such as sewage overflows or elevated biotoxin levels.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

This dataset contains the outputs for Bute Inlet from two simulations shown in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). The Finite Volume Community Ocean Model (FVCOM v4.1) was run with two different sets of initial conditions for the Discovery Islands region of British Columbia, Canada, from May 24 to June 27, 2019. The "Baseline" simulation used observed initial conditions, while the "Sensitivity" simulation removed the observed cold subsurface water mass from the initial profiles. Here in this dataset, we provide 29-day averages of the following variables in a transect along Bute Inlet: potential temperature, density, along-inlet velocity, and Brunt-Väisälä frequency (N^2). The averaging properly removes the tidal effects.

This dataset provides geospatial polygon boundaries for marine bivalve shellfish harvest area classification in New Brunswick, 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

In 2015, a magnitude 4.7 earthquake occurred 60 km beneath Sidney, BC. This scenario visualizes the effects of that event if it had a magnitude of 7.1.

In September 1732 a damaging earthquake occurred immediately beneath the Island of Montréal. This scenario visualizes the effects of that event if it occurred today with a magnitude of 5.0, and represents a strong ground shaking event that could strike Montréal.

This dataset represents meat weight and shell height data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey collected from June to mid-August. Wet meat weights were recorded to a tenth of a gram and shell heights are measured in millimeters. Meat weights and shell heights are sampled from a subset of scallops caught on survey and this detailed sampling is conducted from approximately half of the tows conducted. Each row in the dataset represents an individual scallop and contains information such as tow number, tow date, cruise name, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Meat Weight and Shell Height Data 2011 to 2023. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/65d32794-2d81-4682-b0ea-8d8bbe907a58

A web application that shows the location of businesses in Manitoba that offer agri-food by-products or related services.This web application shows the geographic location of Manitoba businesses that offer agri-food by-products or related services. This list is not exhaustive and does not constitute a recommendation for services. For more information, visit the Manitoba Agriculture website. Contact Manitoba Agriculture at agindustrydev@gov.mb.ca if you want your business listed. This web application uses the point element layer from the Manitoba Agri-Food By-Product Directory and the Manitoba Agri-Food By-Product Map.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The Northwest Atlantic Fisheries Organization (NAFO) Secretariat, Fisheries and Oceans Canada (DFO) and the Canadian Hydrographic Service (CHS) have collaborated to update the spatial representation of the NAFO Subareas, Divisions, and Subdivisions as defined in Annex 1 to the Convention on Cooperation in the Northwest Atlantic Fisheries (2020) (https://www.nafo.int/Portals/0/PDFs/key-publications/NAFOConvention.pdf). The NAFO Convention does not indicate which datum should be used for spatial representation. The datum used at the time of development of the NAFO Convention would have been North American Datum 1927 (NAD27). However, all datasets were derived using NAD83.International boundaries have been updated based on accepted coordinates between the USA and Canada (http://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.php), and Canada and Greenland (https://www.treaty-accord.gc.ca/text-texte.aspx?id=105136).This version of the NAFO Divisions is not intended to be used for legal purposes and is being provided for mapping / illustrative purposes only.

