Marine primary productivity is not available from the NASA Ocean Color website. Currently the best product available for marine primary productivity is available through Oregon State University’s Ocean Productivity Project. A monthly global Net Primary Productivity product at 9 km spatial resolution has been selected for this analysis. The algorithm used to create the primary productivity is a Vertically Generalized Production Model (VGPM) created by Behrenfeld and Falkowski (1997). It is a “chlorophyll-based” model that estimates net primary production from chlorophyll using a temperature-dependent description of chlorophyll photosynthetic efficiency (O’Malley 2010). Inputs to the function are chlorophyll, available light, and photosynthetic efficiency.

The Arctic terrestrial food web includes the exchange of energy and nutrients. Arrows to and from the driver boxes indicate the relative effect and counter effect of different types of drivers on the ecosystem. STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 2 - Page 26- Figure 2.4

Geographic area covered by the Arctic Biodiversity Assessment and the CBMP–Terrestrial Plan. Subzones A to E are depicted as defined in the Circumpolar Arctic Vegetation Map (CAVM Team 2003). Subzones A, B and C are the high Arctic while subzones D and E are the low Arctic. Definition of high Arctic, low Arctic, and sub-Arctic follow Hohn & Jaakkola 2010. STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 1 - Page 14 - Figure 1.2

The MODIS Land Surface Temperature (LST) product provided is a monthlycomposite configured on a 0.05° Climate Model Grid (CMG). It includes both daytime andnighttime surface temperatures, taken at 11 um and 4 um (night). This product has beenscaled. To convert the raster values to a Kelvin temperature scale, multiply by a factor of 0.02.

Number of non-native plant taxa that have become naturalised across the Arctic. No naturalised non-native taxa are recorded from Wrangel Island, Ellesmere Land – northern Greenland, Anabar-Olenyok and Frans Josef Land. Modified from Wasowicz et al. 2020 STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 3 - Page 32 - Figure 3.4

The MODIS Land Cover Type product is created yearly using three landclassification schemes; the International Geosphere Biosphere Programme (IGBP)classification scheme, the Univertiy of Maryland (UMD) classification scheme, and aMODIS-derived Leaf Area Index /Fraction of Photosynthetically Active Radiation(LAI/fPAR) classification scheme (Table 3). The International Geosphere Biosphere Programme (IGBP) identifies seventeenland cover classes, including eleven natural vegetation classes, three non-vegetated landclasses, and three developed land classes. The product provided is derived using the samealgorithm as the 500 m Land Cover Type (MOD12Q1), but is on a 0.05° Climate Model Grid(CMG), that has been clipped to the pan-Arctic extent. The UMD classification scheme issimilar to the IGBP classification scheme, but it excludes the Permanent wetlands,Cropland/Natural vegetation mosaic, and the Snow and ice classes. The LAI/fPARclassification scheme is the smallest of the three, and focuses on forest structure; it only haseleven classes. All three land cover classification schemes are provided, but the IGBPclassification scheme is the most amenable to the Pan-Arctic region.

Trends and distribution of muskoxen populations based on Table 3-5. Modified from Cuyler et al. 2020. STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 3 - Page 79 - Figure 3.30

Circumpolar trends in primary productivity as indicated by the maximum Normalised Difference Vegetation Index, 1982–2017. (a) Brown shading indicates negative MaxNDVI trends, green shading indicates positive MaxNDVI trends. (b) Chart of trends for the circumpolar Arctic, Eurasia, and North America. Modified from Frost et al. 2020. STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 3 - Page 30 - Figure 3.1

Conceptual model of Arctic terrestrial mammals, showing FECs, interactions with other biotic groups and examples of drivers and attributes relevant at various spatial scales. STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 3 - Page 67 - Figure 3.28

Change in plant phenology over time based on published studies, ranging from 9 to 21 years of duration. The bars show the proportion of observations where timing of phenological events advanced (earlier) was stable or were delayed (later) over time. The darker portions of each bar represent visible decrease, stable state, or increase results, and lighter portions represent marginally significant change. The numbers above each bar indicate the number of observations in that group. Figure from Bjorkman et al. 2020. STATE OF THE ARCTIC TERRESTRIAL BIODIVERSITY REPORT - Chapter 3 - Page 31- Figure 3.3