Temporal patterns in % abundance of Atlantic salmon, brown trout, and anadromous Arctic charr from catch statistics in northern Norway rivers monitored from 1993 to 2016, including basins dominated by (a) rivers and (b) lakes. State of the Arctic Freshwater Biodiversity Report - Chapter 4 - Page 81- Figure 4-42

Map of Arctic Marine Areas as defined by the Circumpolar Biodiversity Monitoring Program (CBMP), with one sample finding from each area.

Trends in biomass or diversity of benthic Focal Ecosystem Components across each Arctic Marine Area. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - Chapter 4 - Page 179 - Figure 4.3

Bird and distance transect biodiversity GRID data from Barrow, Alaska-

Vegetation monitoring occurs across the Arctic, but the duration of monitoring efforts is variable and is dependent upon both study design and access to resources. Although many field studies on vegetation have been conducted in the Arctic (Figure 3-5), not all can be considered monitoring since some recorded only select measurements over limited time frames. Studies reporting on abundance and composition of vegetation reflect a larger and more widespread geographical coverage than the typically more site-limited and time-consuming phenology studies (Figure 3-5). Geographical gaps in coverage of Siberia and large parts of the Canadian Arctic are evident. STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 3 - Page 34 - Figure 3.5

The baseline survey and ongoing monitoring required to adequately describe Arctic arthropod biodiversity and to identify trends is largely lacking. Although some existing publications reporting long-term and extensive sampling exist, they are limited in species level information, taxonomic coverage and/or geographic location/extent (Figure 3-19) STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 3 - Page 44 - Figure 3.19

Ice algal community similarity of central Russian Arctic drifting stations from the 1980s to 2010s based on unpublished data by I.A. Melnikov, Shirshov Institute of Oceanology.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."

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.

Appendix 9.7 Species list with full names of liverworts of Greenland according to Damsholt (2010, unpublished) including 22 families, 50 genera and 173 species.

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.