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).

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.

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

An exploratory project on the taxonomic and genetic diversity of decapods in three ocean subregions (Northeast Pacific, Canadian Arctic, and Northwest Atlantic), which were sampled in 2022, was undertaken by the Arctic Working Group under the Canada-U.S. Fisheries and Climate Collaboration between Fisheries and Oceans Canada (DFO) and the National Marine Fisheries Service (NMFS) of the National Oceanic and Atmospheric Administration (NOAA). This collaboration framework aims to pool Canadian and U.S. data to explore the impacts of broad-scale climate change on marine biodiversity. In early summer 2022, a sampling protocol with the selection of targeted decapods was provided to DFO and NOAA collaborators. Targeted genera were collected from a total of 10 research programs across three ocean subregions and four marine regions. The Northeast Pacific samples were collected in the Bering Sea during the Northern Bering Sea Ecosystem and Surface Trawl Survey, and the Eastern and Northern Bering Sea Continental Shelf Bottom Trawl Survey of Groundfish and Invertebrate Fauna onboard the F/V Northwest Explorer, F/V Alaska Knight and F/V Vesteraalen. In the Western Canadian Arctic (mainly from Beaufort Sea and Amundsen Gulf), specimens were collected during DFO’s Canadian Beaufort Sea – Marine Ecosystem Assessment (CBS-MEA) survey onboard the F/V Frosti. In Eastern Canadian Arctic (mainly from Baffin Bay and Davis Strait), specimens were collected during DFO’s Knowledge and Ecosystem-Based Approach in Baffin Bay (KEBABB) survey onboard the CCGS Amundsen and DFO’s North Atlantic Fisheries Organization (NAFO) Subarea 0B survey onboard the R/V Tarajoq. In the Estuary and Gulf of St. Lawrence (EGSL), specimens were collected from coastal surveys (scallops, sea cucumber, snow crab, and whelk surveys) onboard the CCGS Leim and offshore during the Ecosystemic Survey onboard the CCGS Teleost. Decapods were collected from various sampling gears (benthic beam trawl, modified Atlantic Western IIA otter trawl, Bacalao trawl, shrimp trawl, Digby scallop dredge, or modified sea cucumber dredge) and identified to the lowest possible taxonomic level and photographed, when possible. All specimens were frozen at sea (n = 995). In the lab, the identifications were validated or refined with the photos and the frozen specimens. DNA was extracted for 87 specimens and a section of COI gene was amplified in order to be sequenced using Sanger method. Sequences were compared with existing data using The Basic Local Alignment Search Tool (BLAST) in the National Center for Bio-technology Information Nucleotide database (NCBI-nt, including the GenBank database) to compare scientific names, where available.The present dataset includes 391 decapod species occurrences. DNA was extracted for a subset of 87 specimens (COI gene); sequences are publicly available on BOLD data portal under project code DDAO (see supporting document "citations_references.csv" for more information).The data are presented in Darwin Core format and are separated in three files:The "Activité_décapodes_DDAO_decapods_event_en" file contains information about missions, stations and deployments, which are presented under a hierarchical activity structure.The "Occurrence_décapodes_DDAO_decapods_en" file contains the taxonomic occurrences.The "ADN_décapodes_DDAO_decapods_DNA_en" file contains the DNA derived data.For further details, please refer to the technical report available in the supporting document named "citations_references.csv". USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

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.

The Integrated Resource Plan - Local dataset is comprised of all the polygons that represent the Local Integrated Resource Plans (IRP) in Alberta. A Local IRP provides land resource management direction for a relatively smaller geographic planning area. A Local Plan is developed to provide more detailed land and resource use parameters than may be available in a Sub-Regional Plan. An IRP is a plan which identifies the values and associated land and resource management goals for the planning area in consideration of the maintenance of social, economic, and ecological values. An IRP provides direction regarding the type of land and resource management activity that would facilitate meeting the stated objectives in the planning area (e.g. recreation, grazing, industrial and commercial activities). The public was often involved in contributing input to the development of an IRP. IRPs were endorsed by the Government of Alberta in various periods.

The ASTER instrument that was launched onboard NASA’s Terra spacecraft in December 1999 has an along-track stereoscopic capability using two telescopes in its near infrared spectral band to acquire data from nadir and backward views. Over 1.2 million scenes (level-1A products) acquired between March 2000 and August 2008 were used to generate the ASTER Global DEM (ASTGTM) collection.  For more information on the ASTER Global DEM, please see the metadata link.

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.

Border crossings of electric transmission lines. Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.Parent Collection:[North American Cooperation on Energy Information, Mapping Data](https://open.canada.ca/data/en/dataset/aae6619f-f9f3-435d-bc32-42decd58b674)