Rouyn-Noranda cycling network**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Bicycle path routes.attribute:Name - Name of the bike pathTypeLane - Type of bike path**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

A research survey on snow crab (Chionoecetes opilio) was conducted from July 1 to July 17, 2018 on the Lower North Shore of the Gulf of St. Lawrence between Havre-Saint-Pierre and Blanc-Sablon. The main objective of this survey was to assess the abundance of snow crab and benthic species associated with snow crab habitat. Only data for benthic species associated with snow crab habitat are presented in this dataset.Data were collected according to a fixed station sampling design consisting of 61 stations, between 46 and 230 meters depth. Specimens were collected using a beam trawl with a total width of 2.8 meters and a total height of 0.76 meters. The codend was lined with a 16 millimeter stretched mesh net in order to harvest the small individuals. The hauls were made at a target speed of 2 knots and a target duration of 10 minutes depending on seabed conditions. Start and end positions were recorded to calculate the distance traveled on each tow using the geosphere library in R. The average tow distance was approximately 25 m. The area covered at each tow was the product of the trawl opening and the distance traveled.The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "Activity_Information" file includes generic activity information, including date and location. The "occurrence_taxon" file includes the taxonomy of the species observed, identified to the species or lowest possible taxonomic level. To obtain the abundance and biomass assessment, contact Cedric Juillet (cedric.juillet@dfo-mpo.gc.ca).For quality controls, all taxonomic names were checked against the World Register of Marine Species (WoRMS) to match recognized standards. The WoRMS match was placed in the "ScientificIDname" field of the occurrence file. Special cases were noted in the "commentsIdentification" field and selected specimens were confirmed with field photos. Data quality checks were performed using the R obistools and Worms libraries. All sampling locations were spatially validated.

A research survey on snow crab (Chionoecetes opilio) was conducted from July 7 to July 26, 2019 in the Estuary St. Lawrence River between Forestville, Baie-Comeau and Matane. The main objective of this survey was to assess the abundance of snow crab and benthic species associated with snow crab habitat. Only data for benthic species associated with snow crab habitat are presented in this dataset.Data were collected according to a fixed station sampling design consisting of 66 stations, between 31 and 279 meters depth. Specimens were collected using a beam trawl with a total width of 2.8 meters and a total height of 0.76 meters. The codend was lined with a 16 millimeter stretched mesh net in order to harvest the small individuals. The hauls were made at a target speed of 2 knots and a target duration of 15 minutes. Start and end positions were recorded to calculate the distance traveled on each tow using the geosphere library in R. The average tow distance was approximately 25 m. The area covered at each tow was the product of the trawl opening and the distance traveled.The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "Activity_Information" file includes generic activity information, including date and location. The "occurrence_taxon" file includes the taxonomy of the species observed, identified to the species or lowest possible taxonomic level. To obtain the abundance and biomass assessment, contact Cedric Juillet (cedric.juillet@dfo-mpo.gc.ca).For quality controls, all taxonomic names were checked against the World Register of Marine Species (WoRMS) to match recognized standards. The WoRMS match was placed in the "ScientificnameID" field of the occurrence file. Data quality checks were performed using the R obistools and worrms libraries. All sampling locations were spatially validated.

This dataset contains two geotiff layers. The first layer (1) represents the coastwide distribution of Dungeness crab as predicted from a geostatistical model. The model predicts the mean coastwide probability of Dungeness crab detection using trap sampling gear. The second layer (2) represent the uncertainty in those predictions. Detailed descriptions of these data products can be found in Nephin et al. (2023) and the code used to produce them can be found at https://gitlab.com/dfo-msea/dungeness-sdm/.The objectives of this work was to model the habitat of Dungeness crab (_Metacarcinus magister_), a data-limited coastal marine species, to evaluate the efficacy of data integration when making predictions to geographic areas larger than the area covered by any one data source. In British Columbia, Dungeness crab are sampled regionally and sporadically with a variety of sampling gears and survey protocols, making them an ideal case study to investigate whether the integration of disparate surveys can improve habitat predictions. To that aim, we assemble data from dive, trawl, and baited-trap surveys to generate six candidate generalized linear mixed-effect models with spatial random fields. This dataset contains the mean (1) and difference (2) between the Survey-effect and Gear-effect model predictions.

