PURPOSE: Establishing efficient, non-destructive sampling methods for clam population assessments. DESCRIPTION: In the Gulf of St. Lawrence (GSL) Management Region, clam assessments are uncommon due to limited resources and the labour-intensive nature of sampling clam beds. Furthermore, clam assessments typically rely on destructive sampling that disturbs sediment and removes animals from their habitat. Establishing efficient, non-destructive sampling methods for clam population assessments can reduce the impact of scientific sampling on these habitats and provide for more efficient monitoring. In this study, we tested the idea that visually observing siphon holes on the sediment surface could predict the presence, number, and size of soft-shell clams across different sites in the southern GSL. Siphon holes reasonably predicted the presence, number, and size/biomass of soft-shell clams in most, but not all, sites. Thus, in many habitats in the GSL, siphon holes can be used for population assessments, providing a powerful tool to enhance Science advice to fisheries managers. Data was collected at the following sites: * Maisonnette, Parc Maisonnette, Maisonnette, New Brunswick, Canada * Kouchibouguac, Loggiecroft wharf, Kouchibouguac National Park, New Brunswick, Canada * Shemogue, Amos Point Road, Little Shemogue, New Brunswick, Canada * Powell's Cove, Powell's Point Provincial Park, Little Harbour, Nova Scotia, Canada PARAMETERS COLLECTED: - Clam abundance - Clam biomass (total sample) - Clam size (length, weight) - Siphon hole abundance - Siphon hole size - Siphon hole characterization (i.e., identification of actual clam based on shape) - Seawater temperature - Sediment grain size - Sediment organic content (%) - Sediment relative moisture content (%) NOTES ON QUALITY CONTROL: Original data entry by Jillian Hunt and/or Isabelle Brennan. Data checked and validated prior to analysis by Jeff Clements. Data further checked and validated prior to publication by Amélie Robichaud. PHYSICAL SAMPLE DETAILS: No physical samples retained. - Clam samples returned back to original habitat after measuring and weighing in the field. - Sediment core samples stored in walk-in freezer and discarded after processing and analysis. SAMPLING METHODS: i. Identifying, counting, weighing, and measuring (with calipers) clams ii. Identifying, counting, and measuring (with calipers) clam siphon holes iii. Seawater temperature monitoring via data loggers iv. Sediment grain size, organic content, and moisture content analysis USE LIMITATION: To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

These data sets provide information pertaining to abundant taxa including bottom-dwelling shrimp and fish along trawling and trapping transects in Simoom Sound at November, 2000, and February, 2001. Data sets were compiled and formatted by Meagan Mak. Abstract from report: This study is a component of a larger project designed to compare the effects of shrimp trawling and trapping gear on shrimp, fish and the benthic habitat of Simoom Sound located in Broughton Archipelago, British Columbia, Canada. Otter-trawling, beam-trawling, and trapping took place in three distinct experiment blocks of the central seabed of the Sound. In turn, each block consisted of replicate transects, where a towed submersible video-camera surveyed shrimp and fish before and after trawling. Video surveys were deployed only before trapping. From the video surveys, we determined the abundance of common shrimp taxa and fish.

These data sets provide information pertaining to shrimp and bycatch estimates associated with otter-trawling and trapping (November, 2000) and beam-trawling (February, 2001) in Simoom Sound. Data sets were compiled and formatted by Meagan Mak. Abstract from report: As part of a project investigating possible modification of marine ecosystems by shrimp trawling and trapping, we obtained information on catches offish, shrimp, prawns , and bycatch organisms as well as weight, sex ratios , egg location and colIateral damage to several species of pandalids and eualids. Focusing on the humpback shrimp (Pandalus hypsinotus), we assessed damage to the rostrum, carapace, abdomen, and tail fan on specimens caught by beam trawling, otter trawling, and trapping. Data are given from a preliminary study conducted in Northumberland Channel in June 2000 and more comprehensive sampling from Simoom Sound in November 2000 and February 2001.

