Starting in July 2018, ground-based air measurements of pollutants were made at Pond Inlet on the balcony of the Environment Canada building, with an integrated air quality package (Airpointer, recordum Messtechnik GmbH). Pollutants monitored included NOx, O3, SO2, and PM2.5 mass concentration. This package also included a weather station to measure wind direction and speed, temperature, relative humidity, and pressure (Model WXT520, Vaisala). All data were reported with a 1-minute resolution.

Seagrasses support multiple key ecosystem functions (e.g., sediment stabilization, carbon storage, nursery habitat) in nearshore environments across all three Canadian coastlines. Eelgrass (Zostera marina) is a seagrass species that has been designated as an Ecologically Significant Species (ESS) and is the most widely distributed and abundant seagrass in Canada. Given the considerable conservation and management interest in eelgrass habitats, large-scale data aggregation efforts have been initiated to generate comprehensive distribution maps of eelgrass coverage in Canadian coastal waters. However, extensive portions of the Newfoundland coastline have not yet been surveyed for the presence of eelgrass. We combine spatial data layers describing shoreline characteristics, relative exposure index (REI), depth, and freshwater inputs to delineate areas potentially suitable for eelgrass growth in Newfoundland. We determined that many nearshore environments could potentially support eelgrass habitats but confirming eelgrass presence will require further validation and ground-truthing. Incorporating distribution models that use environmental covariates to estimate probabilities of occurrence in nearshore areas could help to strengthen these predictions. Mapping eelgrass distributions provides baseline data essential to eelgrass monitoring and implementation of coastal marine conservation, informing emergency response, and is particularly important considering the consequences associated with the potential loss of ecosystem functions in the event of eelgrass decline. King, B.G.C., Gullage, L., Butt, K., Warren, M., Allard, K., Gregory, R.S., and Byrne, M.A. 2026. Using shoreline characteristics, relative exposure, depth, and freshwater inputs as surrogate measures to identify areas potentially suitable for eelgrass (Zostera marina) in Newfoundland. Can. Tech. Rep. Fish. Aquat. Sci. 3737: vii + 22 p. https://doi.org/10.60825/7thp-4425

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.

Summary The Quebec region of the Department of Fisheries and Oceans (DFO) is responsible for the assessment of several fish and invertebrate stocks exploited in the Estuary and the northern Gulf of St. Lawrence. The commercial catches sampling program is one of the sources of information used to complete these assessments. The data collected by this program, at wharf or at sea, offers among other things the advantage of a relatively large spatio-temporal coverage and provides some of the necessary knowledge to assess the demography and the structure of the exploited populations. This program is implemented by specialized DFO staff whose main mandate is to collect biological data on groundfish, pelagic fish and marine invertebrate species that are commercially exploited in the various marine communities. Data This dataset on the iceland scallop (Chlamys islandica) includes the metadata, shell height and the number shells (empty or full) for all the specimens measured. This dataset covers the periods of 1985-2009 and 2011 to present. In order to protect the confidentiality of the sources, some informations (such as those concerning the vessel) have been excluded and others (such as the date of capture) have been simplified. Entries where there was only one vessel in a fishing area for a given year were also excluded. Further information including the fishing areas coordinates can be found by clicking on the «Atlantic and Arctic commercial fisheries» and «Fishing areas» links below.

The objective of this project was to gather data to develop a model of the food web of the lower trophic levels of the nearshore area of the Beaufort Sea. Sampling took place from 2005 to 2008 using the CCGS Nahidik. The multidisciplinary character of the Nahidik program produced measurements of biology/ecology (primary production, phytoplankton, zooplankton, benthos, fish), chemical and physical oceanography, contaminants, geology and hydro acoustics. The data were collected in July and August of each year. The Nahidik program provided data to provide a baseline for future studies as well as an information source for environmental assessment. This record contains water chemistry data collected as part of this project including suspended nitrogen, dissolved nitrogen, suspended phosphorus, dissolved phosphorus, dissolved organic carbon, suspended carbon, chlorophyll a, and suspended silicon.

