Long-term measurements of sea water properties collected by sensor buoy in Adventfjorden as part of the Svalbard Integrated Arctic Earth Observing System (SIOS).

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 - Richibucto 2007. Published: October 2017. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ca7af8ba-8810-4de5-aa91-473613b0b38d

This dataset contains the modelled and observed data used in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). An application of the Finite Volume Community Ocean Model (FVCOM v4.1) was run from May 24 to June 27, 2019 in the Discovery Islands region of British Columbia, Canada. Observed temperature and salinity profiles available in this area during this time period are included in the dataset, along with the modelled values at the same times and locations.

This dataset contains the outputs for Bute Inlet from two simulations shown in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). The Finite Volume Community Ocean Model (FVCOM v4.1) was run with two different sets of initial conditions for the Discovery Islands region of British Columbia, Canada, from May 24 to June 27, 2019. The "Baseline" simulation used observed initial conditions, while the "Sensitivity" simulation removed the observed cold subsurface water mass from the initial profiles. Here in this dataset, we provide 29-day averages of the following variables in a transect along Bute Inlet: potential temperature, density, along-inlet velocity, and Brunt-Väisälä frequency (N^2). The averaging properly removes the tidal effects.

A novel, bay – scale (i.e. tens of km) survey method was employed to examine algal populations on the southwestern shore of Cape Breton, Canada, for the purposes of potential economic exploitation. Since traditional remote sensing methods were unlikely to be successful in these waters, underwater video and acoustic methods were applied. A transponder positioned towfish housing video camera and sidescan sonar was hauled along predetermined transects perpendicular to shore to provide information on bottom type and algal cover. The towfish data were used to ground truth echosounder data (bottom type and macrophyte canopy height) collected along 5, 10 and 20 m depth contours. The survey area was divided into six zones comprising a range of exposure, depth and bottom types. Destructive quadrat samples were collected at each depth plus shore stations to provide biomass estimates. Over thirty five taxa were enumerated, indicating depths and zones of common occurrence. Ascophyllum was abundant at some of the shore stations. The genera Chondrus, Cystoclonium, Desmarestia, Fucus, Phyllophora, Polysiphonia, and Saccharina were common at 5 m. Desmarestia and Saccharina dominated at 10 m with wet weights sometimes over 1 kg·m-2. Agarum dominated at 20 m. The towfish / echosounder grid sampling system was relatively coarse in order to cover the 140 km2 survey area within 12 days. As a result, the survey did not produce spatially detailed information. However, adequate information was gathered to describe the general characteristics of bottom type and algal cover by zone and for focusing further exploration--Abstract, p. vi. Cite this data as: Vandermeulen H. Data of: A Novel Video and Acoustic Survey of the Seaweeds of Isle Madame. Published: August 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ebdd8f91-9131-45f0-8aec-aba9f65e3fae

Circumpolar depiction of species richness based on the distributions of the 11 ice-associated Focal Ecosystem Components (according to the distributions reported in IUCN Red List species accounts). A maximum of nine species occur in any one geographic location. The Arctic gateways in both the Atlantic and Pacific regions have the highest species diversity. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/marine-mammals" target="_blank">Chapter 3</a> - Page 152 - Figure 3.6.1

The data were collected during two research projects: Development of community-based monitoring for aquatic invasive species in the Canadian Arctic - preparing for increased shipping related to resource development and climate change; Diversity of pelagic primary producers in coastal habitats and the potential for harmful blooms in Eastern Canadian Arctic, with a focus near Iqaluit, Nunavut. Funding was provided by Polar Knowledge Canada, Fisheries and Oceans Canada (Strategic Program for Ecosystem-based Research and Advice, Aquatic Invasive Species Program and Oceans Ocean Protection Plan) and the Nunavik Marine Region Wildlife Board. These data are the abundance, richness and diversity of dinoflagellate communities in Canadian Arctic seaports to provide baseline data and to verify the presence of potential non-indigenous species and harmful taxa. These data can be used as a reference source for monitoring the introduction of potentially non-native species introduced into Arctic ports where shipping activities are high. SAMPLING Dinoflagellate samples were collected using a 20 μm (30 cm diameter) Nitex® plankton net during August in Churchill (MB) (2007 and 2015), in Deception Bay (QC ) (2016), in Iqaluit (NU) (2015 and 2019) and in Milne Inlet (2017). Samples were collected from 1 m of the surface to 1 m above the bottom. PREPARATION : Samples were stored in 4% formaldehyde. Sample preparation and counting were performed using the Utermöhl method. OBSERVATION : Samples were observed using an inverted microscope (NIKON Eclipse TE-2000-U) under a magnification of 200x. ABUNDANCE : The calculation of the abundance of dinoflagellates (cell / liter) was carried out as follows: Number of cells X Volume of the bottle / Volume of the Utermöhl chamber / (pi X Radius^2 X Depth) X 1000 ENVIRONMENTAL VARIABLES Environmental data were measured using a CTD and a Secchi disk. The time between sea ice melt and sampling was calculated by subtracting the sampling day from the breakup dates (ice concentration <1/10) which were extracted from the Canadian Ice Service records. For further information, please consult the following paper: Dhifallah F, Rochon A, Simard N, McKindsey CW, Gosselin M, Howland KL. 2022. Dinoflagellate communities in high-risk Canadian Arctic ports. Estuarine, Coastal and Shelf Science 266:107731

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

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 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 -Tabusintac 2008. Published: March 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/d1c58bc6-69d4-47b2-bb19-988f88233900