This dataset contains observations of species occurrences from seafloor imagery collected by the autonomous underwater vehicle (AUV) during the 2012 Expedition to Cobb Seamount. The National Oceanographic and Atmospheric Administration-operated SeaBED-class AUV which collected photographic images from 4 transects ranging from 436 m to 1154 m in depth.

These data sets provide information pertaining to shrimp and bycatch estimates associated with beam-trawling and trapping (2001-2002) in Clio Channel. Data sets were compiled and formatted by Meagan Mak. Abstract from report: As part of a project investigating possible modification of marine ecosystems by shrimp trawling and trapping, we enumerated beam trawl and prawn trap catches at two locations in Clio Channel, south -central coast of British Columbia. Beam trawl surveys were conducted in Bones Bay and Turnour Bay during October 2001 and January 2002, respectively, and a prawn trap survey was conducted in Turnour Bay during March 2002. Catch data from the two gear types are presented.

Fisheries and Oceans Canada (DFO) conducts an annual summer multidisciplinary scientific survey with a bottom trawl in the Estuary and the northern Gulf of St. Lawrence since 1984. Over the years, this survey has been conducted on four vessels: the MV Lady Hammond (1984-1990), the CCGS Alfred Needler (1990-2005), the CCGS Teleost (2004-2021) and the CCGS Cabot (2022-current). It is important to note that the objectives, the methods used and the identification of the species during these surveys have improved over time in response to DFO requests and mandates. The data are therefore not directly comparable between these surveys. The specificities of the missions onboard the MV Lady Hammond are described below. Objectives: 1. Assess groundfish populations abundance and condition 2. Assess environmental conditions 3. Conduct a biodiversity inventory of benthic and demersal megafauna 4. Monitor the pelagic ecosystem 5. Collect samples for various research projects Survey description The survey covers the northern Gulf of St. Lawrence, that is the divisions 4R, 4S and the northern part of division 4T of the Northwest Atlantic Fisheries Organization (NAFO). A stratified random sampling strategy is used for this survey and the fishing gear used on the MV Lady Hammond is a bottom trawl Western IIA. Standard trawling tows last 30 minutes, starting from the time the trawl touches the sea floor. Towing speed is 3.5 knots. Data For each fishing tow, the catch is sorted and weighed by taxa; individuals are counted and biological data are collected on a sub-sample. For fish, crab and squid, size and weight are measured by individual and, for some species, sex, gonad maturity, and the weight of certain organs (stomach, liver, gonads) are also evaluated. The soft rays of the anal fin are counted for redfish and otoliths are collected for redfish and Atlantic cod. Invertebrates are weighted and counted (no individual measurements). The biological data are divided into 4 files: a “Metadata” file containing set information, a “Catches” file containing catches per set for fish taxa, a “Carbio” file containing biological and morphometric measurements per individual and a “Freql” file containing the length frequency of fish. It's important to note that this is raw data. Only sets considered successful are retained. In each set, all species are kept, with a few exceptions. For more information please contact the data management team (gddaiss-dmsaisb@dfo-mpo.gc.ca).