A research survey on snow crab (Chionoecetes opilio) was conducted from May 2006 to May 2009 in the Bay of Ste. Marguerite near Sept-Îles, Quebec. The main objective of this survey was to assess the abundance of snow crab and benthic species associated with snow crab habitat. Only data for benthic species associated with snow crab habitat are presented in this dataset.Data were collected according to a fixed station sampling design consisting of 79 stations, between 7 to 198 meters depth. Specimens were collected using a beam trawl. The codend was lined with a small stretched mesh net in order to harvest the small individuals. The hauls were made at a target duration of 15 minutes. Start and end positions were recorded to calculate the distance traveled on each tow using the geosphere library in R. The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "Activity_Information" file includes generic activity information, including date and location. The "occurrence_taxon" file includes the taxonomy of the species observed, identified to the species or lowest possible taxonomic level. To obtain the abundance and biomass assessment, contact Bernard Sainte-Marie (Bernard.Sainte-Marie@dfo-mpo.gc.ca).For quality controls, all taxonomic names were checked against the World Register of Marine Species (WoRMS) to match recognized standards. The WoRMS match was placed in the "ScientificnameID" field of the occurrence file. Data quality checks were performed using the R obistools and worrms libraries. All sampling locations were spatially validated.

The Canadian Hydrospatial Network (CHN) is an analysis-ready geospatial network of features that help enable the modelling of surface water flow in Canada. The six main layers and feature types are: flowlines, waterbodies, catchments, catchment aggregates, work units, and hydro nodes. Where possible the CHN is derived from high resolution source data such as Light Detection and Ranging (LiDAR) derived Digital Elevation Models (DEMs) and aerial imagery, to name a few. If existing provincial or territorial hydrographic networks meet the standards, they are incorporated into the CHN, otherwise automatic extraction methods are used on the high-resolution source data. To provide full network connectivity, if neither of these methods is possible in a region, the NHN is converted into the CHN until higher-resolution source data is available.Additional value-added attributes are included in the CHN to aid modelling, such as stream order and reach slope. The CHN physical model and features are also closely aligned and harmonized with the USGS 3DHP hydrographic network, which aids trans-border modelling. Where possible geonames (i.e. toponyms) are also added.The CHN is produced and disseminated by hydrologically connected geographic areas called work units. Work units can contain just one watershed, several small adjacent watersheds outletting into a large body of water, or be one of many parts of a larger watershed. In all cases, the features of a work unit are hydrologically connected. This is a more natural approach to data delivery, in comparison to data that is split into tiles. A generalized work unit index file is provided in the downloads to help users decide which files to download.For more information on the CHN please visit the project webpage: https://natural-resources.canada.ca/canadian-hydrospatial-network

This data is from the Newfoundland and Labrador Region Multispecies Trawl survey, specific to Snow Crab from 2018-25, with only successful tows included in the database. Details of annual survey coverage and an overview of the survey program can be found in Rideout et al. (2025) and references therein. This trawl survey follows a depth-stratified random design, designated by type = 1 (Survey). From 2021-23, a comparative fishing program (i.e., direct side-by-side paired comparison between old and new vessels) was undertaken to determine differences in catchability due to vessel changes and associated modifications to the trawl gear with the retirement of the CCGS Alfred Needler and CCGS Teleost (called ‘old vessels’) and the introduction of the CCGS Capt. Jacques Cartier and CCGS John Cabot (called ‘new vessels’). During this period other set types are in the dataset (6 and 7) from paired tows and all station allocation may not have been stratified random. The DFO NL Region comparative fishing success varied by year, NAFO division, and vessel combinations and resulted in conversion factors to adjust the catches of Snow Crab in the old vessels time series into the same units as the new vessels. Methodologies and conversion factors are described in Wheeland et al. (2024), Trueman et al. (2025), Trueman et al. (2026), and Pantin et al. (in prep). Conversion factors have been applied to the numbers of Snow Crab caught, where conversion factors exist, and are in the converted_number column. An NA in the converted_number column indicates that conversion factors do not exist for this vessel/area combination and therefore direct comparisons cannot be made between old vessels and new vessels. Weights are those recorded at sea and do not have conversion factors applied. Analyses by the DFO NL Snow Crab group apply a length-weight relationship to the converted numbers to determine converted weights, which is not in this dataset. All reasonable attempts are made to standardize fishing time during trawl surveys, however there is always some variation in the actual time on bottom. The species weights and numbers in this dataset are not standardized for tow distance/duration. Spatial coverage of this survey has varied over time, therefore, not all divisions, or depths within divisions, are sampled every year or season. Biological measurements are described in Pantin et al. (2025). Tows that caught zero Snow Crab are denoted in the dataset by a ‘number’ of 0.References:McCallum, B. R., and S. J. Walsh. 1996. Groundfish survey trawls used at the Northwest Atlantic Fisheries Centre, 1971-present. NAFO Sci. Coun. Studies, 29: 93-104.Pantin, J., D. Mullowney, K. Baker, K. Lefort, W. Coffey, F. Cyr, H. Munro, and Koen-Alonso, M. 2025. An Assessment of Newfoundland and Labrador Snow Crab (Chionoecetes opilio) in 2023. DFO. Can. Sci. Advis. Sec. Res. Doc. 2025/080. iv + 152 p.Pantin, J., Charmley, K., Mullowney, D., Baker, K., Lefort, K., Coyne, J., Munro, H., and Koen-Alonso, M. In prep. An Assessment of Newfoundland and Labrador Snow Crab (Chionoecetes opilio) in 2024. DFO Can. Sci. Advis. Sec. Res. Doc. year/nnn.Rideout, R.M., Wheeland, L., Perreault, A., Regular, P., Skanes, K., Simms, L., and Makrides, J. 2025. Canadian (Newfoundland and Labrador Region) Multi-Species Research vessel Bottom Trawl Survey Report for Surveys Conducted in 2024. NAFO SCR Doc. 25/028: 1-68.Trueman, S., Wheeland, L., Benoît, H., Munro, H., Nguyen, T., Novaczek, E., Skanes, K., and Yin, Y. 2025. Results of Comparative Fishing Between the CCGS Teleost and CCGS Alfred Needler with the CCGS John Cabot and CCGS Capt. Jacques Cartier in the Newfoundland and Labrador Region in 2021 and 2022. DFO Can. Sci. Advis. Sec. Res. Doc. 2025/021. v + 237 p. Trueman, S., Wheeland, L., Pantin, J., Baker, K., and Mullowney, D. 2026. On the relative catchability of Snow Crab in the Newfoundland and Labrador Multispecies trawl surveys. DFO Can. Sci. Advis. Sec. Res. Doc. 2026/008. iv + 41 p. Wheeland, L., Skanes, K. and Trueman, S. 2024. Summary of Comparative Fishing Data Collected in Newfoundland & Labrador from 2021-2022. Can. Tech. Rep. Fish. Aquat. Sci. 3579: iv + 132 p.

