Species distribution models (SDMs) are tools that combine species observations of occurrence, abundance, or biomass with environmental variables to predict the distribution of a species in unsampled locations. To produce accurate predictions of occurrence, abundance or biomass distribution, a wide range of physical and/or biological variables is desirable. Such data is often collected over limited or irregular spatial scales, and require the application of geospatial techniques to produce continuous environmental surfaces that can be used for modelling at all spatial scales. Here we provide a review of 102 environmental data layers that were compiled for the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. Variables were obtained from a broad range of physical and biological data sources and spatially interpolated using geostatistical methods. For each variable we document the underlying data distribution, provide relevant diagnostics of the interpolation models and an assessment of model performance, and present the final standard error and interpolation surfaces. These layers have been archived in a common (raster) format at the Bedford Institute of Oceanography to facilitate future use. Based on the diagnostic summaries in this report, a subset of these variables has subsequently been used in species distribution models to predict the distribution of deep-water corals, sponges, and other significant benthic taxa in the Maritimes Region.Cite this data as: Beazley, Lindsay; Guijarro, Javier, Lirette; Camille; Wang, Zeliang; Kenchington, Ellen (2020). Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region. Published July 2023. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/34a917cb-a0e3-403c-91c7-af3dc20628b1

The Labour Force Distribution (LFD) maps are derived from the CanEcumene 2.0 Geodatabase using custom tabulations of census-based labour force data. These LFD maps were calculated for each of the five major natural resource sectors in Canada: Forestry, Fisheries, Agriculture, Minerals, and Petroleum and Coal. The measure used is the labour force of each sector as a proportion of the goods-producing sectors in the economy. Labour force proportions were first calculated at the individual community level, and then interpolated on a regional level using GIS (see Eddy et. al. 2020 for more detail). In effect, these maps show the strong importance of Canada’s natural resource sectors in various regions of the country. The darker the tone in each map indicates a region’s higher degree of dependency on a given sector for their economic livelihood.

Description:This dataset contains layers of predicted occurrence for 65 groundfish species as well as overall species richness (i.e., the total number of species present) in Canadian Pacific waters, and the median standard error per grid cell across all species. They cover all seafloor habitat depths between 10 and 1400 m that have a mean summer salinity above 28 PSU. Two layers are provided for each species: 1) predicted species occurrence (prob_occur) and 2) the probability that a grid cell is an occurrence hotspot for that species (hotspot_prob; defined as being in the lower of: 1) 0.8, or 2) the 80th percentile of the predicted probability of occurrence values across all grid cells that had a probability of occurrence greater than 0.05.). The first measure provides an overall prediction of the distribution of the species while the second metric identifies areas where that species is most likely to be found, accounting for uncertainty within our model. All layers are provided at a 1 km resolution.Methods:These layers were developed using a species distribution model described in Thompson et al. 2023. This model integrates data from three fisheries-independent surveys: the Fisheries and Oceans Canada (DFO) Groundfish Synoptic Bottom Trawl Surveys (Sinclair et al. 2003; Anderson et al. 2019), the DFO Groundfish Hard Bottom Longline Surveys (Lochead and Yamanaka 2006, 2007; Doherty et al. 2019), and the International Pacific Halibut Commission Fisheries Independent Setline Survey (IPHC 2021). Further details on the methods are found in the metadata PDF available with the dataset.Abstract from Thompson et al. 2023:Predictions of the distribution of groundfish species are needed to support ongoing marine spatial planning initiatives in Canadian Pacific waters. Data to inform species distribution models are available from several fisheries-independent surveys. However, no single survey covers the entire region and different gear types are required to survey the range of habitats that are occupied by groundfish. Bottom trawl gear is used to sample soft bottom habitat, predominantly on the continental shelf and slope, whereas longline gear often focuses on nearshore and hardbottom habitats where trawling is not possible. Because data from these two gear types are not directly comparable, previous species distribution models in this region have been limited to using data from one survey at a time, restricting their spatial extent and usefulness at a regional scale. Here we demonstrate a method for integrating presence-absence data across surveys and gear types that allows us to predict the coastwide distributions of 66 groundfish species in British Columbia. Our model leverages the use of available data from multiple surveys to estimate how species respond to environmental gradients while accounting for differences in catchability by the different surveys. Overall, we find that this integrated method has two main benefits: 1) it increases the accuracy of predictions in data-limited surveys and regions while having negligible impacts on the accuracy when data are already sufficient to make predictions, 2) it reduces uncertainty, resulting in tighter confidence intervals on predicted species occurrences. These benefits are particularly relevant in areas of our coast where our understanding of habitat suitability is limited due to a lack of spatially comprehensive long-term groundfish research surveys.Data Sources:Research data was provided by Pacific Science’s Groundfish Data Unit for research surveys from the GFBio database between 2003 and 2020 for all species which had at least 150 observations, across all gear type and survey datasets available.Uncertainties:These are modeled results based on species observations at sea and their related environmental covariate predictions that may not always accurately reflect real-world groundfish distributions though methods that integrate different data types/sources have been demonstrated to improve model inference by increasing the accuracy of the predictions and reducing uncertainty.

