Spatial data for approved and post construction features for Canada Energy Regulator (CER) related ancillary features and Energy Resources Activities Act (ERAA) associated oil and gas activities collected on or after October 30, 2006. Associated oil and gas activities are related activities which require the use of Crown land and require an authorization under either the Land Act or the Petroleum and Natural Gas Act. The dataset includes polygon features such as campsites, workspaces, deck sites, staging areas, and other temporary disturbances. This dataset is updated nightly.

The hydrographic 1991 to 2020 climatology for the Maritimes region Atlantic Zone Monitoring Program core transects, Cabot Strait, Louisbourg, Halifax, Browns Bank, and Northeast Channel, are calculated to support annual reporting on seasonal variability. Details on data coverage for these transects and ancillary transects occupied since the inception of the program are provided. Comparisons with the previous climatology period, years 1981 to 2010, are summarized when possible.Cite this data as: Layton, C. Data of:Maritimes Region Atlantic Zone Monitoring Program 1991 to 2020 Hydrographic Transect Climatology.Published: August 2025. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.https://open.canada.ca/data/en/dataset/5f9c5d65-3ce1-4bdd-8b43-34086620d1e3

Organic soils in the boreal forest commonly store as much carbon as the vegetation above ground. While recent efforts through the National Forest Inventory has yielded new spatial datasets of forest structure across the vast area of Canada’s boreal forest, organic soils are poorly mapped. In this geospatial dataset, we produce a map primarily of forested and treed peatlands, those with more than 40 cm of peat accumulation and over 10% tree canopy cover. National Forest Inventory ground plots were used to identify the range of forest structure that corresponds to the presence of over 40 cm of peat soils. Areas containing that range of forest cover were identified using the National Forest Inventory k-NN forest structure maps and assigned a probability (0-100% as integer) of being a forested or treed peatland according to a statistical model. While this mapping product captures the distribution of forested and treed peatlands at a 250 m resolution, open, completely treeless peatlands are not fully captured by this mapping product as forest cover information was used to create the maps. The methodology used in the creation of this product is described in:Thompson DK, Simpson BN, Beaudoin A. 2016. Using forest structure to predict the distribution of treed boreal peatlands in Canada. Forest Ecology and Management, 372, 19-27. https://cfs.nrcan.gc.ca/publications?id=36751 This distribution uses an updated forest attribute layer current to 2011 from:Beaudoin A, Bernier PY, Villemaire P, Guindon L, Guo XJ. 2017. Species composition, forest properties and land cover types across Canada’s forests at 250m resolution for 2001 and 2011. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990 Additionally, this distribution varies slightly from the original published in 2016 in that here slope data is derived from the CDEM: https://open.canada.ca/data/en/dataset/7f245e4d-76c2-4caa-951a-45d1d2051333 The above peatland probability map was further processed to delineate bogs vs fens (based on mapped Larix content via the k-NN maps), as well as an approximation of the extent of open peatlands using EOSD data. The result is a 9-type peatland map with a more complete methodology as detailed in: Webster, K. L., Bhatti, J. S., Thompson, D. K., Nelson, S. A., Shaw, C. H., Bona, K. A., Hayne, S. L., & Kurz, W. A. (2018). Spatially-integrated estimates of net ecosystem exchange and methane fluxes from Canadian peatlands. Carbon Balance and Management, 13(1), 16. https://doi.org/10.1186/s13021-018-0105-5 In plain text, the legend for the 9-class map is as follows:value="0" label="not peat" alpha="0"value="1" label="Open Bog" alpha="255" color="#0a4b32"value="2" label="Open Poor Fen" alpha="255" color="#5c5430"value="3" label="Open Rich Fen" alpha="255" color="#792652"value="4" label="Treed Bog" alpha="255" color="#6a917b"value="5" label="Treed Poor Fen" alpha="255" color="#aba476"value="6" label="Treed Rich Fen" alpha="255" color="#af7a8f"value="7" label="Forested Bog" alpha="255" color="#aad7bf"value="8" label="Forested Poor Fen" alpha="255" color="#fbfabc"value="9" label="Forested Rich Fen" alpha="255" color="#ffb6db"This colour scale is given in qml/xml format in the resources below. The 9-type peatland map from Webster et al 2018 was further refined slightly following two simple conditions: (1) any 250-m raster cell with greater than 40% pine content is classified as upland (non-peat); (2) all 250-m raster cells classified as water or agriculture via the NRCan North American Land Cover Monitoring System (https://doi.org/10.3390/rs9111098) is also classified as non-peatland (value of zero in the 9-class map. This mapping scheme was used at a regional scale in the following paper: Thompson, D. K., Simpson, B. N., Whitman, E., Barber, Q. E., & Parisien, M.-A. (2019). Peatland Hydrological Dynamics as A Driver of Landscape Connectivity and Fire Activity in the Boreal Plain of Canada. Forests, 10(7), 534. https://doi.org/10.3390/f10070534 And is reproduced here at a national scale. Note that this mapping product does not fully capture all permafrost peatland features covered by open canopy spruce woodland with lichen ground cover. Nor are treeless peatlands near the northern treeline captured in the training data, resulting in unknown mapping quality in those regions.

