Administrative boundaries of sectors, boroughs and cities.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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

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 Beds Using Sidescan and Video - Bouctouche. Published: November 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b4c83cd2-20f2-47d8-8614-08c1c44c9d8c

Towfish (sidescan and video) and echo sounder surveys were utilized to examine bottom type and macrophyte cover within the area of two coastal marine finfish aquaculture sites, one in New Brunswick (Welch Cove) and one in Nova Scotia (Jordan Bay). Both towfish and echo sounder data could be used independently of one another. However, the towfish data were very useful for ground truthing echo sounder based classifications. All survey data were placed into a GIS which could be used to answer management questions such as the placement of cages at sites, benthic impacts and baseline conditions to determine long term changes. Cite this data as: Vandermeulen H. Data of: Exploratory Video-Sidescan and Echosounder Survey of Welch Cove. Published: June 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/0083e317-8bb5-492a-8348-c021e183f307

The layer provides information on suspended particulate matter (SPM) concentrations by area. There is a natural interaction phenomenon between hydrocarbons and SPM, that creates hydrocarbon-SPM aggregates. The SPM in the water column, hence has an effect on hydrocarbon capacity to sink to the bottom in aggregate form (Gong et collab., 2014 ; Fitzpatrick et collab., 2015, cited in Centre d'expertise en analyse environnementale du Québec, 2015). Additional Information The suspended particulate matter data for this layer are derived from multiple sources given the need to cover the St. Lawrence portion from Montreal to Anticosti. The layer has been cut into 6 different zones. Denis Lefaivre, a researcher at Maurice-Lamontagne Institute, has provided the coordinates of the points allowing the delimitation of areas. The values in each zone are derived from different studies carried out at different times. The references are cited below for each of the polygons from West to East, as well as for the summary: 1- Department of Sustainable Development, Environment and Climate Change and Environment and Climate Change Canada, 2016. Recommendations for Suspended Matter Management (ESM) during dredging activities. Quebec. 64 pages and appendices. http://planstlaurent.qc.ca/fileadmin/publications/diverses/Registre_de_dragage/Recommandations_dragage.pdf 2- D'Anglejan, B. 1990. Recent Sediments and Sediment Transport Process in the St. Lawrence Estuary. In Oceanography of a Large-Scale Estuarine System: The St. Lawrence, edited by M. I. El-Sabh and N. Silverberg. New York: Springer-Verlag, 109- 153. 3- Silverberg, N., and B. Sundby. 1979. Observations in the maximum turbidity of the St. Lawrence estuary. Can. J. Earth Sci. 16: 939-950. 4- Michel Lebeuf, 2016.Unpublished personal data.Collected between 2015-2016 for research purposes. 5- Sundby, B. 1974. Distribution and Transport of Suspended Particulate Matter in the Gulf of St. Lawrence. Canadian Journal of Earth Sciences11 (11): 1517-1533. 6- Gong, Y., X. Zhao, Z. Cai, S. E. O'Reilly, X. Hao and D. Zhao. 2014. A review of oil, dispersedoil and sediment interactions in the aquatic environment: Influence on the fate, transportand remediation of oil spills. Marine Pollution Bulletin, vol. 79: 1-2, p.16-33. 7- Fitzpatrick, F.A., M.C., Boufadel, R., Johnson, K., Lee, T.P., Graan, A.C., Bejarano, Z.,Zhu, D., Waterman, D.M., Capone, E., Hayter, S.K., Hamilton, T., Deffer, M.H.,Garcia, et J.S., Hassan. 2015. Oil-particle interactions and submergence from crudeoil spills in marine and freshwater environments – Review of the science and futurescience needs. U.S. Geological Survey Open-file report 2015-2016, 33 p. 8- Centre d'expertise en analyse environnementale du Québec,2015.Hydrocarbures pétroliers : caractéristiques, devenir et criminalistique environnementale –Études GENV222 et GENV23, Évaluation environnementale stratégique globale sur leshydrocarbures. Ministère du Développement durable, de l’Environnement et de la Lutte contreles changements climatiques, 41 p. et annexes. 9- CSL – Centre Saint-Laurent, 1997. Le Saint-Laurent : dynamique et contamination des sédiments, Montréal, Environnement Canada – Région du Québec, Conservation de l’environnement, 127 p. (coll. BILAN Saint-Laurent). [Rapport thématique sur l’état du Saint-Laurent].

