Government of Canada; Fisheries and Oceans Canada
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Commercial catches sampling program in the Estuary and Gulf of St. Lawrence – redfish (Sebastes sp.)
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 redfish (Sebastes sp.) includes the metadata, sample weight, fish length, the sex and the number of specimens measured. This dataset covers the periods of 1980-1996, 1999-2013, 2015-2016 and 2019. 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.
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This dataset contains point distribution occurrences for fish species found in marine waters of Arctic Canada. It was used to create the distribution maps in the book Marine Fishes of Arctic Canada, edited by B.W. Coad and J.D. Reist (2018) and the DFO Data Report of Fisheries and Aquatic Sciences Distributional Records for Marine Fishes of Arctic Canada (Alfonso et al. 2018). The database includes literature (Coad and Reist 2016) and museum records, anecdotal reports, personal communications and data from fisheries surveys and exploratory cruises. Development of the database began in 1998 and data entry ceased in 2016, although the database will be updated periodically. Consult the book (Coad and Reist 2018) and the Data Report (Alfonso et al. 2018) for further details in regards to the specific sources for each data point by species especially those from sources other than published literature.
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The data in this layer represents habitat suitability of soft-shelled clams (Mya arenaria) in the DFO Maritimes region, and was developed using an interdepartmental approach. Substrate classification data as well as bathymetric data for the Region were used to identify potential habitat for soft-shelled clams. Substrates identified as suitable included: sand, mud, sand and mud (Greenlaw, 2022). Contours (0m and 70m) from GEBCO bathymetric data were used to isolate depths between which soft-shelled clams are present. At this stage, a polygon reflecting soft substrates from 0-70m was created as "Suitable". A "Not Suitable" layer was similarly created using the substrates: boulders, continuous bedrock, discontinuous bedrock, gravel, mixed sediment, sand and gravel. To digitally validate the model, the Regional shoreline was divided into subsectors (developed by Environment and Climate Change Canada for the Canadian Shellfish Sanitation Program). Data from DFO (clam harvesting intensity) as well as Conservation and Protection (clam harvesting infraction locations) were used to established species presence within each sub-sector. If there had been any harvesting activity, legal or illegal, in an individual subsector, it was considered "Suitable and Validated". Merged into one final product, the model includes areas that are "Not Suitable", "Suitable", as well as "Suitable and Validated" for soft-shelled clam habitat. Cite this data as: Harvey, C., Vincent, M., Greyson, P., Hamer, A. (2024) Data of: A Soft-Shelled Clam (Mya arenaria) Habitat Suitability Model For The DFO Maritimes Region. Published: January 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/c76f7813-d802-4b31-8ebe-476f8a7cacf2
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The assessment of the status of eelgrass (Zostera marina) beds at the bay-scale in turbid, shallow estuaries is problematic. The bay-scale assessment (i.e., tens of km) of eelgrass beds usually involves remote sensing methods such as aerial photography or satellite imagery. These methods can fail if the water column is turbid, as is the case for many shallow estuaries on Canada’s eastern seaboard. A novel towfish package was developed for the bay-scale assessment of eelgrass beds irrespective of water column turbidity. The towfish consisted of an underwater video camera with scaling lasers, sidescan sonar and a transponder-based positioning system. The towfish was deployed along predetermined transects in three northern New Brunswick estuaries. Maps were created of eelgrass cover and health (epiphyte load) and ancillary bottom features such as benthic algal growth, bacterial mats (Beggiatoa) and oysters. All three estuaries had accumulations of material reminiscent of the oomycete Leptomitus, although it was not positively identified in our study. Tabusintac held the most extensive eelgrass beds of the best health. Cocagne had the lowest scores for eelgrass health, while Bouctouche was slightly better. The towfish method proved to be cost effective and useful for the bay-scale assessment of eelgrass beds to sub-meter precision in real time. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Using Sidescan and Video - Cocagne 2008. Published: November 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/431c815e-65f0-477b-9389-060fa41ec955