PURPOSE: Understanding and predicting species range shifts is crucial for conservation amid global warming. This study analyzes life-history traits of four seal species (ringed (Pusa hispida Schreber, 1775), bearded (Erignathus barbatus Pallas, 1811), harp (Pagophilus groenlandicus Erxleben, 1777), and harbour (Phoca vitulina Linnaeus, 1758) seals) in the Canadian Arctic using data from Inuit subsistence harvests. Bearded seals are largest, followed by harp seals, harbour seals, and ringed seals. Seasonal blubber depth patterns show minimal variation in bearded seals, whereas harbour and ringed seals accumulate fat in open-water seasons and use it during ice-covered seasons. Endemic Arctic seals (ringed and bearded) exhibit greater longevity and determinate body growth, reaching maximum size by 5 years, while harbour and harp seals grow indeterminately, physically maturing around 10-15 years. Age of maturation varies, with ringed and harbour seals being more sensitive to environmental fluctuations. Most bearded seals reproduce successfully each year, while ringed seals exhibit more variability in their annual reproductive success. Analysis of isoprenoid lipids in liver tissue indicates that ringed and bearded seals rely on ice-algal production, whereas harp and harbour seals depend on open-water phytoplankton production. Bearded seals appear more specialized and potentially face less competition, while harp seals may adapt better to changing habitats. Despite expected range shifts to higher latitudes, all species exhibit tradeoffs, complicating predictions for the evolving Arctic environment. DESCRIPTION: This dataset contains the data reported in Steven H. Ferguson, Jeff W. Higdon, Brent G. Young, Stephen D. Petersen, Cody G. Carlyle, Ellen V. Lea, Caroline C. Sauvé, Doreen Kohlbach, Aaron T. Fisk, Gregory W. Thiemann, Katie R. N. Florko, Derek C. G. Muir, Charmain D. Hamilton, Magali Houde, Enooyaq Sudlovenick, and David J. Yurkowski. 2024. A comparative analysis of life-history features and adaptive strategies of Arctic and subarctic seal species - who will win the climate change challenge? Canadian Journal of Zoology 2024-0093.R1 The data set includes species, location, harvest date, sex, age, standard length, girth, fat depth, teste size, parity status, pregnancy status, corpora lutea (n), corpus albicans (n), follicles (n). This dataset includes raw, unfiltered, and unprocessed historical data provided by harvesters that have not been screened for outliers. Individual users should screen the data for their specific use. Cite these data as: Steven H. Ferguson, Jeff W. Higdon, Brent G. Young, Stephen D. Petersen, Cody G. Carlyle, Ellen V. Lea, Caroline C. Sauvé, Doreen Kohlbach, Aaron T. Fisk, Gregory W. Thiemann, Katie R. N. Florko, Derek C. G. Muir, Charmain D. Hamilton, Magali Houde, Enooyaq Sudlovenick, and David J. Yurkowski. 2024. Arctic and Aquatic Research Division, Fisheries and Oceans Canada, Winnipeg, MB. https://open.canada.ca/data/en/dataset/ea9ff038-8b16-11ef-8cce-55cc7f028297

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: This Archer fiord data is associated with a larger program ArcticCORE, which was created to fulfill knowledge gaps and develop long term protection in the extremely remote Tuvaijuittuq region. The main objectives of this expedition were to improve our comprehension of the key drivers for productive capacity, diversity and ecosystem structure in areas connected to Baffin Bay and Tuvaijuittuq, including Archer fiord. DESCRIPTION: ArcticCORE is a 5-year broader program aiming to characterize Tuvaijuittuq’s unique ecosystem and its influence and connectivity with the adjacent ecosystems to inform sustainable management and conservation initiatives in Tuvaijuittuq and the eastern Arctic. In an Arctic Ocean with rapidly declining sea ice, Tuvaijuittuq area retains the oldest and thickest sea ice, and can act as a refuge for ice-dependent species. This program aims to characterize the Arctic marine ecosystem and establish baseline measurements for future comparisons in the region. From 2023, water collection was carried out at four stations throughout Archer Fiord and analyzed for primary productivity, chlorophyll a, phytoplankton flow cytometry and phytoplankton taxonomy down to the lowest identifiable level. These data will contribute to a better understanding of the key drivers for productive capacity, diversity and ecosystem structure in Archer fiord. Characterization of these upstream areas are relevant for an ecosystem-based approach to fisheries management in Baffin Bay, a priority for DFO and an intrinsic part of mandated activities, as they influence the ecosystem and fisheries resources downstream.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past few decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e., Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2011 and 2016, georeferenced high-definition videography and photos were collected for various study sites along the east coast. The study areas include Labrador, Bay of Fundy and Chedabucto Bay in Atlantic Canada. Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation. Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e., shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded. The data was also validated through ground observations (when available) and a second interpreter QA (quality analysis) was performed on each dataset to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres to 2500 metres. In total, from 2011 to 2016, within the 3 study sites, about 1,850 km of shoreline were mapped.