Records of marine mammal sightings (N = 5,324) collected by ASOs and submitted to Fisheries and Oceans Canada (DFO) between 1979-2024, across three DFO regions: the Arctic, Newfoundland and Labrador, and the Maritimes. Methods for initial data compilation are provided in the associated technical report "Marine mammal records collected by the at-sea observer (ASO) program in Arctic, Newfoundland and Labrador, and Maritimes regions: a summary of challenges and opportunities for future research." Cite this data as: Feyrer, L.J., Colbourne, N., Lawson, J.W., Moors-Murphy, H.B., Ferguson, S. Dataset update to Marine mammal records collected by the At-Sea Observer program in Arctic, Newfoundland and Labrador and Maritimes regions. Published: February 2025. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

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 fish and marine mammal species whose DNA has been detected in water samples collected between 2019 and 2021 using the mitochondrial marker MiFish (12S).The surveys were carried out in the summer of 2019 (July 14-18) and (July 30 - August 5), in the fall of 2020 (October 27-28) and in the summer-fall of 2021 (May 31 - June 3 ) and (August 24-25) between Forestville and Godbout (Haute-Côte-Nord). Sampling was carried out between 1-50 meters depth in 91 stations, with 1 to 3 replicates per station. Two liters of water were filtered through a 1.2 µm fiberglass filter. DNA extractions were performed with the DNeasy Blood and Tissues or PowerWater extraction kit (Qiagen). Negative field, extraction and PCR controls were added at the different stages of the protocol. The libraries were prepared either by Génome Québec (2019, 2020) or by the Genomics Laboratory of the Maurice-Lamontagne Institute (2021), then sequenced on a NovaSeq 4000 PE250 system by Génome Québec. The bioinformatics analysis of the sequences obtained was carried out using an analysis pipeline developed in the genomics laboratory. A first step made it possible to obtain a table of molecular operational taxonomic units (MOTU) using the cutadapt software for the removal of the adapters and the R package DADA2 for the filtration, the fusion, removal of chimeras and compilation of data. The MOTUs table was then corrected using the R package metabaR to eliminate the tag-jumping and take contaminants into consideration. Samples showing a strong presence of contaminating MOTUs were removed from the dataset. The MOTUs were also filtered to remove all remaining adapter sequences and also retain only those of the expected size (around 170 bp). Finally, taxonomic assignments were made on the MOTUs using the BLAST+ program and the NCBI-nt database. Taxonomic levels (species, genus or family) were assigned using a best match method (Top hit), with a threshold of 95%. Only assignments at the level of fish and marine mammals were considered, and the taxa detected were compared to a list of regional species, and corrected if necessary. The species detections of the different replicas have been combined.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 were also published on SLGO platform : https://doi.org/10.26071/ogsl-2239bca5-c24a

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.

