The blue shark (Prionace glauca), is a species found in Atlantic Canadian waters which is commonly encountered in commercial and recreational fisheries. Pop-up Satellite Archival Tags (PSAT) and Smart Position and Temperature tag (SPOT) from Wildlife Computers were applied to blue sharks from 2004 to 2008 to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada on commercial and recreational vessels from mid-August to early October, but mostly in September. A variety of tag models were deployed: PAT 4 (n=16), Mk10 (N=28), and SPOT3 (N=2) and 39 of 46 tags reported. The blue sharks tagged ranged in size from 124 cm to 251 cm Fork Length (curved); 30 were female, 15 were male and 1 was unknown sex. Time at liberty ranged from 4 – 210 days and 16 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 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.

Historical finds of Operophtera brumata

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 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 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.

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 basking shark (Cetorhinus maximus), is a species found in Atlantic Canadian waters which is mostly encountered “basking” on the surface waters and sometimes caught accidentally in commercial fisheries. One Pop-up Satellite Archival Tag (PSAT Mk10) from Wildlife Computers was applied to a single female basking shark in September 2008 on a commercial vessel to collect data on depth (pressure), temperature and ambient light level (for position estimation). The basking shark was 610 cm Total Length (curved). The tag released on the pre-programmed date 125 days after deployment. 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 deployment 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

Considered the "king" of sea lions, the Steller sea lion (Eumetopias jubatus) is the biggest of all sea lions and enjoys a lifespan of up to thirty years. In Canada, the Steller can be spotted along the rocky coast of British Columbia. This hefty mammal usually travels alone or in a small group, but wisely, it joins others for protection during the mating and birthing season. Little is known about its oceanic lifestyle; however, the good news for this sea-loving mammal is that since the Steller sea lion first became protected in 1970, the size of the adult population has more than doubled. Recent trends in the abundance of Steller sea lions (Eumetopias jubatus) in British Columbia were assessed based on a series of thirteen province-wide aerial surveys conducted during the breeding season (27-June to 06-July) between 1971 and 2013.