Editing IPCC:AR6/SROCC/Chapter-3 (section)

===== 3.4.3.2.1 Vegetation =====

Changes in tundra vegetation can have important ecosystem effects, in particular on hydrology, carbon and nutrient cycling and surface energy balance, which together impact permafrost (e.g., Myers-Smith and Hik, 2013; Frost and Epstein, 2014 <sup>[[#fn:r1638|1638]]</sup> ; Nauta et al., 2014 <sup>[[#fn:r1639|1639]]</sup> ). Aside from physical impacts, changing vegetation influences the diversity and abundance of herbivores (e.g., Fauchald et al., 2017b; Horstkotte et al., 2017 <sup>[[#fn:r1640|1640]]</sup> ) in the Arctic. The overall trend for tundra vegetation across the 36–year satellite period (1982–2017) shows increasing above ground biomass (greening) throughout a majority of the circumpolar Arctic ( ''high confidence'' ) (Xu et al., 2013a <sup>[[#fn:r1641|1641]]</sup> ; Ju and Masek, 2016 <sup>[[#fn:r1642|1642]]</sup> ; Bhatt et al., 2017 <sup>[[#fn:r1643|1643]]</sup> ). Increasing greenness has been in some cases linked with shifts in plant species dominance away from graminoids (grasses and sedges) towards shrubs ( ''high confidence'' ) (Myers-Smith et al., 2015 <sup>[[#fn:r1644|1644]]</sup> ). Within the overall trend of increases (greening), some tundra areas show declines (browning) (Bhatt et al., 2017).

The spatial variation in greening and browning trends in tundra are also not consistent over time (decadal scale) and can vary across landform/ecosystem types (Lara et al., 2018 <sup>[[#fn:r1645|1645]]</sup> ), suggesting interactions between the changing environment and the biological components of the system that control these trends. There is ''high confidence'' that increases in summer, spring and winter temperatures lead to tundra greening, as well as increases in growing season length (e.g., Vickers et al., 2016; Myers-Smith and Hik, 2018 <sup>[[#fn:r1646|1646]]</sup> ) that are in part linked to reductions in Arctic Ocean sea ice cover (Bhatt et al., 2017 <sup>[[#fn:r1647|1647]]</sup> ; Macias-Fauria et al., 2017 <sup>[[#fn:r1648|1648]]</sup> ). Other factors that stimulate tundra greening include increases in snow water equivalent and soil moisture (Westergaard-Nielsen et al., 2017 <sup>[[#fn:r1649|1649]]</sup> ), increases in active layer thickness (via nutrient availability or changes in moisture), changes in herbivore activity, and to a lesser degree, human use of the land (e.g., Salmon et al., 2016; Horstkotte et al., 2017; Martin et al., 2017; Yu et al., 2017). Research on tundra browning is more limited but suggests causal mechanisms that include changes in winter climate—specifically reductions in snow cover due to winter warming events that expose tundra to subsequent freezing and desiccation—, insect and pathogen outbreaks, increased herbivore grazing and ground ice melting and subsidence that increases surface water (Phoenix and Bjerke, 2016; Bjerke et al., 2017) ( ''medium confidence'' ).

Projections of tundra vegetation distribution across the Arctic by 2050 in response to changing environmental conditions suggest that the areal extent of most tundra types will decrease by at least 50% (Pearson et al., 2013) ( ''medium confidence'' ). Woody shrubs and trees are projected to expand to cover 24–52% of the current tundra region by 2050, or 12–33% if tree dispersal is restricted. Adding to this, the expansion of fire into tundra that has not experienced large-scale disturbance for centuries causes large reductions in soil carbon stocks (Mack et al., 2011), shifts in vegetation composition and productivity (Bret-Harte et al., 2013), and can lead to widespread permafrost degradation (Jones et al., 2015a) at faster rates than would occur by changing environmental conditions alone. In tundra regions, graminoid (grasses and sedges) tundra is projected to be replaced by more flammable shrub tundra in future climate scenarios, and tree migration into tundra could further increase fuel loading (Pastick et al., 2017) ( ''medium confidence'' ).

