The datasets contain land surface evapotranspiration (ET, in mm of H2O) for Canada's landmass at a spatial resolution of 5-km and temporal intervals of a month and a year over a 24-year period of 2000-2023. The ET was produced by the Land Surface Model EALCO (Ecological Assimilation of Land and Climate Observations) developed at Natural Resources Canada. The EALCO model was run at a 30-minute time step. The monthly (or annual) ET in the datasets is the sum of the 30-minute ET values in a month (or a year). Dew and frost formations simulated by EALCO are included in the ET as negative values, so the ET represents the net water flux between land surface and the atmosphere. Details of the datasets and the EALCO ET modelling algorithms can be found in Wang (2007, Simulation of Evapotranspiration and Its Response to Plant Water and CO2 Transfer Dynamics. J. Hydrometeorology, 9, 426-443, doi: 10.1175/2007JHM918.1) and Wang et al. (2013, Spatial and seasonal variations in evapotranspiration over Canada’s landmass. Hydrol. Earth Syst. Sci., 17, 3561–3575, doi:10.5194/hess-17-3561-2013).

The datasets contain water surface evaporation (PET, in mm of H2O) over Canada's landmass at a spatial resolution of 10-km and temporal intervals of a month and a year over a 24-year period of 2000-2023. The PET was produced by the Land Surface Model EALCO (Ecological Assimilation of Land and Climate Observations) developed at Natural Resources Canada. The PET algorithm in EALCO integrates the dynamic surface evolutions of liquid water, ice, and snow-on-ice for a waterbody into the Penman Equation. The PET was simulated at a daily time step. The monthly (or annual) PET in the datasets is the sum of the daily PET values in a month (or a year). Dew and frost formations simulated by EALCO are included in the PET as negative values, so the PET represents the net water flux between water surface and the atmosphere. Details of the dataset and the EALCO PET modelling algorithms can be found in Li, Wang, and Li (2020, Spatial variations and long‑term trends of potential evaporation in Canada. Scientific Reports, 10: 22089, doi.org/10.1038/s41598-020-78994-9).

Historical finds of Adelges abietis

The Ocean Data Inventory database is an inventory of all of the oceanographic time series data held by the Ocean Science Division at the Bedford Institute of Oceanography. The data archive includes about 5800 current meter and acoustic doppler time series, 4500 coastal temperature time series from thermographs, as well as a small number (200) of tide gauges. Many of the current meters also have temperature and salinity sensors. The area for which there are data is roughly defined as the North Atlantic and Arctic from 30° - 82° N, although there are some minor amounts of data from other parts of the world. The time period is from 1960 to present. The database is updated on a regular basis.

Records of marine mammal sightings (N = 5,324) collected by ASOs and submitted to Fisheries and Oceans Canada (DFO) between 1979-2024, across three DFO regions: the Arctic, Newfoundland and Labrador, and the Maritimes. Methods for initial data compilation are provided in the associated technical report "Marine mammal records collected by the at-sea observer (ASO) program in Arctic, Newfoundland and Labrador, and Maritimes regions: a summary of challenges and opportunities for future research." Cite this data as: Feyrer, L.J., Colbourne, N., Lawson, J.W., Moors-Murphy, H.B., Ferguson, S. Dataset update to Marine mammal records collected by the At-Sea Observer program in Arctic, Newfoundland and Labrador and Maritimes regions. Published: February 2025. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.

A compendium of reports that provide information about aquatic and terrestrial animals and plants, soils, surface water, groundwater and their accompanying data files and maps

The Innu Audio Index is an extract from the Canadian Geographical Names Data Base (CGNDB) of geographical names with associated audio. The shared audio with the Geographical Names Board of Canada (GNBC) is the intellectual property of the Innu Nation. The points represent official geographical names in Innu-aimun, the language of the Innu Nation. The CGNDB is the authoritative national database of Canada's geographical names. It contains geographical names and their attributes that have been approved by the GNBC, the national coordinating body responsible for standards and policies on place names.The GNBC is working to increase awareness of existing Indigenous place names and help promote the revitalization of Indigenous cultures and languages. The GNBC does not warrant or guarantee that the information is accurate, complete or current at all times. For more information, to report data errors, or to suggest improvements, please contact the GNBC Secretariat at Natural Resources Canada with questions or for more information.

The Steller sea lion (Eumetopias jubatus) is the largest species of sea lion with males weighing as much as 1,100 kg and females as much as 350 kg. In Canada, the Steller can be spotted along the rocky coast of British Columbia (BC). These highly mobile marine mammals typically travel alone or in small groups, but they congregate in large numbers at traditional rookeries and haul-outs during the mating and pupping season. Females generally live longer (up to 30 years) than males (usually up to 20 years). The population was severely depleted in Canada but following its protection in 1970, the size of the adult population has more than doubled.Trends in the abundance of Steller sea lions in BC have been assessed based on a series of standardized, province-wide aerial surveys conducted during the breeding season (27-June to 06-July) between 1971 and 2021. Additional ad-hoc surveys during the fall, winter, and spring periods were completed to assess sea lion distribution outside of the breeding season. Surveys targeted historically occupied rookeries and haul-out sites with nearby areas also monitored for potential shifts in distribution.Both datasets contain counts that have been collected from sightings of individuals from 1971 through 2021. The updated standard breeding season survey counts data file consolidates and extends two previous datasets – one covering 1971 through 2013 and the other covering the summer portion of the 2016/2017 surveys. The non-breeding season count data was previously limited to the fall-winter portion of the 2016/2017 surveys and the updated data covers the entire study period to date.

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.