Arctic SDI catalogue
RI_540
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This dataset provides 1/36-degree monthly-mean ocean current climatology (April - September) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).
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The Remote Communities Energy Database is a public resource that provides pertinent factual information about the generation and use of electricity and other energy sources for all remote communities in Canada. Communities are identified as remote communities if they are not currently connected to the North-American electrical grid nor to the piped natural gas network; and is a permanent or long-term (5 years or more) settlement with at least 10 dwellings. The Remote Communities Energy Database is the only national data source on energy in remote communities that is publically available on one centralized site. The Remote Communities Energy Database allows users to search and conduct analyses of remote communities and their energy context. Users are also able download the data from the Remote Communities Energy Database dataset in CSV (i.e., excel compatible) format. This data is collected from a number of sources including the remote communities themselves, local utilities, provincial and territorial government’s, Indigenous and Northern Affairs Canada (INAC), Statistics Canada, Natural Resources Canada (NRCan) and various other stakeholders.
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This data depicts site suitability for the establishment of area-based Short Rotation Woody Crops (SRWC) of willow on lands eligible (i.e. non-forested) for afforestation across Canada. Determining the feasibility of a large-scale afforestation program is one approach being investigated by the Government of Canada to increase Canada's potential to sequester carbon from the atmosphere and/or produce bioproducts and bioenergy. Large-scale afforestation, however, requires knowledge of where it is suitable to establish and grow trees. Spatial models based on Boolean logic and/or statistical models within a geographic information system may be used for this purpose, but empirical environmental data are often lacking, and the association of these data to land suitability is most often a subjective process. As a solution to this problem, a fuzzy-logic modeling approach to assess site suitability for afforestation of hybrid poplar (Populus spp.) and willow (Salix spp.) in Canada was developed. Expert knowledge regarding the selection and magnitudes of environmental variables were integrated into fuzzy rule sets from which estimates of site suitability were generated and spatially presented. The environmental variables selected included growing season precipitation, climate moisture index, growing degree days, the Canada Land Inventory capability for agriculture and elevation. Site suitability is generally defined as the fitness of a given type of land for a particular use. For this assessment, site suitability was defined as the fitness of edaphic, climatic and topographic conditions to establish and grow SRWC species at rates 8 times those of native species. Suitability index values range from 1-100, with higher values corresponding to higher suitability. Approximately 246,000 km2, or 38% of the eligible land base within Canada was found to be suitable for afforestation using Short Rotation Woody Crops (SRWC) of hybrid poplar and/or willow.
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Polygons denoting concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations and the area occupied by successive catch weight thresholds was used to identify aggregations. These analyses were performed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures. These polygons identify sea pen fields from the broader distribution of seapens in the region as sampled by Cosmos trawl gear in the Eastern Arctic biogeographic zone. A 0.1 kg minimum threshold for the sea pen catch was identified as the weight that separated the sea pen field habitat from the broader distribution of sea pens with these research vessel tow data and gear type.
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Polygons denoting concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations and the area occupied by successive catch weight thresholds was used to identify aggregations. These analyses wereperformed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures. These polygons identify small gorgonian coral fields from the broader distribution of small gorgonian corals in the region as sampled by Campelen trawl gear in the Eastern Arctic biogeographic zone. A 0.05 kg minimum threshold for the small gorgonian coral catch was identified as the weight that separated the small gorgonian field habitat from the broader distribution of small gorgoninan corals with these research vessel tow data and gear type.
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The raster maps depict a suite of forest attributes in 2001* and 2011 at 250 m by 250 m spatial resolution. The maps were produced using the k nearest neighbours method applied to MODIS imagery and trained from National Forest Inventory photo plot data. For detailed information about map production methods please refer to Beaudoin et al. (2018) "Tracking forest attributes across Canada between 2001 and 2011 using the k nearest neighbours mapping approach applied to MODIS imagery." Canadian Journal of Forest Research 48, 85-93. https://cfs.nrcan.gc.ca/publications?id=38979 The map datasets may be downloaded from https://nfi.nfis.org/downloads/nfi_knn2011.zip or https://open.canada.ca/data/en/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 * Note: the forest composition (leading tree genus) map depicts forest attributes in 2001. How can this data be used? The resolution and accuracy of these map products are best suited for strategic-level forest reporting and informing policy and decision making at regional to national scales. As these maps also offer a coherent set of quantitative values for a large suite of forest attributes, they can be used as baseline information for modelling and in calculations such as merchantable forest volume or percentage of tree species. It is also possible to overlay these maps with other maps produced on the same pixel grid to make assessments of disturbance impacts, such as fire and harvests.