This dataset includes all drainage culverts with a n opening diameter of less than 2 metres. Culverts with a diameter greater than 2 metres are defined as structural culverts and are not present in this dataset.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

Description:Chlorophyll-a concentration (a proxy for phytoplankton biomass) was retrieved from the MODIS instrument on the Aqua satellite, with data distributed by the NASA Ocean Biology Processing Group, and averaged into monthly climatological composites. The data span the years 2003-2020 and this record includes data at 4 km pixel resolution.Methods:MODIS-Aqua Chlorophyll-a (Chl-a) was acquired from the NASA Ocean Biology Processing Group at processing Level-3 (version 2018), 4-km resolution, where Chl-a concentration was calculated using the OC3/OCI method. The months of January and December were excluded from this dataset, as data in the winter months at higher latitudes are missing due to low sun angle preventing acquisition. The monthly geometric mean value at all pixels was calculated for individual years, then the geometric mean and geometric standard deviation factor of chlorophyll-a were calculated by month from these images. These methods of calculating mean and standard deviation were used due to the log-normal distribution of chlorophyll-a. The geometric standard deviation is a unitless factor, where the lower bound is the ratio of the geometric mean and geometric standard deviation, and the upper bound is the multiplication of the two. In addition to the geometric mean and geometric standard deviation factor the number of occurrences of valid data at each pixel over the period of observation were calculated. Pixels with fewer than two occurrences over the entire period of observation were removed from these maps, and set to a NaN value in the tif files. All resulting rasters were cropped to the Canadian Exclusive Economic Zone and assigned to the NAD83 geographic coordinate reference system (EPSG:4269), and have a final pixel resolution of approximately 0.0417 degrees. The monthly geometric mean, monthly geometric standard deviation factor, and number of occurrences for all pixels are provided.Data Sources:NASA Ocean Biology Processing Group. (2017). MODIS-Aqua Level 2 Ocean Color Data Version R2018.0. NASA Ocean Biology Distributed Active Archive Center. https://doi.org/10.5067/AQUA/MODIS/L2/OC/2018Uncertainties:Satellite values have been evaluated against global datasets, and datasets of samples in the Pacific region (see references). However, uncertainties are introduced when averaging together images over time as each pixel has a differing number of observations. Short-lived or spatially limited events may be missed.

Sponge reefs are constructed by hexactinellid (glass) sponges of the Order Hexactinosida. The sponges trap fine sediments, and over centuries of sponge growth and sediment trapping, form large bioherms or reef mounds. Glass sponge reefs are unique habitats found along the Pacific coast of Canada and the United States and they have significant historic, ecological, and economic value. They link benthic and pelagic environments by playing important roles in filtration and carbon and nitrogen processing, and acting as silica sinks. They also form habitat for diverse communities of invertebrates and fish, including those of economic importance. Thus, accurate and up-to-date information on the location and spatial extent of sponge reefs is important to the management and conservation of many of Canada’s Pacific marine species. We generated a map of known sponge reefs, derived from two source shape files: 1) Sponge_Reef_West_Coast, mapped by Natural Resources Canada (NRCan), 2) Howesound_Nine_reef_polygons and 3) HoweSound_Five_reef_polygons, which were mapped by DFO and NRCan. The resultant polygon shapefile is published on the GIS hub as a file geodatabase feature class.

