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.

Forest Elevation(Ht) Covariance 2015Coefficient of variation of first returns height (%). Represents the variability in canopy heights relative to the mean canopy height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

This dataset contains the data reported in Wesley R Ogloff, Randi A Anderson, David J Yurkowski, Cassandra D Debets, W Gary Anderson, Steven H Ferguson, Spatiotemporal variation of ringed seal blubber cortisol levels in the Canadian Arctic, Journal of Mammalogy, 2022;, gyac047, https://doi.org/10.1093/jmammal/gyac047Cite this data as:Wesley R Ogloff, Randi A Anderson, David J Yurkowski, Cassandra D Debets, W Gary Anderson, Steven H Ferguson. 2022 Spatiotemporal variation of ringed seal blubber cortisol levels in the Canadian Arctic. Arctic and Aquatic Research Division, Fisheries and Oceans Canada, Winnipeg, MB. https://open.canada.ca/data/en/dataset/e1c6b350-0159-11ed-8212-1860247f53e3

An ecoregion is an area with major physiographic and minor macroclimatic or oceanographic variation. There are 43 ecoregion in British Columbia of which 39 are terrestrial. Ecodivsions are meant to be mapped at 1:500,000 for regional strategic planning

PURPOSE:Ringed seals (Pusa hispida) rely on sea ice as habitat throughout their life history and inhabit a broad latitudinal range with diverse sea-ice conditions. Anthropogenic climate warming is triggering poleward species redistributions, highlighting the importance of understanding how species distributions and abundance vary along latitudinal gradients. Using ringed seals as a model species, the purpose was to estimate density via aerial surveys along a latitudinal gradient in the eastern Canadian Arctic to investigate latitudinal trends in the ringed seals response to regional variation in sea-ice conditions. DESCRIPTION:Ringed seals (Pusa hispida) rely on sea ice as habitat throughout their life history and inhabit a broad latitudinal range with diverse sea-ice conditions, making them a model species to study patterns in density along a spatial-environmental gradient. We estimated the density of ringed seals from systematic aerial surveys along a latitudinal gradient in the eastern Canadian Arctic to investigate latitudinal trends in the ringed seals response to regional variation in sea-ice conditions. Ringed seals exhibited similar densities at lower and intermediate latitudes, while higher latitudes displayed an order of magnitude lower ringed seal density. This shift is concurrent with the transition in ice conditions from predominantly first-year ice at lower latitudes to primarily multiyear ice at higher latitudes. These findings indicate that the variation in icescapes across the ringed seal’s vast range influences their density. The shift in sea-ice conditions may also have consequences for biological productivity that supports their diet. Our results highlight a likely non-uniform response of ringed seals to ongoing sea-ice recession across the Arctic.

To better understand patterns of temporal and spatial variation of fish assemblages in offshore waters of Lake Winnipeg (Manitoba, Canada), pelagic trawl tows were conducted at lakewide monitoring stations since 2002. Trawl samples collected during spring, summer, and fall from the south basin, channel, and north basin were used to study effects of season and geographic region within the lake on species biomass estimates.

The Coastal Infrastructure Vulnerability Index (CIVI) was jointly developed by DFO Science Branch, Small Craft Harbours (SCH) Program and the Economic Analysis and Statistics Directorate. The CIVI was designed with the intent of developing a climate change adaptation tool that would support management decisions regarding the long-term infrastructure planning for SCH sites.The CIVI provides a numerical indication of the relative vulnerability of small craft harbour sites to the effects of climate change and was designed with three component sub-indices: Environmental Exposure (natural forces), Infrastructure, and Socio-economic. The spatial component for the coastline was derived from the CanVec 1:50,000 hydrographic layer (https://open.canada.ca/data/en/dataset/9d96e8c9-22fe-4ad2-b5e8-94a6991b744b).This layer combines the 1:50,000 CanVec coastline of Canada with the following CIVI environmental exposure variables:- projected sea level rise (for the decades 2030, 2040,...2100) in meters- wave height (metres) and wind speed (metres/second)- change in sea ice coverage in Atlantic Canada from the 1970s to the 2000sSea level change:Data for relative sea level change (SLC) were derived from the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC 2014, AR5). The projected relative sea level change under the high emission scenario (RCP8.5) was calculated for all years between 2006 and 2100. Sea level change for the years 2030, 2040, 2050, 2060, 2070, 2080, 2090, and 2100 were used.Wind Speed and Wave HeightModelled hindcasts of yearly maximum wind speed (1990 - 2012) and wave height (1990- 2014) were used. This dataset was generated from IFREMER wave hindcasts using the WAVEWATCH III model with wind data from NCEP Climate Forecast System Reanalysis (CFSR) (Saha et al. 2010). Two high resolution (10 minute) grids of Atlantic and Pacific maximum modeled wind speeds and maximum significant wave height were used for southern Canadian coastal areas while a coarser (30 minute) worldwide grid was used for the Arctic areas. From these datasets the mean annual maximum wind speed over 23 years and the mean maximum significant wave height over 25 years were calculated.Change in sea ice coverage:Sea ice data from the Canadian Ice Service were acquired for Atlantic and Arctic Canada, representing percent ice coverage for each week over four decades (1970s, 1980s, 1990, 2000s). For each decade a single dataset was calculated to represent the sum of all weeks with ice coverage in excess of 50%, with a maximum possible score of 52 weeks for each decade. To measure change in ice duration, the summary mapsheet from the 2000s was subtracted from the 1970s summary mapsheet. The final dataset represents the change between the 1970s and 2000s in the number of weeks with ice concentrations greater than 50%. A positive number indicates a reduction in weeks of ice coverage, a negative number an increase in ice coverage.The data for individual small craft harbours included here contains predicted sea level change for the decades between 2030 and 2100, wave height, windspeed, change in sea ice coverage, population, and the final environmental exposure sub-index value (ESI). The population for each harbour is derived from the 2016 Census of Canada data for the Census subdivision (CSD) geographic unit.Reference:Relative sea-level projections for Canada based on the IPCC Fifth Assessment Report and the NAD83v70VG national crustal velocity modelhttps://doi.org/10.4095/327878 IPCC, 2014. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1132 pp.Cite this data as: Greenan B. and Greyson P. Coastal Environmental Exposure Layer. Published March 2022. Ocean Ecosystem Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