PURPOSE:In this study, we examined the structure and function of the Southampton Island marine food web across 149 species of benthic and pelagic invertebrates, fishes, marine mammals and seabirds collected from 2016 to 2019, to provide a baseline for future studies that aim to quantify temporal changes in food web structuring. More specifically,we used a multi-biomarker approach combining stable isotopes and HBIs to: (i) determine the vertical trophic structure of the marine food web, (ii) investigate the contribution of benthic and pelagic-derived prey to the higher trophic level species of the Arctic food web, and (iii) determine the role of ice algae and phytoplankton carbon source use across different trophic levels and compartments (pelagic and benthic). By shedding new light on the functioning of the Southampton Island food web and specifically how the contribution of ice algae and benthic habitat shapes its structure, these results will be relevant to adaptive management and conservation initiatives implemented in response to anthropogenic stressors and climate change. DESCRIPTION:Climate-driven alterations of the marine environment are most rapid in Arctic and subarctic regions, including Hudson Bay in northern Canada, where declining sea ice, warming surface waters and ocean acidification are occurring at alarming rates. These changes are altering primary production patterns that will ultimately cascade up through the food web. Here, we investigated (i) the vertical trophic structure of the Southampton Island marine ecosystem in northern Hudson Bay, (ii) the contribution of benthic and pelagic-derived prey to the higher trophic level species, and (iii) the relative contribution of ice algae and phytoplankton derived carbon in sustaining this ecosystem. For this purpose, we measured bulk stable carbon, nitrogen and sulfur isotope ratios as well as highly branched isoprenoids in samples belonging to 149 taxa, including invertebrates, fishes, seabirds and marine mammals. We found that the benthic invertebrates occupied 4 trophic levels and that the overall trophic system went up to an average trophic position of 4.8. The average δ34S signature of pelagic organisms indicated that they exploit both benthic and pelagic food sources, suggesting there are many interconnections between these compartments in this coastal area. The relatively high sympagic carbon dependence of Arctic marine mammals (53.3 ± 22.2 %) through their consumption of benthic invertebrate prey, confirms the important role of the benthic subweb for sustaining higher trophic level consumers in the coastal pelagic environment. Therefore, a potential decrease in the productivity of ice algae could lead to a profound alteration of the benthic food web and a cascading effect on this Arctic ecosystem.Collaborators:Centre for Earth Observation Science, University of Manitoba, Winnipeg, Manitoba, Canada - R´emi Amiraux, C.J. Mundy, Jens K. Ehn, Z.A. Kuzyk.Quebec-Ocean, Sentinel North and Takuvik, Biology Department, Laval University, Quebec, Quebec, Canada - Marie Pierrejean.Scottish Association for Marine Science, Oban, UK - Thomas A. Brown.Department of Natural Resource Sciences, McGill University, Ste. Anne de Bellevue, Quebec, Canada - Kyle H. Elliott.Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada - Steven H. Ferguson, Cory J.D. Matthews, Cortney A. Watt, David J. Yurkowski.School of the Environment, University of Windsor, Windsor, Ontario, Canada - Aaron T. Fisk.Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario, Canada - Grant Gilchrist.College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Fairbanks, AK, USA - Katrin Iken.Department of Earth Sciences, University of New Brunswick, Fredericton, NB, Canada - Audrey Limoges.Department of Integrative Biology, University of Windsor, Windsor, Ontario, Canada - Oliver P. Love, Wesley R. Ogloff.Department of Arctic Biology, The University Centre in Svalbard, Longyearbyen, Norway - Janne E. Søreide.

To identify areas of high residency, fine-scale tracking data from individual animals and coarser, short-term movement patterns of herds were analyzed. Individual radio-tracking was assessed from 2001 to 2005 and herd visual tracking was assessed from 1989 to 2008. Data was collected by two research teams: GREMM (Groupe de recherche et d’éducation sur les mammifères marins) and Fisheries and Océans Canada (DFO). Areas of high residency were determined using net displacement speed of herds and they were defined as adjacent cells where 50% of the herds travelled at or below a threshold speed.Areas of high residency do not represent the general distribution of the beluga whale and no association between these areas and specific biological functions could be established. The exact delimitation of these areas can change according to the definition criteria used in the analysis. Therefore, the marginal cells are not necessarily indicative of lower habitat quality.Data source:Lefebvre, S., Michaud, R., Lesage, V. and Berteaux, D. (2012). Identifying high residency areas of the threatened St. Lawrence beluga whale from fine-scale movements of individuals and coarse-scale movements of herds. Mar. Ecol. Prog. Ser. 450: 243–257.

