Sea ice provides a wide range of microhabitats for diverse biota including microbes, single-celled eukaryotes (labelled algae), multicellular meiofauna, larger under-ice fauna (represented by amphipods), as well as polar cod (Boreogadus saida). Modified from Bluhm et al. (2017). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/sea-ice-biota" target="_blank">Chapter 3</a> - Page 35 - Figure 3.1.1

Bathymetric features, warm currents (red arrows), cold currents (blue arrows) and riverine inflow in the Arctic. Adapted from Jakobsen et al. (2012). Simplified Arctic Ocean currents (Fig. 2.1) show that the main circulation patterns follow the continental shelf breaks and margins of the basins in the Arctic Ocean. Different global models predict different types of changes, which can cause changes to Arctic ecosystems (AMAP 2013, Meltofte 2013). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 2</a> - Page 22 - Figure 2.1

The Regional Ice Ocean Prediction System (RIOPS) provides ice and ocean forecasts up to 84 hours, four times per day on a 1/12° resolution grid (3-8 km). RIOPS is initialized using analyses from the Global Ice-Ocean Prediction System (GIOPS). Atmospheric fluxes up to 84 hours forecasts are calculated using fields from a component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution

Distributions of all capelin species (light green) and Pacific capelin (Mallotus catervarius; dark green pattern) based on participation in research sampling, examination of museum voucher collections, the literature and molecular genetic analysis (Mecklenburg and Steinke 2015, Mecklenburg et al. 2016). Map shows the maximum distribution observed from point data and includes both common and rare locations STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/marine-fishes" target="_blank">Chapter 3</a> - Page 117 - Figure 3.4.5

This dataset provides 1/36-degree monthly-mean ocean current climatology (April - September) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).

Moving 6-year analysis of dissolved oxygen concentration in the Arctic Ocean, for each season in the period 1965-2022. Every year of the time dimension corresponds to the 6-year centered average for each season. Winter: December-February, Spring: March-May, Summer: June-August, Autumn: September-November. Depth range (IODE standard depths): 0, 5, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300, 400, ..., 1500, 1750, 2000, 2500m. Units: umol/l. Description of DIVA analysis: The computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.9, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.1 degrees. Signal-to-noise ratio was fixed to 3.0, horizontal correlation length varying from 45 km near the coast to 150 km, and vertical correlation length varying between 25 and 1000 m. Logarithmic transformation is applied to the data prior to the analysis. Background field: analysis with signal-to-noise ratio = 10, horizontal correlation length 60-200 km, and vertical correlation length 25-1000 m.

A novel towfish incorporating sidescan and video hardware was used to ground truth echosounder data for the nearshore of Halifax Harbour. The resulting sampling grid extended from the shoreline to a depth of 10 m, including Bedford Basin through the Inner Harbour to the Outer Harbour. Each of these three zones could be distinguished from the others based upon combinations of substrate type, benthic invertebrates, and macrophyte canopy. Bedford Basin had a relative lack of macrophytes and evidence of intense herbivory. The Inner Harbour was characterized by shoreline hardening due to anthropogenic activities. The Outer Harbour was the most “natural” nearshore area with a mix of bottom types and a relatively abundant and diverse macrophyte canopy. All survey data were placed into a GIS, which could be used to answer management questions such as the placement and character of habitat compensation projects in the harbour. Future surveys utilizing similar techniques could be used to determine long term changes in the nearshore of the harbour. Cite this data as: Vandermeulen H. Data of: A Video, Sidescan and Echosounder Survey of Nearshore Halifax Harbour. Published: September 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/9122c3e2-3cfc-45d0-ac36-aecb306130f6

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

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.

Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7