This dataset contains the data reported in Wesley R Ogloff, Randi A Anderson, David J Yurkowski, Cassandra D Debets, W Gary Anderson, Steven H Ferguson, Spatiotemporal variation of ringed seal blubber cortisol levels in the Canadian Arctic, Journal of Mammalogy, 2022;, gyac047, https://doi.org/10.1093/jmammal/gyac047 Cite this data as: Wesley R Ogloff, Randi A Anderson, David J Yurkowski, Cassandra D Debets, W Gary Anderson, Steven H Ferguson. 2022 Spatiotemporal variation of ringed seal blubber cortisol levels in the Canadian Arctic. Arctic and Aquatic Research Division, Fisheries and Oceans Canada, Winnipeg, MB. https://open.canada.ca/data/en/dataset/e1c6b350-0159-11ed-8212-1860247f53e3

Summary The Quebec region of the Department of Fisheries and Oceans (DFO) is responsible for the assessment of several fish and invertebrate stocks exploited in the Estuary and the northern Gulf of St. Lawrence. The commercial catches sampling program is one of the sources of information used to complete these assessments. The data collected by this program, at wharf or at sea, offers among other things the advantage of a relatively large spatio-temporal coverage and provides some of the necessary knowledge to assess the demography and the structure of the exploited populations. This program is implemented by specialized DFO staff whose main mandate is to collect biological data on groundfish, pelagic fish and marine invertebrate species that are commercially exploited in the various marine communities. Data This dataset on Stimpson`s surfclam (Mactromeris polynyma) includes the metadata, sample weight, the shell width and the number of specimens measured. This dataset covers the periods of 1992, 1994-1998 and 2000-2021. In order to protect the confidentiality of the sources, some informations (such as those concerning the vessel) have been excluded and others (such as the date of capture) have been simplified. Entries where there was only one vessel in a fishing area for a given year were also excluded. Further information including the fishing areas coordinates can be found by clicking on the «Atlantic and Arctic commercial fisheries» and «Fishing areas» links below.

PURPOSE: To provide access to detailed stomach content data and associated metadata from Atlantic Bluefin Tuna sampled in the southern Gulf of St. Lawrence from 2018 to 2023. These data support fisheries science by contributing to analyses of predator–prey dynamics, diet composition, and ecosystem understanding, as well as informing stock assessment and fisheries management activities within Fisheries and Oceans Canada. DESCRIPTION: This dataset contains metadata and stomach content information collected from Atlantic Bluefin Tuna (ABFT) caught from mid-August to late September in the commercial fishery in the southern Gulf of St. Lawrence between 2018 and 2023. Stomach samples were primarily obtained from fish harvested near the eastern end of Prince Edward Island, with additional samples collected from the Miscou/Baie‑des‑Chaleurs area in 2018 and 2019. SAMPLING METHODS: Fish were measured to the nearest curved fork length (cm) and weighed to the nearest round weight (kg). Stomachs were obtained directly from harvesters or through a fish buyer and were stored at −20 ◦C before being processed in the laboratory. Stomachs identification numbers were cross-referenced with ABFT tag numbers recorded by fish provider in order to obtain logbook and port data (catch location, time, weight length, sex, gear, etc.) for each sample. Stomachs were thawed in the laboratory and the content was sorted and identified to the lowest possible taxonomic level. For each stomach, prey were weighed collectively as a taxonomic group and individually to the nearest 0.1 g. Dead bait used to capture ABFT, identified by cut marks, were recorded and weighed but excluded from the analysis. Live bait items cannot be identified from stomach content analyses. Only a few otoliths were found in 2018 and their degraded quality precluded performing ageing or species identification. Rare and small prey items such as algae and rocks were classified in the category “other”. Fish remains that could not be identified were classified in the category “Unidentified teleostei remains”. For 2019 to 2023, when stomach content items could not be visually identified and when tissue was available, tissue samples were collected and stored at −20 °C for DNA barcoding analysis. DNA extraction, mitochondrial cytochrome oxidase subunit 1 amplification, Sanger sequencing and species assignation were performed at the Plateforme d’Analyses Génomiques and Plateforme Bio-informatique of the Institut de Biologie Intégrative et des Systèmes (PAG-IBIS, Université Laval, Quebec city, QC, Canada, http://www.ibis.ulaval.ca/en/services-2/genomic-analysis-platform/). DNA was extracted from 20 mg of muscle tissue using the Omega Bio-tek E-Z-96 Tissue DNA Kit (Omega Bio-tek, Norcross GA, USA) following manufacturer instructions. The mitochondrial cytochrome oxidase subunit 1 region was amplified and sequenced as described in Hashemzadeh Segherloo et al., 2021). Sanger forward and reverse reads were analyzed independently using the Basic Local Alignment Search Tool against non-redundant sequences to identify the top hit for each sequence. When samples could not be identified by a top hit sequence they were classified as “unidentifiable fish”. Prey items that were successfully identified using DNA barcoding were incorporated into the stomach content analysis database and used in all subsequent diet analyses (abundance, occurrence and weight). The weight of the items used in the database was the weight of the remains as they were, and not reconstructed weights calculated for a live animal of the species identified by the barcoding. USE LIMITATION: To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

