This GIS dataset depicts the surficial geology of NTS map area 84O south (permafrost polygon features). The data were created in geodatabase format and output for public distribution in shapefile format. The map was prepared by airphoto interpretation of 1:60 000-scale images flown in 1994. There was no ground-truthing.

Maximum Temperature represents the highest recorded temperature value (°C) at each location for a given time period. Time periods include the previous 24 hours and the previous 7 days from the available date where a climate day starts at 0600UTC.

This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census subdivision. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.

Heat Wave represents the consecutive number of days (April 1 – October 31) where the maximum daily temperature is greater than 25 or 30 degrees respectively. Heat wave products are only generated during the Growing Season, April 1 through October 31.

Phytoplankton species abundance (cell/L) and oceanographic conditions (temperature, salinity, chlorophylle-a (mg/m³) for some years and nutrient content (mmol/m³)) at stations of the Harmful Algae Monitoring Programme (HAMP) from1994 to 2016.The layer presents the station positions of the HAMP. Two files are attached to each station: one containing the cell counts and the second the oceanographic conditions.PurposeThe summer growth of many toxic and harmful microalgae species poses a serious threat for the public health and commercial or recreational exploitation of some marine species.The Department of Fisheries and Oceans (DFO) initiated the Harmful Algae Monitoring Programme (HAMP) in 1989 in order to complete the monitoring program for paralytic shellfish poisoning (PSP). Under the responsibility of Maurice-Lamontagne Institute scientists, the HAMP is to monitor, by means of a coastal station network, the natural occurrence of toxic and harmful algae in the St. Lawrence in order to determine their spatio-temporal distribution and the environmental conditions leading to their bloom.The network is made up of 11 coastal stations which are sampled every week from April to November and which are established along Quebec eastern shores. It extends from Tadoussac to Tête-à-la-Baleine on the St. Lawrence north shore and from Sainte-Flavie to Carleton on the south shore along the Gaspé peninsula. Another station is located in Havre-Aux-Maisons, Magdalen Islands.The HAMP was discontinued in 2010 but opportunistic samplings are still done at some stations.Additional informationThe sampling and analysis protocol is described in details in the following publication apart from the fact that the number of identified and counted species significantly has been increasing with time. Phytoplankton samples are preserved in a lugol solution.Blasco D., M. Levasseur, R. Gélinas, R. Larocque, A.D. Cembella, B. Huppertz et E. Bonneau.1998. Monitorage du phytoplancton toxique et des toxines de type IPM dans les mollusques du Saint-Laurent: 1989 à 1994. Rapp. stat. can. hydrogr. sci. océan. 15 1 : x i-117 p.

Background:More than 80% of the heat produced in the Earth's crust comes from granitoid rocks. When granitoid rocks form they naturally concentrate radioactive elements such as U, Th, and K, and the radiogenic decay of these elements is an exothermic reaction. The radioactive decay of these elements within a granitoid body may generate local heat anomalies and elevated geothermal gradient at relatively shallow crustal levels. In combination with other local rock properties (e.g, porosity, permeability, thermal conductivity), radiogenic heat has the potential to generate a geothermal resource. The decay of radioactive elements converts mass into radiation energy, which in turn gets converted to heat. While all naturally radioactive isotopes generate some heat, significant heat generation only occurs from the decay of 238 U ,235 U ,232 Th and 40 K. Therefore, potential heat production is governed by the concentrations of U ,Th and K in the rock. In igneous rocks, radiogenic heat production is dependent on the bulk chemistry of the rock and decreases from acidic (e.g. granite) through basic to ultra basic rock types. Therefore, granites with anomalously high concentrations of U ,Th and K are targets for calculating potential radiogenic heat production. Potential radiogenic heat production (A)from plutonic rocks can be calculated using this equation:A (\\u03BCW/m 3 )=10 -5 \\u1D29 (9.52c u +2.56c K +3.48c Th )where "c" is the concentration of radioactive elements "U" and "Th" in ppm, and "K" in %; and "\\u1D29" is the rock density. Heat production constants of the natural radio-elements U, Th, K are 9.525x10 -5 , 2.561x10 -5 and 3.477x10 -9 W/kg, respectively.Data and Methods:Geochemical data from \~1760 samples of plutonic rocks from Yukon are used to calculate potential heat production. The calculated values for radiogenic heat production (A) are plotted over the mapped distribution of Paleozoic and younger plutonic rocks and major crustal faults are also shown for reference.

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

Climatological monthly-mean temperature and salinity data were computed for each of the 27 Line P stations (https://www.dfo-mpo.gc.ca/science/data-donnees/line-p/index-eng.html). For any particular station, data were accepted as belonging to that station if the location was within 10 km of the intended station (or 24km at Ocean Station Papa, P26). Data were binned by month/year over all available data for each station up to and including 2012. Hence the time interval that the mean state was computed from starts between 1956 and 1960 and ends at the end of 2012. Standard deviations were computed for each month independently and at each 5-m depth bin and were estimated as the variability between different years for the month in question.

This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census division. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

The annual maximum and minimum daily data are the maximum and minimum daily mean values for a given year.