Phytoplankton pigments, determined by high-performance liquid chromatography (HPLC) are measured seasonally along a 20-station transect in the Juan de Fuca / Strait of Georgia Basin. Sampling was initiated in 2004, discontinued in 2012 and restarted in 2015. In addition, occasional sampling is carried out at several locations and times in inland waters. For data inquiries please contact: Angelica Pena for data from 2004 to 2015 and Nina Nemcek for data from 2015 to present.

Information regarding processor facilities in British Columbia including location, company name and license tag information. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.

Part of the Nova Scotia Topographic database, the County Boundaries are a generalized cartographic representation of the County boundaries.

This product contains contiguously settled area (CSA) boundaries for a subset of Canadian population centres for 2010 and 2020. The CSA boundaries are derived from land cover data and represent the geographic extent of settled areas based on their physical footprint on the landscape. The boundaries can be used for reference, mapping and spatial analysis of settled areas and urban ecosystems. The CSA boundaries are created and maintained under the umbrella of the Census of Environment, and will support Statistics Canada’s ecosystem accounting efforts following the System of Environmental-Economic Accounting — Ecosystem Accounting (SEEA EA) framework. The primary purpose of the CSA boundaries is to represent the extent of the contiguous urban footprint and allow for the measurement of settled area expansion over time. They will also contribute to the urban and industrial ecosystem class in Statistics Canada’s ecosystem accounting efforts. The boundaries will be used for other types of urban ecosystem analyses, including measures of urban ecosystem condition and services. The CSA boundaries may also be used for urban thematic accounts or to inform where users of ecosystem services are located. Moving forward, CSA boundaries will be updated on an ongoing basis.

Consolidated Local Health Areas (CLHAs) Boundaries. B.C. Consolidated Local Health Areas (CLHAs) are a health geography standard that partitions the province into distinct areas that support coordination of specialized care between Health Authorities and Primary Care. The province is divided into five Health Authorities, which are subdivided into 41 Consolidated Local Health Areas (CLHAs), which are subdivided into 231 Community Health Service Areas (CHSAs). CLHAs encompass all of B.C., so the classification is exhaustive of all the land area in the province.

Appropriately responding to a marine pollution event, especially hydrocarbon spills, often requires detailed knowledge of local habitat and environmental features. Access to high resolution habitat profiles can support effective spill response plans, informing discussions on protection priorities or expediated remediation. However, marine habitat composition data for a given area is often lacking due to the high cost and effort of conducting such surveys across the vast shorelines of Canada. The purpose of this study was to develop methodologies for conducting rapid and affordable habitat compositions in the marine environment via drone aerial photography; an emerging technology for conducting high resolution surveys. We used the Musquash Marine Protected Area (MPA; Musquash, NB, Canada) as a model system as it contains a diverse range of habitat types, is a region of conservation concern in Atlantic Canada, and is in close proximity to oil and gas handling facilities and vessel traffic. The MPA consists of a tidal river that outflows into the Bay of Fundy. Using Geographic Information System (GIS) software, we subdivided the MPA into several transects (N =61) that were used to generate flight plans for a Remotely Piloted Aircraft System (RPAS; DJI Mavic 3 Enterprise, DJI ). The RPAS was flown (6 m s-1) at an altitude of 100m (Above ground level) taking images with side (70%) and front (80%) overlap. Resulting images were then compiled as an orthomosaic map using Pix4Dmatic software. These data will be used to inform marine spill response planning in the region, to support marine planning and conservation, and Marine Protected Area (MPA) monitoring efforts as well as develop further methodological approaches for conducting RPAS-based habitat surveys in other coastal systems within Atlantic Canada. Cite this data as: Lawrence MJ, Coates PJ, Matheson K, Hamer A. Characterisation of intertidal habitat types in the Musquash Marine Protected Area using aerial drone photography. Published November 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B.

This service shows the median total income of households in 2015 for Canada by 2016 census division.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 division” web service, accessible in the data resources section below.

Multi-model ensembles of surface wind speed based on projections from twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of surface wind speed (m/s) are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better-projected climate change information.

