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oceans

1039 record(s)
 
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    The Coastal Environmental Baseline Program is a multi-year Fisheries and Oceans Canada initiative designed to work with Indigenous and local communities and other key parties to collect coastal environmental data at six pilot sites across Canada (Port of Vancouver, Port of Prince Rupert, Lower St. Lawrence Estuary, Port of Saint John, Placentia Bay, and Iqaluit). The goal of the Program is to gather local information in these areas in effort to build a better understanding of marine ecological conditions. The Maritimes region has developed a physical oceanography program to align with the oceanographic interests and data needs of local communities and stakeholders, with the goal of sharing this information via open data. Starting in 2019, oceanographic parameters including temperature, salinity, depth, turbidity and currents have been continuously monitored at a series of locations covering a broad range of environments in the Port of Saint John and approaches vicinity, including the lower Saint John and Kennebecasis rivers, coastal fringe marshes and embayments, as well as the Musquash estuary Marine Protected Area (MPA). This dataset includes CTD data starting in 2019 and turbidity data from August 2020. Data collection methods range from bottom-mounted instruments in water depths of 10-50 meters, buoyant surface moorings, and hard-mounted instruments in intertidal zones. Intertidal data is interrupted during some low tide events, where the water level drops below the sensor, resulting in loss of functionality for periods up to 1-2 hours. Overall this dataset captures a dynamic balance between salt and fresh water on the highly tidal lower Saint John river, coastal seasonal dynamics in near-shore marine environments in the Musquash MPA, and the constant fluctuations of intertidal creeks and marshes. Update 2 - April 2025: included 2023-24 data Update 1 - Nov 2023: included 2022 data; removed daylight savings errors from 2019, 2020 and 2021; updated position for Evandale surface mooring.

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    The shallow substrate bottom type model was created to support near shore habitat modelling. Data sources include both available observations of bottom type and environmental predictor layers including oceanographic layers, fetch, and bathymetry and its derivatives. Using weighted random forest classification from the ranger R package, the relationship between observed bottom type and predictor layers can be determined, allowing bottom type to be classified across the study areas. The predicted raster files are classified as follows: 1) Rock, 2) Mixed, 3) Sand, 4) Mud The categorical substrate model domains are restricted to the extent of the input bathymetry layers (see data sources) which is 5 km from the 50 m depth contour.

  • This collection holds the layers used for the "Map of Upper Intertidal shoreline segmentation with Shoreline Cleanup Assessment Technique (SCAT) classification", a WMS service maintained by ECCC. The segmentation covers shorelines for Northern Canada, the North coast of British Columbia, as well as Ontario, Quebec, and Atlantic regions.

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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 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

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    This gridded product visualizes 1960 - 2014 water body dissolved oxygen concentration (umol/l) in the North Sea domain, for each season (winter: December – February; spring: March – May; summer: June – August; autumn: September – November). It is produced as a Diva 4D analysis, version 4.6.11: a reference field of all seasonal data between 1960-2014 was used; results were logit transformed to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. Every step of the time dimension corresponds to a 10-year moving average for each season. The depth dimension allows visualizing the gridded field at various depths.

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    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.

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    In 2012 and 2013, Fisheries and Oceans Canada conducted benthic imagery surveys in the Davis Strait and Baffin Basin in two areas then closed to bottom fishing, the Hatton Basin Voluntary Closure (now the Hatton Basin Conservation Area) and the Narwhal Closure (now partially in the Disko Fan Conservation Area). The photo transects were established as long-term biodiversity monitoring sites to monitor the impact of human activity, including climate change, on the region’s benthic marine biota in accordance with the protocols of the Circumpolar Biodiversity Monitoring Program established by the Council of Arctic Flora and Fauna. These images were analyzed in a techncial report that summarises the epibenthic megafauna found in seven image transects from the Disko Fan Conservation Area. A total of 480 taxa were found, 280 of which were identified as belonging to one of the following phyla: Annelida, Arthropoda, Brachiopoda, Bryozoa, Chordata, Cnidaria, Echinodermata, Mollusca, Nemertea, and Porifera. The remaining 200 taxa could not be assigned to a phylum and were categorised as Unidentified. Each taxon was identified to the lowest possible taxonomic level, typically class, order, or family. The summaries for each of the taxa include their identification numbers in the World Register of Marine Species and Integrated Taxonomic Information System’s databases, taxonomic hierarchies, images, and written descriptions. The report is intended to provide baseline documentation of the epibenthic megafauna in the Disko Fan Conservation Area, and serve as a taxonomic resource for future image analyses in the Arctic. Baker, E., Beazley, L., McMillan, A., Rowsell, J. and Kenchington, E. 2018. Epibenthic Megafauna of the Disko Fan Conservation Area in the Davis Strait (Eastern Arctic) Identified from In Situ Benthic Image Transects. Can. Tech. Rep. Fish. Aquat. Sci. 3272: vi + 388 p.

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    Envision Mapping was sub-contracted by Heriot Watt University for Scottish Natural Heritage (SNH) to undertake broad scale subtidal biotope mapping of Sullom Voe cSAC. Sullom Voe in the Shetland Isles is the most northerly site in the UK to be selected as a representative of large shallow inlets and bays, and within the site series it is the only Scottish example of a ria (known locally as a ?voe?). The boreal-arctic (northern) species-rich communities of Sullom Voe are restricted to Shetland voes and are not represented elsewhere in the SAC series. The purpose was to map the main features and biota using acoustic remote sensing techniques combined with grab and video sampling.

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    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

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    This visualization product displays the total abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations. 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 processings 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 surveys from non-MSFD 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. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata). - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 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, the median abundance for each beach and year is calculated from these normalized abundances per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account other sources data for all years. More information is available in the attached documents. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area.