Zooplankton samples were collected at Ocean Station "P" (50.0000, -145.0000) from 1956 to 1980, and were analyzed to various levels of taxonomic resolution over the years. Although summaries of these data have been previously published ((LeBrasseur 1965) and (Fulton 1978, 1983)) the detailed species data have never been published. This detailed dataset contains total zooplankton wet weights/m3 for the whole period of 1956 to 1980, as well as densities (numbers/m3) for five major taxa (copepods, chaetognaths, euphausiids, amphipods, and Aglantha) from 1964 to 1967, species identifications, counts and lengths for many samples collected between 1968 to 1980. The attached supporting document (Ocean Station "Papa" detailed zooplankton data: 1956 – 1980) contains information on the methods used to collect and process the data along with descriptions of a number of fairly minor points about the data that were not resolved. It also describes, in detail, the format of the original data files, the corrections/changes that were made to these files in creating this version, and how these errors affect what was published in Fulton (1983).The purpose of this record is to make the detailed data available to the scientific community in an electronic format and to provide a convenient reference for citing the detailed data. Waddell, Brenda J., and Skip McKinnell. 1995. Ocean Station "Papa" detailed zooplankton data:1956 - 1980. Can. Tech. Rep. Fish. Aquat. Sci. 2056: 21 p.

Since 1985, research surveys targeting scallops—primarily the sea scallop (Placopecten magellanicus) and, to a lesser extent, the Icelandic scallop (Chlamys islandica)—have been conducted by Fisheries and Oceans Canada (DFO) at one- or two-year intervals around the Magdalen Islands (fishing area 20A). The main objective of this survey is to assess the status of sea scallop stocks. The study area is situated south of the Magdalen Islands, where scallop beds are typically sampled at depths ranging from approximately 25 to 35 m. Sampling stations are randomly selected from a predetermined fixed grid, with sampling conducted along transects at these randomly assigned locations within the study area. Each station is sampled using a lined Digby scallop dredge (20 mm mesh size), towed for roughly 500 m across the seabed.This publication includes three files: the file biometriePetoncle_20, which contains detailed biometric data (species, size, weights and sex) from 1998 to 2024; the file taillePetoncle_20, which provides the size of the individuals sampled from 2009 to 2024; and the file traitPetoncle_20 which contains the abundances and densities per tow from 2009 to 2024. Data on abundances and densities per tow from 1998-2008 is available upon request.This dataset is updated every one to two years as data becomes available. A cleaning of aberrant data has been carried out. However, there is missing data in various columns of the dataset – use the data with caution. If you have any questions please contact DFO.DataManagementSAISB-GestionDonneesDAISS.MPO@dfo-mpo.gc.ca or the author. For certain time periods, associated species are identified and semi-quantitatively counted directly on the sorting table, and the results are presented in the following publications: - https://open.canada.ca/data/en/dataset/6529a4b0-f863-4568-ac71-1fa26cf68679- https://open.canada.ca/data/en/dataset/71732ad5-5c70-4dbf-916d-a94e1380c53b 

BiologicEcologic ISO Feature Dataset symbolization and publication. September 5, 2017.

As part of the International Polar Year (IPY) 2007'08 and 2008'09 activities, and related objectives of the Commission for the Geological Map of the World (CGMW), nations of the circumpolar Arctic have co-operated to produce a new bedrock geology map and related digital map database at a scale of 1:5 000 000. The map, released in north polar stereographic projection using the World Geodetic System (WGS) 84 datum, includes complete geological and physiographic coverage of all onshore and offshore bedrock areas north of latitude 60° north.