This service shows the median total income of households in 2015 for Canada by 2016 census subdivision. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.Total income refers to the sum of certain incomes (in cash and, in some circumstances, in kind) of the statistical unit during a specified reference period. The median income of a specified group is the amount that divides the income distribution of that group into two halves. For additional information refer to 'Total income' in the 2016 Census Dictionary.For additional information refer to 'Total income' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.

This layer represents the seasonal distribution of the St. Lawrence Estuary beluga whale population (Delphinapterus leucas). Three groups are represented: females with calf, adult males and mixed sectors. Herd distribution was defined using Fisheries and Oceans Canada (DFO) published data about beluga whales (see references).Herd distribution areas are only valid during the summer, and the uses of these areas by the herds are unknown.Data source :Michaud, R. 1993. Distribution estivale du béluga du St-Laurent; synthèse 1986-1992. Can. Tech. Rep. Fish. Aquat. Sci. 1906: vi + 28 p.

YEC Power Distribution Lines depict Yukon Energy Corporation (YEC) primary distribution lines. These lines distribute lower voltage electrical power between Power Substations and consumers (e.g. communities, mines). This data was provided by YEC and will be updated when new primary distribution lines are constructed.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)

A spatial representation of the general distribution of wild mountain sheep (bighorn and thinhorn sheep) in British Columbia. Populations that extend into neighbouring provinces and states are also included. The distribution polygons are divided by species into bighorn and thinhorn sheep.

The Forest Reserve Range Distribution Units dataset represent the functional grazing management areas within the Rocky Mountains Forest Reserve. Boundaries of the allotments and/or distribution units may be defined by fencelines, height of land, natural boundaries, and/or a combination of these. This is currently the most accurate representation of the distribution unit boundary and is subject to change. In some cases these boundaries may extend beyond the boundary of the Rocky Mountains Forest Reserve. In these cases this is a representation of the management unit as a whole.

This layer represents the seasonal distribution of St. Lawrence Estuary beluga whale population (Delphinapterus leucas). Summer distribution is based on many surveys conducted between the end of August and early September. Fall and winter distributions are based on aerial surveys conducted during mid-October, November and from December to March 1989-1990. Spring distribution is based on anecdotal reports and two aerial surveys conducted in late April and early June 1990.Beluga whale seasonal distribution can change according to sea ice cover, predation risk and food availability. This layer represents the general seasonal distribution and does not account for the sexual segregation among males and females in the St. Lawrence Estuary.This layer do not represent the beluga's critical habitat. See the data layer “Beluga whale critical habitat in the Saguenay River and the St. Lawrence Estuary” (https://open.canada.ca/data/en/dataset/fdfef550-b94c-466c-9dcb-24c297c00e3e). Data source : Mosnier, A., Lesage, V., Gosselin, J.-F., Lemieux Lefebvre, S., Hammill, M. O., Doniol-Valcroze, T. 2010. Information relevant to the documentation of habitat use by St. Lawrence beluga (Delphinapterus leucas), and quantification of habitat quality. DFO Can. Sci. Advis. Sec., Res. Doc. 2009/098. iv + 35 p.

UTC - Utility and communication networks (utilitiesCommunication) Energy, water and waste systems, and communications infrastructure and services. For example, resources describing hydroelectricity; geothermal, solar, and nuclear sources of energy; water purification and distribution; sewage collection and disposal; electricity and gas distribution; data communication; telecommunication; radio; and communication networks.