Figure 4 12 Diatom groups from Self Organizing Maps (SOMs) in lake top sediments, showing the geographical distribution of each group (with colors representing different SOM groups). State of the Arctic Freshwater Biodiversity Report - Chapter 4 - Page 39 - Figure 4-12

Population estimates and trends for Rangifer populations of the migratory tundra, Arctic island, mountain, and forest ecotypes where their circumpolar distribution intersects the CAFF boundary. Population trends (Increasing, Stable, Decreasing, or Unknown) are indicated by shading. Data sources for each population are indicated as footnotes. STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 3 - Page 70 - Table 3.4

Taxa accumulation curves for (left) lake surface sediment samples, and (right) stream scrapes across the sub-Arctic (blue), Low Arctic (green) and High Arctic (red) ABA Arctic zones. Dashed lines represent the bounds of the 95% confidence interval of the estimate. State of the Arctic Freshwater Biodiversity Report - Chapter 4 - Page 38 - Figure 4-11

Satellite-tracked SVP drifting buoys (Sybrandy and Niiler, 1991; Niiler, 2001) provide observations of near-surface circulation at unprecedented resolution. In September 2005, the Global Drifter Array became the first fully realized component of the Global Ocean Observing System when it reached an array size of 1250 drifters. A drifter is composed of a surface float which includes a transmitter to relay data, a thermometer which reads temperature a few centimeters below the air/sea interface, and a submergence sensor used to detect when/if the drogue is lost. The surface float is tethered to a subsurface float which minimizes rectification of surface wave motion (Niiler et al., 1987; Niiler et al., 1995). This in turn is tethered to a holey sock drogue, centered at 15 m depth. The drifter follows the flow integrated over the drogue depth, although some slip with respect to this motion is associated with direct wind forcing (Niiler and Paduan, 1995). This slip is greatly enhanced in drifters which have lost their drogues (Pazan and Niiler, 2000). Drifter velocities are derived from finite differencing their raw position fixes. These velocities, and the concurrent SST measurements, are archived at <a href="http://www.aoml.noaa.gov/phod/dac/dacdata.php" target="_blank">AOML's Drifting Buoy Data Assembly Center</a> where the data are quality controlled and interpolated to 1/4-day intervals (Hansen and Herman, 1989; Hansen and Poulain, 1996). Reference: Lumpkin, R. and Z. Garraffo, 2005: Evaluating the Decomposition of Tropical Atlantic Drifter Observations. J. Atmos. Oceanic Techn. I 22, 1403-1415.

Macrofauna distribution of biomass (g wet fixed weight m-2) in the Barents Sea over three time periods: 1924-32 (Figure A), 1968-70 (Figure B) and 2003 (Figure C, constructed from original archive data, except for area south of 72° N where digitized megafaunal-data taken from Anisimova et al. (2010) was used. Adapted from Denisenko (2013). Blue boxes delineate the areas within which the zoobenthos biomass values were compared. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/benthos" target="_blank">Chapter 3</a> - Page 96- Figure 3.3.3

Figure 3-1 Long-term trends in ice duration (as days) in the River Torne (upper plot) and Lake Torneträsk (lower plot) at 68° north on the Scandinavian peninsula. Lines show smooth fit. Data source: Swedish Meteorological and Hydrological Institute. State of the Arctic Freshwater Biodiversity Report - Chapter 3 - Page 19 - Figure 3-1

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

Global catches of Greenland halibut (FAO 2015). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/marine-fishes" target="_blank">Chapter 3</a> - Page 121 - Figure 3.4.8

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.

We present the first digital seafloor geomorphic features map (GSFM) of the global ocean. The GSFM includes 131,192 separate polygons in 29 geomorphic feature categories, used here to assess differences between passive and active continental margins as well as between 8 major ocean regions (the Arctic, Indian, North Atlantic, North Pacific, South Atlantic, South Pacific and the Southern Oceans and the Mediterranean and Black Seas). The GSFM provides quantitative assessments of differences between passive and active margins: continental shelf width of passive margins (88 km) is nearly three times that of active margins (31 km); the average width of active slopes (36 km) is less than the average width of passive margin slopes (46 km); active margin slopes contain an area of 3.4 million km2 where the gradient exceeds 5°, compared with 1.3 million km2 on passive margin slopes; the continental rise covers 27 million km2 adjacent to passive margins and less than 2.3 million km2 adjacent to active margins. Examples of specific applications of the GSFM are presented to show that: 1) larger rift valley segments are generally associated with slow-spreading rates and smaller rift valley segments are associated with fast spreading; 2) polar submarine canyons are twice the average size of non-polar canyons and abyssal polar regions exhibit lower seafloor roughness than non-polar regions, expressed as spatially extensive fan, rise and abyssal plain sediment deposits – all of which are attributed here to the effects of continental glaciations; and 3) recognition of seamounts as a separate category of feature from ridges results in a lower estimate of seamount number compared with estimates of previous workers. Reference: Harris PT, Macmillan-Lawler M, Rupp J, Baker EK Geomorphology of the oceans. Marine Geology.