The blue whale (Balaenopterus musculus) is a wide-ranging cetacean that can be found in all oceans, inhabiting coastal and oceanic habitats. In the North Atlantic, little is known about blue whale distribution and genetic structure, and if whether animals found in Icelandic waters, the Azores, or Northwest Africa are part of the same population as those from the Northwest Atlantic. In the Northwest Atlantic, seasonal movements of blue whales and habitat use, including the location of breeding and wintering areas, are poorly understood.The behaviour of remotely-monitored animals can be inferred from a time series of location data. This is because animals tend to demonstrate stochasticity in their movement paths as a result of spatial variation in environmental characteristics, such as topography or prey density (Curio 1976; Gardner et al. 1989; Turchin 1991; Wiens et al. 1993). Predators are expected to decrease travel speed and/or increase turning frequency and turning angle when a suitable resource, e.g., food patch, is encountered (Turchin 1991), otherwise known as area-restricted search (ARS). In contrast, animals in transit or travelling tend to move at faster and more regular speeds, with infrequent and smaller turning angles (Kareiva and Odell 1987; Turchin 1998).Based on satellite telemetry to track the seasonal movements of 24 blue whales from eastern Canada in 2002 and from 2010 to 2015, it was possible to estimate trajectories and locations where ARS behaviour of blue whales was inferred at a 4h time interval.To assess blue whale movements and behavior, a Bayesian switching statespace model (SSSM) was applied to Argos-derived telemetry data (Jonsen et al. 2005; Jonsen et al. 2013). An SSSM essentially estimates animal location at fixed time intervals, movement parameters and behavioral patterns.Two important sources of uncertainty can be measured separately: estimation error resulting from inaccurate observations (Argos location error) and process variability linked to the stochasticity of the movement process (behavior mode estimation) (Jonsen et al. 2003; Patterson et al. 2008).The points visible on land are the result of errors in the Argos geographic position calculation. They have been deliberately left unchanged to assess the performance of the model, which was able to clean up some positions, but not all.Lesage, V., Gavrilchuk, K., Andrews, R.D., and Sears, R. 2016. Wintering areas, fall movements and foraging sites of blue whales satellite-tracked in the Western North Atlantic. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/078. v + 38 p.

Historical finds of Operophtera brumata

The St. Lawrence Estuary is known as a summer foraging area for several species of marine mammals, including several species of rorquals. Among these is the blue whale, which feeds almost exclusively on euphausiids. Therefore, the abundance, distribution and local density of krill should logically be a strong explanatory variable for the distribution of blue whales. However little is known about the spatial association of blue whales with the aggregation dynamics of krill in eastern Canada. Six years of acoustic surveys, conducted in August from 2009 to 2014, were undertaken to study the medium- and small-scale distribution of krill within the northwestern Gulf of St. Lawrence and estuary. The data shows a mosaic of the maximum annual density of arctic krill (T. raschii) made from these surveys.McQuinn, I.H., Gosselin, J.-F., Bourassa, M.-N., Mosnier, A., St-Pierre, J.-F., Plourde, S., Lesage, V., Raymond, A. 2016. The spatial association of blue whales (Balaenoptera musculus) with krill patches (Thysanoessa spp. and Meganyctiphanes norvegica) in the estuary and northwestern Gulf of St. Lawrence. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/104. iv + 19 p.

A research survey of scallops (mainly sea scallop Placopecten magellanicus, but also Icelandic Scallop Chlamys islandica) using a dredge was carried out by DFO (Fisheries and Oceans Canada) every 1 or 2 years since 1992 in the Magdalen Islands (fishing area 20). The main objective of this research survey was to assess Sea Scallop stocks. Another objective was to document taxa associated with scallop habitat according to a fixed random sampling plan. Occurrences by species (or taxon) are presented by station. The taxonomic and geographical validity of the data was checked and the World Register of Marine Species served as the taxonomic authority for naming all taxa recorded during the survey. Epibenthic invertebrates (mainly molluscs, echinoderms and crustaceans) as well as demersal fish were identified from the dredge catches. The current data starting in 2021 are available at the following link : https://open.canada.ca/data/en/dataset/6529a4b0-f863-4568-ac71-1fa26cf68679The study area is located south of the Magdalen Islands and the sampling of scallop beds is carried out at depths of 10 to 38 m, generally around 25 to 35 m. A random selection of sampling stations is carried out from a fixed station grid. Sampling is done along transects at these randomly drawn stations in the study area. Sampling is done with a lined Digby scallop dredge (20 mm mesh) over approximately 500 m along the seabed. The four baskets of the dredge are examined for all scallops. Next, a basket (the first on the starboard side) is sorted and examined for associated species. Most specimens are counted by taxon. The presence or relative abundance of undersized and numerous, or colonial, organisms is noted. Special cases are sometimes retained for taxonomic analysis, for example, ascidians (to monitor invasive species) and sponges (to document new species).

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.

The bedrock geologic units designate units of the same types of rock which composed the solid rock exposed at ground surface (as outcrop) or which underlies unconsolidated surficial sediments. This dataset represents a general description of the stratigraphy and geology, including geologic unit thickness, morphology, age and rank. It features a list of the geologic unit names and types of rock (lithology) in the hydrogeological unit, from a controlled vocabulary. While the preferred format to deliver this data is by using a shapefile and its linked attributes, this dataset can be delivered also by providing link to external data which should have at least the same properties or also by joining a georeferenced image of the map.