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

The locations of coastal British Columbia marine navigation hazards. The Coastal BC datasets are circa 2004 and legacy in nature. Caution should be exercised when using this data, as it may not be accurate or complete. There are currently no plans to update.

This dataset provides projected 30-year, 50-year, and 100-year return levels for harbours in British Columbia by 2050 and 2100 under an intermediate emission scenario SSP245, relative to the mean sea level over 1993-2020. The return levels are a combination of estimated present extreme sea levels and projected mean sea level rise. The present extreme sea levels are derived from hourly coastal sea levels for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM). The projected mean sea level rise is derived from the regional mean sea level rise data of the IPCC 6th Assessment Report under SSP245, adjusted for the local vertical land motion.

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 provides projected 30-year, 50-year, and 100-year return levels for harbours in British Columbia by 2050 and 2100 under a high emission scenario SSP585, relative to the mean sea level over 1993-2020. The return levels are a combination of estimated present extreme sea levels and projected mean sea level rise. The present extreme sea levels are derived from hourly coastal sea levels for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM). The projected mean sea level rise is derived from the regional mean sea level rise data of the IPCC 6th Assessment Report under SSP585, adjusted for the local vertical land motion.

Running 6-year analysis of Water body phosphate in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to a 6-year centred average. Periods span between 1975-2021. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300. Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis in n dimensions) tool. GEBCO_08 Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the horizontal correlation length is fixed to 80 km and decreasing towards the coastline, the vertical correlation length is varying with depth. Signal to noise ratio is fixed to 1.0. Background fields were created using data for the given time period and season. Log transformation was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is umol/l.

The Quebec—Saint-Lawrence River dataset is part of Environment and Climate Change Canada’s Shoreline Classification and Pre-Spill database. Shoreline classification data has been developed for use by the Environmental Emergencies Program of Environment and Climate Change Canada for environmental protection purposes. Marine and freshwater shorelines are classified according to the character (substrate and form) of the upper intertidal (foreshore) or upper swash zone (Sergy, 2008). This is the area where oil from a spill usually becomes stranded and where the treatment or cleanup activities take place. The basic parameter that defines the shoreline type is the material that is present in the intertidal zone. The presence or absence of sediments is a key factor in determining whether oil is stranded on the surface of a substrate or can penetrate and/or be buried. This dataset contains thousands of linear shoreline segments ranging in length from 200 m and 2 km long. The entities represent the location of the segments and their geomorphological description. There exist further fields in the attribute table for this dataset. We are currently working on standardizing our shoreline segmentation datasets and the updated data will soon be uploaded to the catalog. Sergy, G. (2008). The Shoreline Classification Scheme for SCAT and Oil Spill Response in Canada. Proceedings of the 31stArctic and Marine Oil Spill Program Technical Seminar.Environment Canada, Ottawa, ON, Pp. 811-819.

The locations of coastal British Columbia marine navigation aids. The Coastal BC datasets are circa 2004 and legacy in nature. Caution should be exercised when using this data, as it may not be accurate or complete. There are currently no plans to update.

Moving 6-year analysis of Oxygen at Atlantic Sea for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centered average of each season. 6-year periods span from 1960-1965 until 2015-2020. Observational data span from 1960 to 2020. Depth range (IODE standard depths): -3000.0, -2500.0, -2000.0, -1750, -1500.0, -1400.0, -1300.0, -1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -20.0, -10.0, -5.0, -0.0 Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5 DIVA settings. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. Signal to noise ratio was fixed to 1. Background field: the data mean value is subtracted from the data. Detrending of data: no, Advection constraint applied: no. Units: umol/l

This product displays for Triphenyltin, 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.