The Canada Basemap Transportation (CBMT) is a raster tile service that provides spatial reference context with an emphasis on transportation networks across Canada. It is designed especially for use as a background layer in a web mapping application or geographic information system (GIS). Access: Access is free of charge under the terms of the Open Government Licence - Canada.Data Sources: Data for the CBMT is sourced from the following datasets:- Topographic data of Canada – CanVec Series- Official names from the Canadian Geographical Names Database (CGNDB).Projections:- Data is provided in the EPSG:3978 (NAD83 Canada Atlas Lambert) projected coordinate system.- Data is provided in the EPSG:3857 (WGS84 Pseudo-Mercator) projected coordinate system.Geographic Coverage: - The CBMT in the EPSG:3857 has complete coverage of the world, with full datasets in Canada and only partial data in other parts of the world including boundaries, Country Names, and major cities.- The CBMT in the EPSG:3978 covers the entire geographic area of Canada and some major transportation routes and cities in the northern States of the USA.Additional Versions: - The CBMT is available as a dynamic service (WMS) or a tiled service (ESRI REST and WMTS). - A geometry-only version (CBMT GEOM) and a text-only version (CBMT TXT) are available. - French versions of the basemap are accessible via the Carte de base du Canada - Transport (CBCT).

The Brier Island/Digby Neck area has been identified as an Ecologically and Biologically Significant Area (EBSA) by Fisheries and Oceans Canada and is one of four marine areas within the Bay of Fundy recognised by Parks Canada as of national significance for marine conservation planning. The area is representative of important outer Bay of Fundy features with significant marine mammal, bird, and benthic diversity including potentially important aggregations of sensitive benthic species such as horse mussel and sponge. Much of the information used for this recognition is now over 40 years old and should be re-validated using standardised georeferenced survey methods. As a first phase, a diver-based survey of the sublittoral habitats and associated species was conducted in August and September of 2017 for the Brier Island area. This report summarises the major sublittoral habitat types, species assemblages, and oceanographic conditions observed at 20 locations including Northwest and Southwest Ledges, Gull Rock, Peter’s Island, and Grand Passage. A total of 962 records were made of 178 taxa, consisting of 43 algae and 135 animals. Comparison with historical records largely confirmed the continued presence of unique habitats and species assemblages for which this area was initially recognised as an EBSA. Differences in species richness observed for cryptic and less known taxonomic groups such as sponges and bryozoans were attributable to changes in survey methods and knowledge. Based on these findings, additional surveys of inshore and offshore Brier Island using more quantitative methods developed for other Bay of Fundy EBSAs would further support regional MPA network planning and provide relative scales of species diversity and habitat coverage for this area.