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 for the year 2021 and 2022 are presented by species (or taxon) by station. Starting in 2021, catches were weighed, and specimens photographed, with information available upon request. 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 historical dataset is available at the following link : https://open.canada.ca/data/en/dataset/71732ad5-5c70-4dbf-916d-a94e1380c53bThe study area is located south of the Magdalen Islands and the sampling of scallop beds is carried out at depths of 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, and starting in 2022, also for all fishes. One basket (first on the starboard side) is sorted and examined for associated species. Most specimens are counted by taxa. Those that are too small and numerous, or colonial, are noted for presence or relative abundance. Special cases are occasionally conserved for taxonomic analysis, for example, ascidians (to monitor for invasive species) and sponges (to document new species). The availability of photos and some conserved specimens enables future review. Changes are anticipated in the identifications, notably for Bryozoan, Hydrozoa, and Porifera, that are currently the focus of research efforts.

The white shark (Carcharodon carcharias), is a species found in Atlantic Canadian waters which is encountered in commercial and recreational fisheries. Pop-up Satellite Archival Tags (PSAT) from Wildlife Computers were applied to white sharks from 2016 to the present to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada and the United States (Cape Cod and South Carolina) on scientific charters, typically in summer. Tag models deployed included: Mk10 (N=1), and MiniPAT (N=29) and 22 of 27 tags reported with 3 still at liberty. One individual shark returned to the location of tagging 1 year later and the physical tag was recovered. Another tag was recovered 5 years after deployment. White sharks tagged ranged in size from 259 cm to 459 cm Total Length (curved) estimated; 15 were female, 13 were male, and 2 were of unknown sex. Time at liberty ranged from 48 – 377 days and to date, only 3 tags remained on the shark for the programmed duration. Tagging of white sharks is an ongoing study and data will be updated here when it becomes available. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

The mako shark (Isurus oxyrinchus), is a species found in Atlantic Canadian waters which is encountered in commercial and recreational fisheries. Pop-up Satellite Archival Tags (PSAT) from Wildlife Computers were applied to mako sharks from 2011 to 2013 to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada on commercial vessels, typically in summer and fall from July to October. Two types of tag models were deployed: Mk10 (N=28), and MiniPAT (N=9) and 28 of 37 tags reported (one female shark was recaptured). The mako sharks tagged ranged in size from 80 cm to 229 cm Fork Length (curved); 13 were female, 17 were male, and 7 were unknown sex. Time at liberty ranged from 0 – 185 days and 6 tags remained on for the programmed duration. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

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.

The greenland shark (Somniosus microcephalus), is a species found in Atlantic Canadian waters which is occasionally encountered in commercial fisheries. Pop-up Satellite Archival Tags (PSAT) from Wildlife Computers were applied to greenland sharks from 2006 to 2009 to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada on commercial vessels throughout the year and in Cumberland Sound (Pangirtung) on a scientific expedition in April 2008. A variety of tag models were deployed: PAT 4 (n=1) and Mk10 (N=15) and 14 of 16 tags reported. Greenland sharks tagged ranged in size from 250 cm to 549 cm Total Length (curved); 3 were female, 9 were male, and 4 were of unknown sex. Time at liberty ranged from 48 – 350 days and 9 tags remained on the sharks for the programmed duration. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

The Olympia oyster (Ostrea lurida Carpenter, 1864) is one of four species of oysters established in British Columbia (BC), Canada, and the only naturally occurring oyster in BC (Bourne 1997; Gillespie 1999, 2009). O. lurida reaches the northern limit of its range in the Central Coast of British Columbia at Gale Passage, Campbell Island, approximately 52°12’N, 128°24’W (Gillespie 2009).First Nations historically utilized Olympia oysters for food and their shells for ornamentation (Ellis and Swan 1981; Harbo 1997). European settlers harvested Olympia oysters commercially from the early 1800s until the early 1930s when stocks became depleted and the industry moved towards other larger, introduced oyster species (Bourne 1997; Quayle 1988). Since that time, Olympia oysters have likely maintained stable populations in BC, but have not recovered to abundance levels observed prior to the late 1800s (Gillespie 1999, 2009).Olympia oysters were designated a species of Special Concern by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) in 2000 and 2010 and listed under the Species at Risk Act (SARA) in 2003 (DFO 2009; COSEWIC 2011). A management plan was developed and posted to the SARA Public Registry in 2009 (DFO 2009). One of the objectives of this plan was to ensure maintenance of the relative abundance (density) of Olympia oyster at index sites. The plan also recommended development of a survey protocol for determining relative abundance (density) estimates. In response, a Canadian Science Advisory Secretariat (CSAS) Research Document was completed recommending a survey method for Olympia oysters (Norgard et al. 2010); a CSAS Science Advisory Report (DFO 2010) for selection of index sites was also completed.Thirteen index sites were chosen from a mixture of previously surveyed sites, and by random site selection. In 2014, a fourteenth site was added at Joes Bay in the Broken Group area in partnership with Parks Canada. The selected sites provided a representative sample of Olympia oyster populations in different geographic zones in the Pacific region and span the much of the range of Olympia oysters in BC. The number of sites was reduced to six in 2018 so that annual surveys could be completed to better understand population dynamics and identify long-term trends.