Layer of dots showing where custom packaging services in Manitoba are located.This dot layer shows where custom packaging services in Manitoba are located. A contract packager (subcontractor) is a company that manufactures and packages food products sold by other businesses. This list is not exhaustive and does not constitute a recommendation for services. For more information, visit the Manitoba Agriculture website. This point layer is used in the Manitoba Custom Packaging Services Map and the Manitoba Custom Packaging Services app.Fields included [Alias (Field Name): Field Description] Business Name (Business_Name): Contract Packer Business Name: Contract Packer Business Name Service Details (Service_Details): Summary of Services Provided by the Contract Packager Processing Capabilities (Business_Name): Business Name of Contract Packager: Business Name: Business Name of Contract Packager: Business Name: Contract Packager Business Name Service Details (Service_Details): Summary of Services Provided by the Contract Packager Processing Capabilities (Business_Name): Business Name of the Packager _transformation): List of specific food processing processes that the packager has package can provide Minimum production (Minimum_Production): Minimum number of units per order required by the package packager Types of packaging (packaging_types): List of packaging options offered by the packager Permits and licenses (Permis_and_licenses): List of permits and licenses that the packager has Certificates (Certifications): List of certifications obtained by the packager (e.g. organic, kosher): List of certifications obtained by the packager, halal, vegan, gluten-free) Unverified certifications ( Certifications_unverified_): List of unverified certifications obtained by the contract packager (e.g., healthy quality food, good manufacturing practices, British Retail Consortium) Contact information (Contact information): Name of the contact person for the package packager Contact email of the contact person Email of the contact person Email (Email_of_the_contact person): Email of the contact person Number of the contact person (Number_of_the_the_person_resource): Email of the contact person Resource (s): Telephone number of the contact person Address (Address): Municipal address of the packager at package City or town (City_or_village): City or village of the package packager Website (Site_Web): URL of the packager's website Logo URL (Url_du_logo): URL of the package packager logo Latitude (Latitude): Latitudinal coordinates of the entity's representative center (Latitude): Latitudinal coordinates of the entity's representative center in decimal degrees Longitude (Longitude): Longitudinal coordinates of the entity's representative center in decimal degrees**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This data publication contains a set of files in which areas affected by fire or by harvest from 1984 to 2015 are identified at the level of individual 30m pixels on the Landsat grid. Details of the product development can be found in Guindon et al (2018). The change detection is based on reflectance-corrected yearly summer (July and August) Landsat mosaics from 1984 to 2015 created from individual scenes developed from USGS reflectance products (Masek et al, 2006; Vermote et al, 2006). Briefly, the change detection method uses a six-year temporal signature centered on the disturbance year to identify fire, harvest and no change. The signatures were derived from visually-interpreted disturbance or no-change polygons that were used to fit a decision tree model. The method detects about 91% of the areas harvested and 85% of the areas burned across Canada’s forests over the study period, but overestimates areas disturbed in the two initial and mostly in the two final years of the 1985 to 2015 time series. This is caused by the absence of appropriate pre-disturbance and post-disturbance data for the model-based detection and attribution. Disturbance coverage in those four years should therefore be used with caution. As in Guindon et al (2014), the method was designed to minimize commission errors and has a disturbance class attribution success rate of about 98%. The attribution success rate of disturbance year for fire is of about 69% for the exact year and of about 99% when attribution to the following year is also considered as a success. This common one-year lag is mostly due to the use of mid-summer Landsat mosaics for the analysis that will cause spring and fall events of the same year to be attributed to successive years. For example, a fire that occurred in the fall of 2004 (after July and August), will be detected and attributed to 2005, while for a fire that occurred in the spring of 2004 will be detected and attributed to 2004. The presence of clouds and shadows or image availability causes 10% of missing data annually and therefore can too delay the capture of events. The data provides uniform spatial and temporal information on fire and harvest across all provinces and territories of Canada and is intended for strategic-level analysis. Since no attention was given to other minor disturbances such as mining, road or flooding, the product should not be used for their identification. Finally, calibration datasets were developed for only three major forest pests (mountain pine beetle, eastern spruce budworm and forest tent caterpillar), but were folded within the “no-change” class in order to minimize commission errors for fire and harvest . Less common pests for which validation datasets are hard to develop were not considered and therefore could in rare circumstances generate false fire events. Considering that area having two (3.3%) to three disturbances (less than 1%) events are not common, only the most recent disturbance is provided, overlapping older disturbances in these rare case. ## Please cite this dataset as: Guindon, L., P. Villemaire, R. St-Amant, P.Y. Bernier, A. Beaudoin, F. Caron, M. Bonucelli and H. Dorion. 2017. Canada Landsat Disturbance (CanLaD): a Canada-wide Landsat-based 30-m resolution product of fire and harvest detection and attribution since 1984. https://doi.org/10.23687/add1346b-f632-4eb9-a83d-a662b38655ad ## Scientific article citation: The creation, validation and limitations of the CanLaD product are described in the Supplementary Material file associated with the following article: Guindon, L.; Bernier, P.Y.; Gauthier, S.; Stinson, G.; Villemaire, P.; Beaudoin, A. 2018. Missing forest cover gains in boreal forests explained. Ecosphere, 9 (1) Article e02094. doi:10.1002/ecs2.2094. ## Cited references: Masek, J.G., Vermote, E.F., Saleous N.E., Wolfe, R., Hall, F.G., Huemmrich, K.F., Gao, F., Kutler, J., and Lim, T-K. (2006). A Landsat surface reflectance dataset for North America, 1990–2000. IEEE Geoscience and Remote Sensing Letters 3(1):68-72. http://dx.doi.org/10.1109/LGRS.2005.857030. Vermote, E., Justice, C., Claverie, M., & Franch, B. (2016). Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sensing of Environment. http://dx.doi.org/10.1016/j.rse.2016.04.008.