This dataset is part of Environment and Climate Change Canada’s Shoreline Classification and Pre-Spill database and it covers various locations across the Canadian Arctic i.e. James Bay, Resolute Bay and the south coast of Devon Island, the south-west coast of Hudson Bay, Labrador Coast, Victoria Strait, Beaufort Sea, and the North-east coast of Baffin Island. 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 of the upper intertidal (foreshore) or upper swash zone. 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 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.

To develop a database of high quality CTD observations at key locations in DFO’s Pacific Region, 22 stations have been selected for sampling as often as possible. Chief Scientists of DFO vessels with CTD equipment on board are asked to acquire a CTD profile at as many of these stations as possible. There may be circumstances that will prevent conducting a CTD cast but the intent is to collect as many as possible such that over time useful time series of CTD profiles will be available at these locations.

Status of monitoring activities for each Focal Ecosystem Component (i.e., selected species groups) across each Arctic Marine Area as included in this report. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/monitoring-status-and-advice" target="_blank">Key Findings</a> - Page 5 - Figure 1

Ice algal community similarity of central Russian Arctic drifting stations from the 1980s to 2010s based on unpublished data by I.A. Melnikov, Shirshov Institute of Oceanology. The closer two samples (symbols) are to each other in this multi-dimensional scaling plot, the more similar their algal communities were, based on presence/absence of algal species. Samples from the same year tend to be similar and group together on the plot, with some exceptions. Dispersion across the plot suggests that community structure has changed over the decades, although sampling locations in the central Arctic have also shifted, thus introducing bias. An analysis of similarity (PRIMER version 6) with a high Global R=0.80 indicates strong community difference among decades (global R=0 indicates no difference, R=1 indicates complete dissimilarity). Regional differences were low (global R=0.26) and difference by ice type moderate (global R=0.38). Grey arrows point to the very different and only two samples from 2013. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/sea-ice-biota" target="_blank">Chapter 3</a> - Page 47 - Figure 3.1.8 "For the analysis of possible interannual trends in the ice algal community, we used a data set from the Central Arctic, the area most consistently and frequently sampled (Melnikov 2002, I. Melnikov, Shirshov Institute, unpubl. data). Multivariate community structure was analysed based on a presence-absence matrix of cores from 1980 to 2013. The analysis is biased by the varying numbers of analysed cores taken per year ranging widely from 1 to 24, ice thickness between 0.6 and 4.2 m, and including both first-year as well as multiyear sea ice. Locations included were in a bounding box within 74.9 to 90.0 °N and 179.9°W to 176.6°E and varied among years."

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.

This 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 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.

Seasonal abundance (1000 individuals m- 2) of sea ice meiofauna at landfast sea ice (Barrow, 2005-2006, A and C) and pack ice (North of Svalbard, 2015, B and D). A and B show larval stages (polychaete juveniles and nauplii, respectively), while C and D show nematodes and harpacticoid copepods, respectively. Circles represent individual cores (n = 107 for A and C, and 39 for B and D), shading the extent of minimum as well as maximum values, and blue line indicates mean values. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/sea-ice-biota" target="_blank">Chapter 3</a> - Page 43 - Figure 3.1.5 From the report draft: "In addition to showing composition and peak abundance ranges, we illustrate the phenology of ice meiofauna over the ice-covered season in the entire combined data set. For this purpose, the data were normalized to the daylight hours at each location during the date of sampling using R package geosphere (Hijmans 2015) and a method described in Forsythe et al. (1995). This was necessary, because ‘spring’ arrives earlier at lower latitudes than at higher latitudes, so that using month or day of year would obscure the pan-Arctic integration of the data. Other influential factors such as snow depth, ice thickness and nutrient concentrations were not accounted for in this analysis."

Trends in kittiwake colonies 2001-2010, based on linear regression with year as the explanatory variable. Slope of the regression is red = negative trend, blue = positive trend; shaded circle = significant trend (at p<0.05), open circle = non-significant trend. Non-significant deviation from zero could imply a stable population, but in some cases was due to low sample size and low power. Provided with permission from Descamps et al. (in prep). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/seabirds" target="_blank">Chapter 3</a> - Page 135 - Figure 3.5.3 This figure is compiled from data from researchers working throughout circumpolar regions, primarily members of the Circumpolar Seabird Group, an EN of CAFF/seabirds. Dr. Sebastien Decamps conducted the analysis and produced the original figure; the full results will be available in an article in prep titled: “Descamps et al. in prep. Circumpolar dynamics of black-legged kittiwakes track large-scale environmental shifts and oceans' warming rate.” [expected submission spring 2016]. Colony population trends were analyzed using a linear regression with the year as explanatory variable. Based on slope of the regression (which cannot be exactly 0) colonies are either Declining (Slope of the regression <0) or Increasing (Slope of the regression >0). (Colonies may have had a negative but not significant slope, and could be stable but for some others, the slope is not significant due to small sample size / low power; thus we cannot say that all colonies with a non- significant slope are stable. The threshold was put at 5% to assess the significance of the trend.

Trends in abundance or diversity of sea ice biota Focal Ecosystem Components across each Arctic Marine Area. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - Chapter 4 - Page 177 - Figure 4.1