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Ecologically and Biologically Significant Areas (EBSAs) are areas within Canada's oceans that have been identified through formal scientific assessments as having special biological or ecological significance when compared with the surrounding marine ecosystem. Failure to define an area as an EBSA does not mean that it is unimportant ecologically. All areas serve ecological functions to some extent and require sustainable management. Rather, areas identified as EBSAs should be viewed as the most important areas where, with existing knowledge, regulators and marine users should be particularly risk averse to ensure ecosystems remain healthy and productive. Why are EBSAs identified? EBSA information is used to inform marine planning, including environmental assessment and the siting of marine-based activities, by: - Informing and guiding project-specific or regional environmental assessments; - Informing and guiding industries and regulators in their planning and operations, for example: EBSAs have been acknowledged and referred to (often as "Special Areas" or "Potentially Sensitive Areas") in oil and gas related assessments; - EBSA information has been provided to proponents of submarine cable projects to be used for route planning purposes; - Informing and guiding Integrated Oceans Management (IOM) process within five Large Ocean Management Areas (LOMAs) and twelve marine bioregions; - Serving as a basis for the identification of Areas of Interest (AOIs) and of Marine Protected Areas (MPAs) (individually and in the context of planning bioregional networks of MPAs). How are EBSAs identified? The process used to identify EBSAs is generally comprised of two phases. The first phase involves compiling scientific data and knowledge of a marine area's ecosystems - notably fish species, marine mammals, sea birds, marine flora, marine productivity, physical and chemical conditions and geology. "Knowledge" includes experiential knowledge of long-time uses of the areas. In some cases (e.g., in the Arctic), substantial efforts are taken to collect traditional knowledge on ecosystems and environmental conditions from community members, fish harvests, hunters and individuals whose knowledge of the study area complement often helps fill scientific data gaps. In the second phase, the available information for a marine area (e.g. a bioregion) is assessed against five nationally-established science-based criteria including: - Uniqueness: How distinct is the ecosystem of an area compared to surrounding ones? - Aggregation: Whether or not species populate or convene to the study area? - Fitness consequence: How critical the area is to the life history of the species that use it (e.g. is it a spawning or feeding ground)? - Naturalness: How pristine or disturbed by human activities is the study area? - Resilience: What is the ability of the ecosystem to bounce back if it is disturbed? Progress to date and next steps EBSAs have been identified for large portions of Canada's Atlantic and Pacific Oceans as well as most of the Arctic oceans. EBSAs will continue to be identified in priority areas as resources become available to carry out the process. The boundaries or locations of existing EBSAs may be modified to reflect both new knowledge and changing environmental conditions.
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Across the Canadian North, Arctic Char, Salvelinus alpinus, are culturally important and critical for maintaining subsistence lifestyles and ensuring food security for Inuit. Arctic Char also support economic development initiatives in many Arctic communities through the establishment of coastal and inland commercial char fisheries. The Halokvik River, located near the community of Cambridge Bay, Nunavut, has supported a commercial fishery for anadromous Arctic Char since the late 1960s. The sustainable management of this fishery, however, remains challenging given the lack of biological data on Arctic Char from this system and the limited information on abundance and biomass needed for resolving sustainable rates of exploitation. In 2013 and 2014, we enumerated the upstream run of Arctic Char in this system using a weir normally used for commercial harvesting. Additionally, we measured fish length and used T-bar anchor tags to mark a subset of the run. Subsequently, we estimated population size using capture-mark-recapture (CMR) methods. The estimated number of Arctic Char differed substantially between years. In 2013, 1967 Arctic Char were enumerated whereas in 2014, 14,502 Arctic Char were enumerated. We attribute this marked difference primarily to differences in weir design between years. There was also no significant relationship between daily mean water temperature and number of Arctic Char counted per day in either year of the enumeration. The CMR population estimates of Arctic Char (those ≥450mm in length) for 2013 and 2014 were 35,546 (95% C.I 30,513-49,254) and 48,377 (95% C.I. 37,398-74,601) respectively. The 95% CI overlapped between years, suggesting that inter-annual differences may not be as extreme as what is suggested by the enumeration. The population estimates reported here are also the first estimates of population size for an Arctic Char stock in the Cambridge Bay region using CMR methodology. Overall, the results of this study will be valuable for understanding how population size may fluctuate over time in the region and for potentially providing advice on the sustainable rates of harvest for Halokvik River Arctic Char. Additionally, the results generated here may prove valuable for validating current stock assessment models that are being explored for estimating biomass and abundance for commercial stocks of Arctic Char in the region.