Historical finds of Coleophora serratella

Species characterization by environmental DNA (eDNA) is a method that allows the use of DNA released into the environment by organisms from various sources (secretions, faeces, gametes, tissues, etc.). It is a complementary tool to standard sampling methods for the identification of biodiversity. This project provides a list of invertebrates species whose DNA has been detected in water samples collected at 2018 using the marker COI.The surveys were carried out in the summer of 2018 from August 11 to 14, between Forestville and Godbout (Haute-Côte-Nord). Sampling was carried out between 9-52 meters depth in 40 stations with one sample par station. Two liters of water were filtered through a 1.2 µm fiberglass filter. DNA extractions were performed with the DNeasy Blood and Tissue extraction kit (Qiagen). Negative field, extraction and PCR controls were added at the different stages of the protocol. Libraries at the COI locus were prepared by Genome Quebec and sequenced on an Illumina MiSeq PE250 system. The bioinformatics analysis of the sequences obtained was carried out using an in-house analysis pipeline as reported in Bourret et al. 2022. A first step made it possible to obtain a molecular operational taxonomic unit table (MOTU) using the cutadapt software for the removal of the adapters and the DADA2 R package for the filtration, fusion, chimera removal and data compilation. The MOTUs table was subsequently corrected by taking into account the negative controls, where the number of observations in the latter was removed from the linked samples. Singleton MOTUs have also been removed. Finally, the taxonomic assignments were carried out on the MOTUs using the IDTAXA classifier (present in the DECIPHIER R package) using a training set trained on the COI reference bank for Golf St-Laurent (GSL-rl v1.0, https://github.com/GenomicsMLI-DFO/MLI_GSL-rl) and a threshold of 40. Detections with an “Unreliable due to gaps” category were reported at the genus level only.The file provided includes generic activity information, including site, station name, date, marker type, assignment types used for taxa identification, and a list of taxa or species. The list of taxa has been verified by a biodiversity expert from the Maurice-Lamontagne Institute.This project was funded by Fisheries and Oceans Canada's Coastal Environmental Baseline Data Program under the Oceans Protection Plan. This initiative aims to acquire baseline environmental data that contributes to the characterization of significant coastal areas and supports evidence-based assessments and management decisions to preserve marine ecosystems.Data are also available on SLGO platform : https://doi.org/10.26071/ogsl-cd4c205b-f63b

The porbeagle shark (Lamna nasus), is a species found in Atlantic Canadian waters which is encountered in commercial and recreational fisheries. Pop-up Satellite Archival Tags (PSAT) from Wildlife Computers were applied to porbeagle sharks from 2005 to 2021 to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada and the Faroe Islands on commercial, recreational and scientific charters, typically in summer and fall but some over winter when the porbeagle commercial fishery was active in Canada. A variety of tag models were deployed: PAT 4 (n=1), Mk10 (N=41), and MiniPAT (N=15) and 51 of 57 tags reported. One individual shark was recaptured and the physical tag was returned. The porbeagle sharks tagged ranged in size from 76 cm to 249 cm Fork Length (curved); 42 were female, 15 were male. Time at liberty ranged from 4 – 356 days and 14 tags remained on for the programmed duration. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

Marine classification schemes based on abiotic surrogates often inform regional marine conservation planning in lieu of detailed biological data. However, theses chemes may poorly represent ecologically relevant biological patterns required for effective design and management strategies. We used a community-level modeling approach to characterize and delineate representative mesoscale (tens to thousands of kilometers) assemblages of demersal fish and benthic invertebrates in the North-west Atlantic. Hierarchical clustering of species occurrence data from four regional annual multispecies trawl surveys revealed three to six groupings (predominant assemblage types) in each survey region, broadly associated with geomorphic and oceanographic features. Indicator analyses identified 3–34 emblematic taxa of each assemblage type. Random forest classifications accurately predicted assemblage dis-tributions from environmental covariates (AUC > 0.95) and identified thermal limits (annual minimum and maximum bottom temperatures) as important pre-dictors of distribution in each region. Using forecasted oceanographic conditions for the year 2075 and a regional classification model, we projected assemblage dis-tributions in the southernmost bioregion (Scotian Shelf-Bay of Fundy) under ahigh emissions climate scenario (RCP 8.5). Range expansions to the north eastare projected for assemblages associated with warmer and shallower waters of the Western Scotian Shelf over the 21st century as thermal habitat on the rela-tively cooler Eastern Scotian Shelf becomes more favorable. Community-level modeling provides a biotic-informed approach for identifying broadscale ecolog-ical structure required for the design and management of ecologically coherent, representative, well-connected networks of Marine Protected Areas. When com-bined with oceanographic forecasts, this modeling approach provides a spatial tool for assessing sensitivity and resilience to climate change, which can improve conservation planning, monitoring, and adaptive management.Cite this data as: O'Brien, J.M., Stanley, R.R.E., Jeffery, N.W., Heaslip, S.W., DiBacco, C., and Wang, Z. Demersal fish and benthic invertebrate assemblages in the Northwest Atlantic.Published: December 2024. Coastal Ecosystems Science Division, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS.https://open.canada.ca/data/en/dataset/14d55ea5-b17d-478c-b9ee-6a7c04439d2b