Layer that includes the known information on harbor seal breeding and feeding areas in the Saguenay Fjord, the Estuary and Gulf of St. Lawrence according to a literature review of documents produced between 1968 and 2001. Additional Information Harbor seal breeding and feeding areas were produced according to a literature review of the following documents: Andersen, A. et M. Gagnon. 1980. Les ressources halieutiques de l'estuaire du Saint-Laurent. Rapp. can. ind. sci. halieut. aquat., 119: iv + 56 p. Communications personnelles par Fournier, C. 1999. Communications personnelles par Gosselin, J-F-. 1996. Communications personnelles par Gosselin. J.-F. 2001. Communications personnelles par Lavigueur, L. 1996. Dignard, N., R. Lalumière, A. Reed et M. Julien. 1991. Les habitats côtiers du nord-est de la Baie James. Publication hors-série no. 70. Environnement Canada, Service canadien de la faune. 30 p. + carte. Enquête auprès des pêcheurs et agents du MEF et du MPO. 1995. Mansfield, A. W. 1968. Seals and walruses. In: Beals, C.S., ed. Science, History and Hudson Bay. Vol. 1. Ottawa: Queen’s Printer. 501 p.

Description: This dataset consists of monthly mean simulation results from Canada's three Oceans: the Atlantic, Pacific and Arctic from 2015 to 2017. Abstract from the report: A numerical ocean model with biogeochemistry has been developed for a domain that spans Canada's three oceans: the Atlantic, Pacific and Arctic. The domain extends to 26°N in the Atlantic and 44°N in the Pacific, and spans the full width of each basin as well as the whole of the Arctic Ocean. The resolution is moderate to high (≈0.25°, 75 levels). A series of simulations was conducted to assess the best choices for biogeochemical model parameters across the diverse regions, using a variety of validation data sets including satellite ocean colour (surface chlorophyll and particulate organic carbon, integrated primary production), surface underway pCO2, and depth profiles of oxygen and nitrate concentration from ships and Argo floats. In addition to parameter values, processes examined include interactive sediments, fluvial nutrients, light attenuation by fluvial coloured dissolved organic matter (CDOM), and iron limitation. The results indicate that the optimal parameter set is one that limits phytoplankton losses to grazing and other processes so as to ensure strong biological drawdown of dissolved inorganic carbon and nutrients in spring and summer; among the parameter sets tested both insufficient and excessive drawdown were observed. Sensitivity to other processes such as interactive sediments, fluvial nutrients or CDOM attenuation was weak in most regions. In some regions, attenuation by CDOM or sequestration of nutrients in the sediment can substantially reduce primary production and zooplankton biomass, and fluvial nutrients can cause localized reduction of pCO2 by as much as 60 μatm. Iron limitation has an effect on the model solution in regions generally considered iron-replete; building a model that successfully spans iron-limited and non-iron-limited domains will require complete and accurate specification of iron sources and sinks.

This dataset represents abundance data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey. Data is binned into 5-mm shell height bins, is prorated to an 800 m tow length and 17.5 feet (5.334 m) drag width (i.e., representing an area swept of 4267 m2), and was collected using unlined dredge gear. Each row represents a tow and contains information such as tow date, cruise name, gear type, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025). References Glass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p. Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p. Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Commercial Size Abundance Data. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ecc09d98-56ed-4a27-ad62-5c3714a1d9b4

A towfish containing sidescan and video hardware was used to map eelgrass in two shallow northern New Brunswick estuaries. The sidescan and video data were useful in documenting suspected impacts of oyster aquaculture gear and eutrophication on eelgrass. With one boat and a crew of three, the mapping was accomplished at a rate of almost 10 km2 per day. That rate far exceeds what could be accomplished by a SCUBA based survey with the same crew. Moreover, the towfish survey applied with a complementary echosounder survey is potentially a more cost effective mapping method than satellite based remote sensing. Cite this data as: Vandermeulen H. Data of: Bay Scale Assessment of Eelgrass Beds Using Sidescan and Video - Shippagan 2007. Published: November 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/6454594e-c8f9-41c4-801a-db125b8a8875

This dataset was collected in support of a Competitive Science and Research Fund project (21-CC-05-06 Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop: larval supply, recruitment and adaptive capacity to multiple global change drivers) lead by Fisheries and Oceans Canada (DFO). The objective of this research is to characterize coastal environmental conditions associated with scallop spawning and larval drift in Passamaquoddy Bay, New Brunswick. This dataset includes temperature, conductivity, salinity, sigma-theta, sea pressure, and depth information taken at weekly intervals at the sampling stations. In total, this dataset represents a total of 62 CTD profiles collected across 3 sampling stations over 22 sampling days from June to October 2022. Sampling stations were selected to compare scallop recruitment signals from Chamcook Harbour, a decommissioned scallop aquaculture site in Big Bay (MS-1077) and in the middle of Passamaquoddy Bay. Data were processed in accordance with instrumentation manufacturer guidelines and DFO Ocean Data and Information Section QAQC procedures. Cite this data as: Miller, E., Quinn, B., Azetsu-Scott, K., Childs, D., Gabriel, C-E., Newhook, M. 2025. Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop. Published October 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B