Bay Scale Assessment of Habitat in Bras d'Or Lake - River Denys 2005 - 2009 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - River Denys 2005 - 2009. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

This product displays for Hexachlorobenzene, median values of the last 6 available years that have been measured per matrix and are present in EMODnet regional contaminants aggregated datasets, v2022. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, >90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.

This product displays for Lead, positions with values counts that have been measured per matrix for each year and are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for every available year.

Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Chapel Island 2008 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Chapel Island 2008. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

Data layers show commercial fishery footprints for directed fisheries using bottom and pelagic longlines for groundfish and large pelagics respectively, and traps for hagfish, LFA 41 and Grey Zone lobster, snow crab, and other crab on the Scotian Shelf, the Bay of Fundy, and Georges Bank in NAFO Divisions 4VWX and Canadian portions of 5Y and 5Z. Bottom longline and trap fishery maps aggregate commercial logbook effort (bottom longline soak time and logbook entries) per 2-minute grid cell using 2002–2017 data. Pelagic longline maps aggregate speed-filtered vessel monitoring system (VMS) track lines as vessel minutes per km2 on a base-10 log scale using 2003–2018 data. The following data layers are included in the mapping service for use in marine spatial planning and ecological risk assessment: 1) multi-year and quarterly composite data layers for bottom longline and trap gear, and 2) multi-year and monthly composite data layers for pelagic longline gear. Additional details are available online: S. Butler, D. Ibarra and S. Coffen-Smout, 2019. Maritimes Region Longline and Trap Fisheries Footprint Mapping for Marine Spatial Planning and Risk Assessment. Can. Tech. Rep. Fish. Aquat. Sci. 3293: v + 30 p. http://publications.gc.ca/collections/collection_2019/mpo-dfo/Fs97-6-3293-eng.pdf

This visualization product displays the total abundance of marine macro-litter (> 2.5cm) per beach, per 100m & to 1 survey aggregated over the period 2001 to 2020 from Marine Strategy Framework Directive (MSFD) monitoring surveys. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Some categories & some litter types like organic litter, small fragments (paraffin and wax; items > 2.5cm) and pollutants have been removed. The list of selected items is attached to this metadata (total abundance list). This list was created using EU Marine Beach Litter Baselines and EU Threshold Value for Macro Litter on Coastlines from JRC (these two documents are attached to this metadata); - Normalization of survey lengths to 100m & 1 survey / year: in some cases, the survey length was not exactly 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of items (normalized by 100 m) = Number of litter per items x (100 / survey length) Then, this normalized number of items is summed to obtain the total normalized number of litter for each survey. Finally, a median is calculated over the entire period among all these total numbers of litter per 100m calculated for each survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. The size of each circle on this map increases with the calculated median number of marine litter per beach, per 100m & to 1 survey. The median litter abundance values displayed in the legend correspond to the 50 and 99 percentiles and the maximum value. More information is available in the attached documents. Warning: - the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area. - This map was created to give an idea of the distribution of beach litter between 2001 and 2021 in a synthetic manner. NOT ALL BEACHES MAY HAVE DATA FOR THE ENTIRE PERIOD, SO IT IS NOT POSSIBLE TO MAKE A COMPARISON BETWEEN BEACHES.

This layer details Important Areas (IAs) relevant to sponge reefs (Hexactinosida) in the Strait of Georgia (SOG) ecoregion. This data was mapped to inform the selection of marine Ecologically and Biologically Significant Areas (EBSA). Experts have indicated that these areas are relevant based upon their high ranking in one or more of three criteria (Uniqueness, Aggregation, and Fitness Consequences). The distribution of IAs within ecoregions is used in the designation of EBSAs. Canada’s Oceans Act provides the legislative framework for an integrated ecosystem approach to management in Canadian oceans, particularly in areas considered ecologically or biologically significant. DFO has developed general guidance for the identification of ecologically or biologically significant areas. The criteria for defining such areas include uniqueness, aggregation, fitness consequences, resilience, and naturalness. This science advisory process identifies proposed EBSAs in Canadian Pacific marine waters, specifically in the Strait of Georgia (SOG), along the west coast of Vancouver Island (WCVI, southern shelf ecoregion), and in the Pacific North Coast Integrated Management Area (PNCIMA, northern shelf ecoregion). Initial assessment of IA's in PNCIMA was carried out in September 2004 to March 2005 with spatial data collection coordinated by Cathryn Clarke. Subsequent efforts in WCVI and SOG were conducted in 2009, and may have used different scientific advisors, temporal extents, data, and assessment methods. WCVI and SOG IA assessment in some cases revisits data collected for PNCIMA, but should be treated as a separate effort. Other datasets in this series detail IAs for birds, cetaceans, fish, geographic features, invertebrates, and other vertebrates. Though data collection is considered complete, the emergence of significant new data may merit revisiting of IA's on a case by case basis.

This dataset was compiled as part of a multiyear effort lead by Fisheries and Oceans Canada (DFO) to support sustainable aquaculture regulation in the Coast of Bays, an area of the south coast of Newfoundland. It is the second of a series aiming to provide an oceanographic knowledge baseline of the Coast of Bays. This dataset includes temperature, salinity, and dissolved oxygen concentration profiles collected during CTD surveys, each survey containing a varying number of casts/profiles taken within the area of interest. In total, 760 profiles from 11 surveys, executed over 276 stations, were collected from June 2009 to November 2013. Data were processed and quality controlled using the instrumentation manufacturer guidelines, custom tools as well as visual inspection. Data are provided in tab-delimited text-based format compatible with most data processing language and tools (e.g. MS. Excel) as well as with the Ocean Data View software (https://odv.awi.de/) for rapid visualisation. A summary of the CTD profiles and stations surveyed is also provided as a comma separated values (CSV) file. A full description of the data and of its use in the context of the motivating project can be found in http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2017/2017_077-eng.html. Analyses from this dataset were presented during a Canadian Science Advisory Secretariat (CSAS) meeting which took place in St John’s in March 2015 (http://www.dfo-mpo.gc.ca/csas-sccs/schedule-horraire/2015/03_25-26b-eng.html) and from which a Science Advisory Report (http://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2016/2016_039-eng.html) and Proceedings (http://www.dfo-mpo.gc.ca/csas-sccs/Publications/Pro-Cr/2017/2017_043-eng.html) were published.

This product displays for Anthracene, median values since 2012 that have been measured per matrix and are present in EMODnet regional contaminants aggregated datasets, v2024. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, >90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.

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.