A Conservation Unit (CU) is a group of wild Pacific salmon sufficiently isolated from other groups that, if extirpated, is very unlikely to recolonize naturally within an acceptable timeframe, such as a human lifetime or a specified number of salmon generations.Holtby and Ciruna (2007) provided a framework for aggregating the five species of salmon (genus Oncorhynchus) found on Canada’s Pacific coast into species-specific CUs based on three primary characteristics: ecotypology, life history and genetics. The first stage in the description of the Conservation Units is based solely on ecology. The ecotypologies used in this framework include a combined characterization of both freshwater and near-shore marine environments, and is termed “joint adaptive zone”. The second stage of the description involves the use of life history, molecular genetics, and further ecological characterizations to group and partition the first stage units into the final Conservation Units. The result is CUs that are described through the joint application of all three axes. It is important to note that CUs are distinct from other aggregates of Pacific salmon, such as designatable units (DUs) under the Species at Risk Act or management units (MUs).CU Counting Sites:Salmon spawner enumeration data in the Pacific Region is stored and managed in the New Salmon Escapement Database (NuSEDS). The term “escapement” is used to refer to the group of mature salmon that have ‘escaped’ from various sources of exploitation, and returned to freshwater to spawn and reproduce. This data is assigned to a “Counting Site”, which may be a complete watercourse with a marine terminus, a tributary to a larger watercourse, or a defined reach within a watercourse that may or may not encompass the entire population but represents an index of the abundance of that population. CU Status:CUs form the basic unit for assessment under Canada’s Policy for the Conservation of Wild Salmon Policy (WSP) (DFO 2005). The biological status of a CU is evaluated using a number of metrics (Holt et al. 2009; Holt 2009), which indicate a WSP status zone: Red (poor status), Amber (marginal status), or Green (healthy status). A final step then incorporates all metric and status-related information into a final integrated status for each CU, along with expert commentary to support the final status determination (e.g., DFO 2012; DFO 2016). This information is used as inputs to fisheries management processes to help prioritize assessment activities and management actions.Note: CU boundaries were reviewed in 2020-2021 and have been updated from the BC Freshwater Atlas 1:50,000 scale to the BC Freshwater Atlas 1:20,000 scale. The CU boundaries were last updated in March 2023. Please be aware that CUs may be reviewed and are subject to change without notice.Please refer to Conservation Unit Review Requests-Form and Summary for a list of CU review requests that are ongoing or have been finalized.

Description:Seasonal mean total alkalinity from the British Columbia continental margin model (BCCM) were averaged over the 1993 to 2020 period to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone.Methods:Total alkalinities at up to forty-six linearly interpolated vertical levels from surface to 2400 m and at the sea bottom are included. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal total alkalinity climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution and 47 vertical levels.Uncertainties:Model results have been extensively evaluated against observations (e.g. altimetry, CTD and nutrient profiles, observed geostrophic currents), which showed the model can reproduce with reasonable accuracy the main oceanographic features of the region including salient features of the seasonal cycle and the vertical and cross-shore gradient of water properties. However, the model resolution is too coarse to allow for an adequate representation of inlets, nearshore areas, and the Strait of Georgia.

This product provides the variability index for selected drainage regions in Canada. Variability is measured using a coefficient of variation (CV) to compare all months over a 42-year time period and is a measure of the dispersion or variation in the monthly yield values from 1971 to 2013 (and 1971 to 2012 for drainage region 1). It is defined as the ratio of the standard deviation to the mean or the standard deviation divided by the mean, with higher CVs indicating more variability in monthly water yields. The monthly variability was not calculated for drainage regions 5, 7, 8, 16, 17, 18, or the Labrador portion of 25.

Canada is divided into 338 electoral districts. A representative or member of Parliament is elected for each electoral district. Following the release of population counts from each decennial census, the Chief Electoral Officer determines the number of seats in the House of Commons and publishes the information in the Canada Gazette. Electoral boundaries commissions then determine the adjustments to the constituency boundaries. The federal electoral boundaries commissions are independent bodies that make all decisions regarding the proposed and final federal electoral boundaries. Elections Canada provides support services to the boundaries commission in each province. Based on reports from these commissions, the Chief Electoral Officer prepares a representation order that describes the boundaries and specifies the name and the population of each FED. The representation order is in force on the first dissolution of Parliament that occurs at least seven months after its proclamation. The 2013 Representation Order (proclaimed on October 5, 2013) was based on 2011 Census population counts, and increased the number of FEDs to 338, up from 308 from the previous 2003 Representation Order. Ontario received fifteen additional seats, Alberta and British Columbia each gained six seats while Quebec added three seats. On June 19, 2014, the Riding Name Change Act, 2014 (Bill C-37) received Royal Assent changing the names of 31 FEDs. The names of FEDs may change at any time through an Act of Parliament.