This dataset is derived from analyses of photo samples obtained by deploying drop camera photo (DCP) systems conducted during various research surveys in coastal areas of the north shore of the St. Lawrence Estuary and the Gulf between Portneuf-sur-Mer and Sept-Îles between June and October of 2019 to 2022. It contains 4866 species occurrence data of 109 different taxa for epibenthic invertebrates and submerged aquatic vegetation (including algae) at depths ranging from 0 to more than 50 meters. Additional information about this dataset is available in the “Method step description” section. The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems. Data acquired during the research surveys additionally include: 1) fish and invertebrate species occurrence data derived from analyses of video samples collected using a stereoscopic baited remote underwater camera video systems (stereo-BRUVs) 2) fish and invertebrates catch data from beam trawl sampling (occurrence and catch weights by species), 3) substrate classification based on drop camera samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The datasets of the first two elements will also be available as independent datasets on the OBIS/GBIF portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux. The elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary and Gulf between Portneuf-sur-Mer and Sept-Îles (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as drop camera photo (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs). The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments. Method Step Description: 1. Acquisition of photo samples in sequence: The drop camera photo (DCP) system used to sample underwater pictures is a stainless steel frame in the shape of a triangular prism of 50 cm wide, 100 cm long and 76 cm high at the level of the central eyelet. The sampling area is a quadrat of 0.25 m2 (interior dimensions of 50 cm by 50 cm). The system consists of two GoPro Hero 5 cameras (4000 × 3000 pixels) and two 8000 lumens dive lights (Big Blue VL8000). The first camera captures the elements located in the quadrat when viewed from above. The second camera offers an oblique view facilitating the evaluation of the elements present in the quadrat. At all sampling stations, five to nine system deployments (replicas) capturing photos every 10 seconds for 60 to 120 seconds were performed. Surveys took place between : June 28th to July 5th 2019 July 13th to July 20th 2019 September 30th to October 9th 2019 August 10th to August 20th 2020 October 1st to October 10th 2020 April 22nd to May 5th 2021 July 27th to August 10th 2021 October 15th to October 24th 2021 June 24th to Jully 5th 2022 August 15th to August 26th 2022 2. Image analysis: A photo image analysis method with sequence (moving images) was used for the occurrence data extraction and organism counts; measurements were taken to obtain vegetation cover percentages and substrate analyzes were also carried out. Analyzes were performed with the open-source Fiji software from ImageJ. A quality/visibility rating was assigned to the analyzed image sequences. 3. Taxonomic approach: Epibenthic organisms were identified at the lowest possible taxonomic rank. A morphotype approach has been systematically used (during annotations) for the identification of sponges, hydrozoans and bryozoans, and occasionally for other organisms such as algae. Species codes were also used to distinguish certain species that could not be identified at the time of the annotations (see verbatim Identification). To eliminate observer bias, the same person analyzed all images used in this database. The organisms were identified from underwater images using a combination of identification guides and scientific papers. 4. Open nomenclature: The concept of open nomenclature has been integrated into occurrence data to support taxonomic identifications with their level of certainty, as recommended by Horton et al., 2021. The abbreviation stet. (stetit) was used when the decision not to go lower was made but an identification might be possible, whereas indet (Indeterminabilis) was used when a lower level identification was considered uncertain or impossible (see identificationqualifier). In addition, the abbreviation Confer (cf.) was used and integrated into the data tables (see occurrenceRemarks) in order to link identifications that could potentially and/or possibly be associated. 5. Remarks: Several remarks have also been incorporated (see organismRemarks, identificationRemarks and taxonRemarks), and are intended to provide additional information that may be useful to some data users; Please note that these sections could be modified or improved. 6. Quality control: The taxonomic identifications were verified through a validation process, in collaboration with various expert taxonomists. All scientific names have been checked against the World Register of Marine Species (WoRMS) to match currently recognized standards. The WoRMS match was placed in the taxonID field of the instance file. Data quality control was performed using Robistools and worms packages. All sample locations were plotted on a map for visual verification that the latitude and longitude coordinates were within the described sample area. 7. Data sharing: Only metadata and biodiversity occurrence data are shared in this dataset. The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event" file includes generic event information, including date and location. The "occurrence" file includes the original identifiers of the observed organisms, identification comments and their taxonomy. A data dictionary is also provided to explain the fields used. For access to other data or images, contact David Lévesque. For more details about the project and the methodology, a technical report (Scallon-Chouinard et al., 2022) including sampling methods with drop camera photo systems (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs) is currently available online (https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/41081225.pdf); another technical report detailing photo and video image analysis methods will also be available. This project was funded by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan.

The national agricultural ecumene includes all dissemination areas with 'significant' agricultural activity. Agricultural indicators, such as the ratio of agricultural land on census farms relative to total land area, and total economic value of agricultural production, are used. Regional variations are also taken into account. The ecumene is generalized for small-scale mapping. A new version of the agricultural ecumene is generated every census years (in vector format) since 1986. This file was produced by Statistics Canada, Agriculture Division, Ottawa.