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The annual summer scallop surveys on the principal grounds in the Bay of Fundy follow stratified-random designs. The gear comprises a ‘Digby scallop drag’ with four ‘buckets’, each of 760 mm inside width, their bags being made of 74 mm steel-wire rings linked by rubber washers. A comparative data set of three scallop grounds (Digby, Lurcher Shoal and Grand Manan) was produced comprised of 190 stations sampled in 1997 and 213 from 2007–08. Presence/absence of a common suite of 68 benthic invertebrate taxa were recorded: 43 individual species, 20 additional genera and five higher taxa, all drawn from nine phyla. Each taxon was coded for each of seven biological traits (each with associated modalities), selected for their assumed relevance to environmental drivers. A score between 0 and 3 was assigned based on the literature for the taxon’s affinity to each modality, using ‘fuzzy coding’. Non-zero scores were assigned to as many modalities as required to represent the traits of the taxon’s adult stage. The resulting taxa x traits matrix, of 68 taxa by 27 modalities, is provided here along with the metadata for each station sampled. In addition, fourteen environmental variables, deemed relevant to benthic epifauna and representing both seabed sediments and the water column, were quantified for each survey station. Seabed depth, mean grain size, mean significant wave height, mean seabed shear stress, root mean square tidal current speed 1 m above the seabed and combined averaged wave-current shear velocity were each extracted from a sediment transport model for the Bay of Fundy prepared by Li et al. (2015). Mean values for current velocities, salinity and temperature for both surface and bottom layers, plus maximum mixed layer depth and bottom shear were each drawn from the Bedford Institute of Oceanography North Atlantic Model (BNAM: Wang et al., 2018). BNAM values averaged across 1990–2015 were used when examining faunal differences among survey areas, but explorations of temporal change used annual values for 1997 and 2007 individually. The variable nomenclature in the attached spreadsheet follows those of Li et al. (2015) and Wang et al. (2018). Results of the spatial and temporal analyses of these data are found in Staniforth et al. (2023). The values for each of the environmental variables are provided in the spreadsheet below. Their interpolated surfaces are also provided. Cite this data as: MacDonald, Barry; Staniforth, Calisa; Lirette, Camille; Murillo, Francisco; Kenchington, Ellen; Kenchington, Trevor (2023). Benthic Megafaunal Assemblages on Scallop Fishing Grounds in the Bay of Fundy (1997 and 2007). Published May 2024. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/935836da-a565-4f1e-806e-d354d8db252c
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White Hake otoliths are collected from scientific surveys, fisheries observers on fishing vessels and from scientific sampling of commercial fisheries. The otoliths collected are placed in paper envelopes, recorded and held in a climate-controlled storage facility. Age determination is performed episodically on the available samples. Digital images of each pair of otoliths collected are captured when possible. The information made available through this metadata record is the summary of otoliths present in the collection at the Gulf Fisheries Centre in Moncton, NB, Canada. There is additional information of observed sex, length, weight and age information of fish specimens made by trained Fisheries and Oceans Canada technicians that can be made available upon request. PARAMETERS COLLECTED: length (biological), age (biological) NOTES ON QUALITY CONTROL: A reference collection for ageing White Hake exists and is used to calibrate the age readings obtained by the fisheries technicians that use the otoliths for age estimation. Digital images of the otoliths that are part of the reference collection are available and used for calibration and training purposes. The otolith images are also authoritatively annotated by fisheries technicians. PHYSICAL SAMPLE DETAILS: Fish otoliths SAMPLING METHODS: White Hake otoliths are obtained from fish specimens collected during research surveys, observer activities onboard commercial fishing vessels and during scientific sampling of commercial fisheries. The sagittal otolith is removed from sampled specimens, recorded, placed in a protective medium and held in a climate-controlled storage facility. Digital images of each pair of otoliths collected are captured when possible.
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The St. Anns Bank Marine Protected Area was established in June 2017. Data describing the spatial-temporal patterns and drivers of species movement is essential for evaluating species composition and to gauge the protective capacity of the MPA. Since 2015, an acoustic telemetry receiver array has been deployed and re-deployed annually in St. Anns Bank Marine Protected Area. Each receiver detects tagged fish that swim past and records hourly bottom temperature. Here we provide the bottom temperature data recorded on 46 receivers. Note that in 2021 the array design (mooring positions) changed. Please visit the Ocean Tracking Network data portal for more details (https://members.oceantrack.org/project?ccode=SABMPA). Cite this data as: Pettitt-Wade, H., Jeffery, N.W., Stanley, R.E. Data of: Bottom temperature data from St. Anns Bank MPA acoustic telemetry receivers deployed 2015 to 2022 Published: January 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/910b8e22-2fd1-4ba1-8db6-d16763c7a625
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The Coastal Oceanography and Ecosystem Research section (DFO Science) reviewed the presence of Cod in the Population Ecology Division (DFO Science) Ecosystem Survey trawls to describe the likelihood of presence. The survey consists of a stratified random design using a bottom trawl. This layer was created for consideration in oil spill response planning. A version of this dataset was created for the National Environmental Emergency Center (NEEC) following their data model and is available for download in the Resources section. Cite this data as: Lazin, G., Hamer, A.,Corrigan, S., Bower, B., and Harvey, C. Data of: Likelihood of presence of Atlantic Cod in Area Response Planning pilot areas. Published: June 2018. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/af2bf6c0-481d-4445-bbc6-7a785d2a9aa9