Similar to tundra, boreal forest vegetation shows trends of both greening and browning over multiple years in different regions across the satellite record (Beck and Goetz, 2011; Ju and Masek, 2016) ( ''high confidence'' ). Here, patterns of changing vegetation are a result of direct responses to changes in climate (temperature, precipitation and seasonality) and other driving factors for vegetation (nutrients, disturbance) similar to what has been reported in tundra. While boreal forest may expand at the northern edge (Pearson et al., 2013), climate projections suggest that it could diminish at the southern edge and be replaced by lower biomass woodland/shrublands (Koven, 2013; Gauthier et al., 2015) ( ''medium confidence'' ). Furthermore, changes in fire disturbance are leading to shifts in landscape distribution of early and late successional ecosystem types, which is also a major factor in satellite trends. Fires that burn deeply into the organic soil layer can alter permafrost stability, hydrology and vegetation. Loss of the soil organic layer exposes mineral soil seedbeds (Johnstone et al., 2009), leading to recruitment of deciduous tree and shrub species that do not establish on organic soil (Johnstone et al., 2010). This recruitment has been shown to shift post-fire vegetation to alternate successional trajectories (Johnstone et al., 2010). Model projections suggest that Alaskan boreal forest soon may cross a point where recent increases in fire activity have made deciduous stands as abundant as spruce stands on the landscape (Mann et al., 2012) ( ''medium confidence'' ). This projected trend of increasing deciduous forest at the expense of evergreen forest is mirrored in Russian and Chinese boreal forests as well (Shakhova et al., 2013; Shuman et al., 2015; Wu et al., 2017) ( ''medium confidence'' ).

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'''Figure 3.11'''

<span id="figure-3.11-estimates-of-cumulative-net-soil-carbon-pool-change-for-the-northern-circumpolar-permafrost-region-by-2100-following-medium-and-high-emission-scenarios-e.g.-representative-concentration-pathway-rcp4.5-and-rcp8.5-or-equivalent.-cumulative-carbon-amounts-are-shown-in-gigatons-c-1-gt-c1-billion-metric-tonnes-with-source-negative-values-indicating-net-carbon"></span>
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'''Figure 3.11 | Estimates of cumulative net soil carbon pool change for the northern circumpolar permafrost region by 2100 following medium and high emission scenarios (e.g., Representative Concentration Pathway (RCP)4.5 and RCP8.5 or equivalent). Cumulative carbon amounts are shown in Gigatons C (1 Gt C=1 billion metric tonnes), with source (negative values) indicating net carbon […]'''
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[[File:3a8fa4a00a17dd1acc4f3014b3ee2577 IPCC-SROCC-CH_3_11.jpg]]

Figure 3.11 | Estimates of cumulative net soil carbon pool change for the northern circumpolar permafrost region by 2100 following medium and high emission scenarios (e.g., Representative Concentration Pathway (RCP)4.5 and RCP8.5 or equivalent). Cumulative carbon amounts are shown in Gigatons C (1 Gt C=1 billion metric tonnes), with source (negative values) indicating net carbon movement from soil to the atmosphere and sink (positive values) indicating the reverse. Some data-constrained models differentiated CO2 and CH4; bars show total carbon by weight, paired bars with * indicate CO2-equivalent, which takes into account the global warming potential of CH4. Ensemble mean bars refer to the model average for the Permafrost Carbon Model Intercomparison Project [5 models]. Bars that do not start at zero are in part informed by expert assessment and are shown as ranges; all other bars represent model mean estimates. Data are from 1 (Schuur et al., 2013 <sup>[[#fn:r1650|1650]]</sup> ); 2 (Schaefer et al., 2014 <sup>[[#fn:r1651|1651]]</sup> ) [8 models]; 3 (Schuur et al., 2015 <sup>[[#fn:r1652|1652]]</sup> ); 4 (Koven et al., 2015 <sup>[[#fn:r1653|1653]]</sup> ; Schneider von Deimling et al., 2015 <sup>[[#fn:r1654|1654]]</sup> ; Walter Anthony et al., 2018 <sup>[[#fn:r1655|1655]]</sup> ); 5 (MacDougall and Knutti, 2016 <sup>[[#fn:r1656|1656]]</sup> ; Burke et al., 2017a <sup>[[#fn:r1657|1657]]</sup> ; Kleinen and Brovkin, 2018 <sup>[[#fn:r1658|1658]]</sup> ); 6 (McGuire et al., 2018 <sup>[[#fn:r1659|1659]]</sup> ).

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