PURPOSE: To characterize food webs of freshwater fish communities using stable isotopes DESCRIPTION: Data set containing the carbon, nitrogen, and sulphur stable isotope ratios of fishes caught in the Northwest Miramichi River system PARAMETERS COLLECTED: Species gut contents (ecological); species isotopic signatures (ecological); points (spatial) PHYSICAL SAMPLE DETAILS: Powdered animal tissue SAMPLING METHODS: Invertebrates were sampled via kicknet and were collected 1-4 meters from the shore of each location in one-minute intervals with 5-10 intervals per site. Fish were captured using a variety of net types in order to maximize sampling breadth. Please see below for list of net types and mesh sizes: Large fyke (box, lead line, and cod = 5mm tight, 10mm loose); 6mm beach seine; Site 3: two small fyke nets (box, lead line, and cod = 17mm, 17mm and 10mm tight, and 32mm, 32mm, 20mm loose), one trap net (box = 47.6mm and lead line = 146mm) were used). USE LIMITATION: To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

PURPOSE: This study is part of a two-decade series of research aimed to provide a comprehensive synthesis of the effects of harvest and environmental change on fisheries in Great Bear Lake. The main objectives are to assess demographic traits and the current status of harvested species, with a focus on evaluating sustainable harvest levels of lake trout, a cold-adapted species with a relatively narrow thermal niche. As part of this research, trends in water quality and primary productivity are monitored to evaluate potential effects of change on fisheries. DESCRIPTION: Great Bear Lake, one of the largest lakes in North America, contains culturally and recreationally important fish species. Great Bear Lake is located in the sub-Arctic and Arctic Circle. As part of a two-decade series of research aimed to provide a comprehensive synthesis of the effects of harvest and environmental change on fisheries in Great Bear Lake, the main objectives of this study are to assess demographic traits and the current status of harvested species, with a focus on evaluating sustainable harvest levels of lake trout, a cold-adapted species with a relatively narrow thermal niche. As part of this research, trends in water quality and primary productivity are monitored to evaluate potential effects of change on fisheries. From 2021 to 2024, surface water temperature data was collected at depths of 0.1 to 1.0 meters using an RBR Maestro3 through partnered community-led and community/Fisheries and Oceans Canada/university partner collaborative sampling. The project has strong community involvement, including youth through the Guardian Program, to facilitate capacity building and community leadership in the long-term monitoring of Great Bear Lake fisheries and the aquatic ecosystem. This data is an extension of baseline data sets on water quality on the lake. These data will contribute to a better understanding cumulative impacts of climate change on the functioning of large northern lake ecosystems and provide a benchmark for monitoring further change. This data will be important for developing effective strategies for maintaining community-led aquatic monitoring and managing natural resources, particularly fish, which are expected to be increasingly important to communities with declines in other country foods such as caribou. We acknowledge the data were collected in the Sahtú Settlement Area and are made publicly available with the agreement of the Délı̨nę Renewable Resources Council (Délı̨nę Ɂehdzo Got’ı̨nę (Renewable Resources Council)). Collaborators include: the Community of Délı̨nę partners (data collection), Délı̨nę Renewable Resource Council, Sahtú Renewable Resource Board, and University of Manitoba. Community of Délı̨nę partners and field workers that participated in data collection include Chris Yukon, Archie Vital, Ted Mackienzo, Daniel Baton, Lloyd Baton, Simon Neyelle, and Stanley Ferdanan. Funding and logistical support was provided by: Northwest Territories Cumulative Impact Monitoring, Sahtú Renewable Resource Board, the Polar Continental Shelf Program and Fisheries and Oceans Canada.