Arctic Ecologically and Biologically Significant Areas (EBSAs) and Arctic Marine Areas of Heightened Ecological and Cultural Significance as identified in the Arctic Marine Shipping Assessment (AMSA) IIC report. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 1</a> - Page 16 - Box Figure 1.1

Critical to the successful implementation of EBM in the Arctic is the existence of a cohesive circumpolar approach to the collection and management of data and the application of compatible frameworks, standards and protocols that this entails. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 2</a> - Page 29 - Box Figure 2.2

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.

Average September sea ice extent in 1979 (blue) compared with 2016 (white) and the median sea ice extent (yellow line) from 1981 to 2010 (Data: NSDIC 2016). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 2</a> - Page 27 - Figure 2.4

Figure 3.2.1a: Map of high throughput sequencing records from the Arctic Marine Areas. Figure 3.2.1b: Map of records of phytoplankton taxa using microscopy from the Arctic Marine Areas. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/plankton" target="_blank">Chapter 3</a> - Page 35 - Figure 3.2.1a and Figure 3.2.1b In terms of stations sampled, the greatest sampling effort of high-throughput sequencing in Arctic marine water columns, by far, has been in the Beaufort Sea/Amundsen Gulf region and around Svalbard. High through-put sequencing has also been used on samples from the Chukchi Sea, Canadian Arctic Archipelago, Baffin Bay, Hudson Bay, the Greenland Sea and Laptev Sea.

Benthic macro-infauna biomass in the northern Bering and Chukchi Seas from 1970 to 2012, displayed as decadal pattern Adapted from Grebmeier et al. (2015a) with permission from Elsevier. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/benthos" target="_blank">Chapter 3</a> - Page 98 - Figure 3.3.6 Cumulative scores of benthos drivers for each of the 8 CAFF-AMAs. The cumulative scores are taken from the last column of Table 3.3.1. The flower chart/plot helps to visualize the data.

Abundance (birds/km2) of least auklets in four regions (see map) of the eastern Chukchi Sea, 1975-1981 and 2007-2012, based on at-sea surveys (archived in the North Pacific Pelagic Seabird Database). Figures provided by Adrian Gall, ABR, Inc. and reprinted with permission. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/seabirds" target="_blank">Chapter 3</a> - Page 138 - Box fig. 3.5.1 The shapefile outlines 4 regions of the eastern Chukchi Sea that were surveyed for seabirds during the open-water seasons of 1976-2012. We compared the density of seabirds in these regions among two time periods (1975-1981 and 2008-2012) to assess changes in seabird abundance over the past 4 decades. We also include a figure showing abundance of Least Auklets 1975-2012. Data are from the North Pacific Pelagic Seabird Database, maintained by the USGS (http://alaska.usgs.gov/science/biology/nppsd/index.php).

Sea ice meiofauna composition (pie charts) and total abundance (red circles) across the Arctic, compiled by the CBMP Sea Ice Biota Expert Network from 27 studies between 1979 and 2015. Scaled circles show total abundance per individual ice core while pie charts show average relative contribution by taxon per Arctic Marine Area (AMA). Number of ice cores for each AMA is given in parenthesis after region name. Note that studies were conducted at different times of the year, with the majority between March and August (see 3.1 Appendix). The category ‘other’ includes young stages of bristle worms (Polychaeta), mussel shrimps (Ostracoda), forams (Foraminifera), hydroid polyps (Cnidaria), comb jellies (Ctenophora), sea butterflies (Pteropoda), marine mites (Acari) and unidentified organisms. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/sea-ice-biota" target="_blank">Chapter 3</a> - Page 40 - Figure 3.1.4 From the report draft: "Here, we synthesized 19 studies across the Arctic conducted between 1979 and 2015, including unpublished sources (B. Bluhm, R. Gradinger, UiT – The Arctic University of Norway; H. Hop, Norwegian Polar Institute; K. Iken, University of Alaska Fairbanks). These studies sampled landfast sea ice and offshore pack ice, both first- and multiyear ice (Appendix 3.1). Meiofauna abundances reported in individual data sources were converted to individuals m-2 of sea ice assuming that ice density was 95% of that in melted ice. Due to the low taxonomic resolution in the reviewed studies, ice meiofauna were grouped into: Copepoda, nauplii (for copepods as well as other taxa with naupliar stages), Nematoda, Polychaeta (mostly juveniles, but also trochophores), flatworms (Acoelomorpha and Platyhelminthes; these phyla have mostly been reported as one category), Rotifera, and others (which include meroplanktonic larvae other than Polychaeta, Ostracoda, Foraminifera, Cnidaria, Ctenophora, Pteropoda, Acari, and unidentified organisms). Percentage of total abundance for each group was calculated for each ice core, and these percentages were used for regional averages. Maximum available ice core length was used in data analysis, but 50% of these ice cores included only the bottom 10 cm of the ice, 12% the bottom 5 cm, 10% the bottom 2 cm, and 11% the entire ice-thickness. Data from 617 cores were used."