Get data on fish stocking records from 1900 - 2012. This dataset is the most complete collection of historical fish stocking records available for the time period 1900 to 2012. It includes: * data source * species * rearing location * developmental stage * stock strain * spawning year * stocking date Related datasets: * [Ontario waterbody location identifer](https://data.ontario.ca/dataset/ontario-waterbody-location-identifier)

The Ecological Land Mass (ELM) classification was established through the 2020 National Interest Land Mass (NILM) Update. ELM lands describe ecological corridors that have inherent natural values and that protect Species at Risk (SAR) and their habitats. The classification identifies lands to protect in perpetuity through planning and partnership efforts. ELM was derived from two separate analyses - the Ontario side from the AECOM natural linkages analysis (2012) and the Quebec side from Del Degan, Masse (DDM) ecological corridors analysis (2012). Adjustments were made as appropriate.

Basic biological data for all fish caught during the 2012 BSMFP expedition. Includes identification, weight, length (total, fork, and, standard), liver weight, gonad weight, sex and maturity level.

In 1949 a magnitude 8.1 earthquake occurred on the Queen Charlotte Fault, off the west coast of the Haida Gwaii archipelago. This magnitude 8.0 scenario along the Queen Charlotte Fault is slightly different and closer to population centres than the magnitude 7.8 earthquake that occurred in 2012.

In 1949 a magnitude 8.1 earthquake occurred on the Queen Charlotte Fault, off the west coast of the Haida Gwaii archipelago. This magnitude 7.7 scenario along the Queen Charlotte Fault is slightly different and closer to population centres than the magnitude 7.8 earthquake that occurred in 2012.

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 dataset contains observations of species occurrences from seafloor imagery collected by the remotely operated underwater vehicle (ROV) during the 2012 Expedition to Cobb Seamount. The ROV operated by Fisheries and Oceans Canada was a customized Deep Ocean Engineering Phantom HD2+2 which collected photographic images from 12 transects ranging from 35 m to 211 m in depth.

Temporal analysis of changes in the Iqaluit region, Nunavut, based on GeoAI features automatically extracted from satellite images acquired in 2012 and 2022. Simple geospatial analysis intersecting GeoAI multidate building features enables the detection of buildings observed in 2022 that were not detected in 2012. The addition of new buildings is a good indicator of urban development and/or sprawl.GeoAI enables temporal coverage of various areas in Canada, thus providing a useful tool for change detection and trend analysis at high resolution. While the series is still fairly new, and such examples are limited for the time being, NRCan strives to gradually increase its GeoAI data offering for both spatial and temporal coverage.For more information about the GeoAI - GeoBase Series, please visit the following link: https://open.canada.ca/data/en/dataset/74738ff5-5367-5958-9aee-98fffdcd1876

This dataset contains observations of species occurrences from seafloor imagery collected by the autonomous underwater vehicle (AUV) during the 2012 Expedition to Cobb Seamount. The National Oceanographic and Atmospheric Administration-operated SeaBED-class AUV which collected photographic images from 4 transects ranging from 436 m to 1154 m in depth.

Wildfire ignition density rasters separated by cause (human, natural (lightning)) for mean and normalized mean summaries from 1980 to 2023.