The Fish Habitat Management System for Yukon Placer Mining replaced the Yukon Place Authorization (YPA) in 15 Yukon watersheds on April 11, 2008. Founded on principles of adaptive management and incorporating a risk-based approach to decision-making, the system is intended to balance the objectives of a sustainable Yukon placer mining industry with the conservation and protection of fish and fish habitat supporting fisheries Adaptive management recognizes that the effectiveness of any management system is hampered by a degree of uncertainty and lack of knowledge. It seeks to improve the system by monitoring the effects of management actions, in order to learn from the results. The Adaptive Management Framework for Yukon placer mining is complemented by traditional knowledge and water quality objectives monitoring, aquatic health monitoring and economic health monitoring programs. The results should provide new information and a rational basis for making any adjustments required to achieve the two management objectives. The water quality objectives monitoring program is governed by the Water Quality Objectives Monitoring Protocol. The Protocol describes the locations, timing, frequency and methods employed during sampling, as well as the methods used to analyze sampling data. Precipitation data was collected from a variety of sources to assist in the interpretation of results. The water quality objectives monitoring program relies upon both continuous sampling and grab sampling. Continuous sampling is performed by automated instruments that pump water from the creek or river at a preset volume and at precise times each day. Grab samples are taken by personnel at a selected location, depth and time. Normally the quantity of water taken is sufficient for all the physical and chemical analyses that will be done on the sample. Grab sampling is also performed during sampling "blitzes", when single grab samples are collected from as many sites as possible within a short timeframe in order to get a snapshot of the water quality in a watershed over a 24 hour period.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)

This product provides population counts for 2001 and 2016 for 105 census subdivisions (CSDs) for which the forest sector is a major source of employment income—defined by Natural Resources Canada as 20% or more of total CSD income excluding government transfers. These files were produced by Statistics Canada, Environment, Energy and Transportation Statistics Division, 2018, special tabulation from the 2001 and 2016 Census of Population; Natural Resources Canada, Canadian Forest Services, Economic Analysis Division; Canada’s National Forest Inventory (NFI), 2016, Grouped kNN Map layers, http://tree.pfc.forestry.ca (accessed April 7, 2017). Data from the 2016 Census of Population were used to identify the 105 census subdivisions. Note that changes occur to the number and the boundaries of CSDs between censuses. Adjustments were made to CSD boundaries to account for changes.Some data were suppressed for data quality reasons or to meet the confidentiality requirements of the Statistics Act. Income data were available for 3,675 of 5,162 CSDs. This analysis may therefore underreport the total number of communities for which the forest sector is a major economic driver. Note that a decline in the percentage of forest sector income may be due to a decrease in forest sector income or an increase in income from other sources. The reference period for income data in the Census of Population is the calendar year prior to the census.The forest sector includes North American Industry Classification codes 113 – forestry and logging, 1153 – support activities for forestry and logging, 321 – wood product manufacturing and 322 – paper product manufacturing.

The atlas provides printable maps, Web Services and downloadable data files representing seabirds at-sea densities in eastern Canada.The information provided on the open data web site can be used to identify areas where seabirds at sea are found in eastern Canada. However, low survey effort or high variation in some areas introduces uncertainty in the density estimates provided. The data and maps found on the open data web site should therefore be interpreted with an understanding of this uncertainty.Data were collected using ships of opportunity surveys and therefore spatial and seasonal coverage varies considerably. Densities are computed using distance sampling to adjust for variation in detection rates among observers and survey conditions. Depending on conditions, seabirds can be difficult to identify to species level. Therefore, densities at higher taxonomic levels are provided. more details in the document: Atlas_SeabirdsAtSea-OiseauxMarinsEnMer.pdf.By clicking on "View on Map" you will visualize a example of the density measured for all species combined from April to July - 2006-2020. ESRI REST or WMS map services can be added to your web maps or opened directly in your desktop mapping applications. These are alternatives to downloading and provide densities for all taxonomical groups and species as well as survey effort.