Situated in the Gwich’in settlement Area (GSA), the Rat River is inhabited by anadromous Dolly Varden (Salvelinus malma malma) that are harvested by both Gwich’in and Inuvialuit beneficiaries. The harvest of Dolly Varden from the Rat River occurs during the summer at feeding areas along the coast (by the Inuvialuit) and during upstream migration in the Mackenzie Delta (by both Gwich’in and Inuvialuit). Dolly Varden stocks are co-managed under an Integrated Fisheries Management Plan (IFMP) whose signatories include Fisheries and Oceans Canada (DFO), Gwich'in Renewable Resources Board, Fisheries Joint Management Committee, and Parks Canada Agency. The Rat River Working Group, the co-management body that makes recommendations for harvest levels for Dolly Varden stocks in the GSA, has supported research activities that facilitate implementation of the IFMP, including studies to monitor harvest levels and assess population status. Population studies (e.g., abundance estimates, biological and genetic sampling) and coastal harvest monitoring activities allow for a comprehensive assessment of this stock. The data are used to inform co-management partners on the status of Dolly Varden from the Rat River.

Historical finds of Fenusa pumila

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.

Cold-water corals are conspicuous in the waters off Eastern Canada. Despite that, there are few DNA sequence records from specimens collected in the region available in GenBank, and not all species recorded in the region have sequence data regardless of geographic origin. This can limit the use of eDNA techniques to detect and identify corals. Our objective was to sequence and publish sequences for two octocoral DNA barcoding markers: CO1 and MutS. We sequenced and deposited 36 sequences to GenBank from 19 specimens representing three sea pen taxa (Octocorallia: Pennatuloidea): Distichoptilum gracile, Pennatula aculeata, and Protoptilum carpenteri. Identification of all specimens was confirmed by B. M. Neves before submission. Specimens and DNA tissues were donated to the Canadian Museum of Nature, where they are currently stored. This publication is part 1 of a series of GenBank submissions by our lab.Specimens were collected from across the Northwest Atlantic and originate from depths ranging between 200-1924 meters. Specimens were collected as part of research vessel multispecies trawl surveys or remotely operated vehicle (ROV ROPOS) surveys. DNA was isolated and purified using the QIAgen DNeasy Blood and Tissue kit, with an initial overnight incubation with Proteinase K. Two commonly used octocoral barcoding regions were amplified using previously described primers: 1) COII8068F (McFadden et al., 2004) and COIOCTR (France and Hoover, 2002) for the CO1 gene, and 2) ND42599F (France and Hoover, 2002) and mut3458R (Sánchez et al., 2003) for the MutS gene. Amplifications were conducted using 12.5 µl of Green DreamTaq Master Mix (Thermo Fisher Scientific), 1 µl of template DNA, 0.5 µl of each 10 µM forward and reverse primers, 0.5 µl of 10 µM reverse primer, and 10.5 µl of water. Thermocycling was run as follows: 3 min of initial denaturation at 95 °C, followed by 40 cycles at 95 °C for 30 s, 30 s at annealing temperature of 48 °C, then 65 s at an extension temperature of 72 °C, and a final elongation at 72 °C for 4 min. PCR products were cleaned using Agencourt AMPure XP Beads (Beckman Coulter) and sent to The Center for Advanced Genomics, Toronto, Canada for Sanger sequencing. Sequences were visualized and aligned using Geneious Prime 2022.0.2. Obtained sequences have been deposited in GenBank under accession numbers OQ569768- OQ569784 and OQ420359- OQ420377. This work was funded by Fisheries and Oceans Canada under an Enhanced Regional Capacity grant (2020-2021) and the Marine Conservation Targets (MCT) program (2021-2024), Newfoundland and Labrador Region.

Morrison Creek lamprey, Lampetra richardsoni variety marifuga are found only in Morrison Creek in Courtenay, BC. In 1995, this variety was designated Endangered by COSEWIC and is currently protected under the Species at Risk Act (SARA). For the years, 2011-2013 and 2015-2017, efforts were made to live trap Morrison Creek lamprey on and around spawning time. In 2014, DFO worked collaboratively with Hancock Forestry Management to assess the extent of the distribution of lamprey within the headwaters of Morrison creek on the land owned by the company. This dataset includes data for 2011 to 2017 inclusive.