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Phytoplankton pigments, determined by high-performance liquid chromatography (HPLC) are measured on DFO cruises three times a year in February, June, and August/September along Line P in the northeast subarctic Pacific. Sampling for phytoplankton pigments started in 2006 at the five main Line P stations and was expanded to sample at all twenty seven stations along the transect in June 2010.
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Identification of significant concentrations of sea pens in the Gulf of St. Lawrence biogeographic unit using Kernel density estimation (KDE). This method was applied to create a modelled biomass surface for each taxa and an aerial expansion method was permitted to identify significant concentrations. Only geo-referenced biomass data have been used to identify the “hot spots”. The borders of the areas were refined using knowledge of null catches and species distribution models. Predictive models were produced using a random forest machine-learning technique. For more details, please refer to this report: Kenchington, E., L. Beazley, C. Lirette, F.J. Murillo, J. Guijarro, V. Wareham, K. Gilkinson, M. Koen Alonso, H. Benoît, H. Bourdages, B. Sainte-Marie, M. Treble, and T. Siferd. 2016. Delineation of Coral and Sponge Significant Benthic Areas in Eastern Canada Using Kernel Density Analyses and Species Distribution Models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/093. vi + 178 p. http://waves-vagues.dfo-mpo.gc.ca/Library/40577806.pdf The present layer only contains the analysis results for sea pens. Purpose: As part of the Canada's commitment to the identification and protection of sensitive benthic marine ecosystems, maps of the location of significant concentrations of corals and sponges on the east coast of Canada were produced through quantitative analyses of research vessel trawl survey data, supplemented with other data sources where available. The taxa analyzed are sponges (Porifera), large and small gorgonian corals (Alcyonacea), and sea pens (Pennatulacea). However, only the sponges (Porifera) and sea pens (Pennatulacea) have been considered in the analysis concerning the Gulf of St. Lawrence biogeographic unit.
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The raster maps depict a suite of forest attributes in 2001* and 2011 at 250 m by 250 m spatial resolution. The maps were produced using the k nearest neighbours method applied to MODIS imagery and trained from National Forest Inventory photo plot data. For detailed information about map production methods please refer to Beaudoin et al. (2018) "Tracking forest attributes across Canada between 2001 and 2011 using the k nearest neighbours mapping approach applied to MODIS imagery." Canadian Journal of Forest Research 48, 85-93. https://cfs.nrcan.gc.ca/publications?id=38979 The map datasets may be downloaded from https://nfi.nfis.org/downloads/nfi_knn2011.zip or https://open.canada.ca/data/en/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 * Note: the forest composition (leading tree genus) map depicts forest attributes in 2001. How can this data be used? The resolution and accuracy of these map products are best suited for strategic-level forest reporting and informing policy and decision making at regional to national scales. As these maps also offer a coherent set of quantitative values for a large suite of forest attributes, they can be used as baseline information for modelling and in calculations such as merchantable forest volume or percentage of tree species. It is also possible to overlay these maps with other maps produced on the same pixel grid to make assessments of disturbance impacts, such as fire and harvests.
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The Pan-Canadian Wind Integration Study (PCWIS), completed in 2016, assessed the operational and economic implications of integrating large amounts of wind energy into the Canadian electricity system. The PCWIS study generated a significant amount of high-resolution modelled wind data at many locations across Canada. This dataset contains over 54,000 “cells”, with each cell representing one node on a 2×2 km grid. Each cell has an associated time history of three years of modelled wind data, from 2008 to 2010, at 10-minute intervals. The interactive map allows a user to readily visualize the geographic distribution of Canada’s wind resources, as well as to quickly estimate the strength of the wind resource at a particular location.