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

=== 3.4.3 Consequences and Impacts ===

<div id="section-3-4-3-1global-climate-feedbacks"></div>

<span id="global-climate-feedbacks"></span>
==== 3.4.3.1 Global Climate Feedbacks ====

<div id="section-3-4-3-1global-climate-feedbacks-block-1"></div>

<span id="carbon-cycle"></span>
===== 3.4.3.1.1 Carbon cycle =====

Climate warming is expected to change the storage of carbon in vegetation and soils in northern regions, and net carbon transferred to the atmosphere as CO 2 and methane acts as a feedback to accelerate global climate change. There is ''high confidence'' that the northern region acted as a net carbon sink as carbon accumulated in terrestrial ecosystems over the Holocene (Loisel et al., 2014 <sup>[[#fn:r1575|1575]]</sup> ; Lindgren et al., 2018 <sup>[[#fn:r1576|1576]]</sup> ). There is ''medium evidence'' with ''low agreement'' whether changing climate in the modern period has shifted these ecosystems into net carbon sources. Syntheses of ecosystem CO 2 fluxes have alternately showed tundra ecosystems as carbon sinks or neutral averaged across the circumpolar region for the 1990s and 2000s (McGuire et al., 2012 <sup>[[#fn:r1577|1577]]</sup> ), or carbon sources over the same time period (Belshe et al., 2013 <sup>[[#fn:r1578|1578]]</sup> ). Both syntheses agree that the summer growing season is a period of net carbon uptake into terrestrial ecosystems ( ''high confidence'' ), and this uptake appears to be increasing as a function of vegetation density/biomass (Ueyama et al., 2013 <sup>[[#fn:r1579|1579]]</sup> ). The discrepancy between these syntheses may be a result of CO 2 release rates during the non-summer season that are now thought to be higher than previously estimated ( ''high confidence'' ) (Webb et al., 2016 <sup>[[#fn:r1580|1580]]</sup> ) or the separation of upland and wetland ecosystem types, which was done in one synthesis but not the other. Moisture status is a primary control over ecosystem carbon sink/source strength with wetlands more often than not still acting as annual net carbon sinks even while methane is emitted (Lund et al., 2010 <sup>[[#fn:r1581|1581]]</sup> ). Recent aircraft measurements of atmospheric CO 2 concentrations over Alaska showed that tundra regions of Alaska were a consistent net CO 2 source to the atmosphere, whereas boreal forest regions were either neutral or net CO 2 sinks for the period 2012–2014 (Commane et al., 2017 <sup>[[#fn:r1582|1582]]</sup> ). That study region as a whole was estimated to be a net carbon source of 25 ± 14 Tg CO 2 -C yr -1 averaged over the land area of both biomes for the entire study period. For comparison to projected global emissions, this would be equivalent to a net source of 0.3 Pg CO 2 -C yr -1 assuming the Alaska study region (1.6 x 10 6 km 2 ) could be scaled to the entire northern circumpolar permafrost region soil area (17.8 x 10 6 km 2 ).

The permafrost soil carbon pool is climate sensitive and an order of magnitude larger than carbon stored in plant biomass (Schuur et al., 2018 <sup>[[#fn:r1583|1583]]</sup> ) ( ''very high confidence'' ). Initial estimates were converging on a range of cumulative emissions from soils to the atmosphere by 2100, but recent studies have actually widened that range somewhat (Figure 3.11) ( ''medium confidence'' ). Expert assessment and laboratory soil incubation studies suggest that substantial quantities of C (tens to hundreds Pg C) could potentially be transferred from the permafrost carbon pool into the atmosphere under RCP8.5 (Schuur et al., 2013 <sup>[[#fn:r1584|1584]]</sup> ; Schädel et al., 2014 <sup>[[#fn:4|4]]</sup> ) . Global dynamical models supported these findings, showing potential carbon release from the permafrost zone ranging from 37–174 Pg C by 2100 under high emission climate warming trajectories, with an average across models of 92 ± 17 Pg C (mean ± SE) (Zhuang et al., 2006 <sup>[[#fn:r1585|1585]]</sup> ; Koven et al., 2011 <sup>[[#fn:r1586|1586]]</sup> ; Schaefer et al., 2011 <sup>[[#fn:r1587|1587]]</sup> ; MacDougall et al., 2012 <sup>[[#fn:r1588|1588]]</sup> ; Burke et al., 2013 <sup>[[#fn:r1589|1589]]</sup> ; Schaphoff et al., 2013 <sup>[[#fn:r1590|1590]]</sup> ; Schneider von Deimling et al., 2015 <sup>[[#fn:r1591|1591]]</sup> ). This range is generally consistent with several newer data-driven modelling approaches that estimated that soil carbon releases by 2100 (for RCP8.5) will be 57 Pg C (Koven et al., 2015 <sup>[[#fn:r1592|1592]]</sup> ) and 87 Pg C (Schneider von Deimling et al., 2015 <sup>[[#fn:r1593|1593]]</sup> ), as well as an updated estimate of 102 Pg C from one of the previous models (MacDougall and Knutti, 2016 <sup>[[#fn:r1594|1594]]</sup> ). However, the latest model runs performed with either structural enhancements to better represent permafrost carbon dynamics (Burke et al., 2017a <sup>[[#fn:r1595|1595]]</sup> ), or common environmental input data (McGuire et al., 2016 <sup>[[#fn:r1596|1596]]</sup> ) show similar soil carbon losses, but also indicate the potential for stimulated plant growth (nutrients, temperature/growing season length, CO 2 fertilisation) to offset some (Kleinen and Brovkin, 2018 <sup>[[#fn:r1597|1597]]</sup> ) or all of these losses, at least during this century, by sequestering new carbon into plant biomass and increasing carbon inputs into the surface soil (McGuire et al., 2018 <sup>[[#fn:r1598|1598]]</sup> ). These future carbon emission levels would be a significant fraction of those projected from fossil fuels with implications for allowable carbon budgets that are consistent with limiting global warming, but will also depend on how vegetation responds ( ''high confidence'' ). Furthermore, there is ''high confidence'' that climate scenarios that involve mitigation (e.g., RCP4.5) will help to dampen the response of carbon emissions from the Arctic and boreal regions.

Northern ecosystems contribute significantly to the global methane budget, but there is ''low confidence'' about the degree to which additional methane from northern lakes, ponds, wetland ecosystems, and the shallow Arctic Ocean shelves is currently contributing to increasing atmospheric concentrations. Analyses of atmospheric concentrations in Alaska concluded that local ecosystems surrounding the observation site have not changed in the exchange of methane from the 1980s until the present, which suggests that either the local wetland ecosystems are responding similarly to other northern wetland ecosystems, or that increasing atmospheric methane concentrations in northern observation sites is derived from methane coming from mid-latitudes (Sweeney et al., 2016 <sup>[[#fn:r1600|1600]]</sup> ). However, this contrasts with indirect integrated estimates of methane emissions from observations of expanding permafrost thaw lakes that suggest a release of an additional 1.6–5 Tg CH 4 yr –1 over the last 60 years (Walter Anthony et al., 2014 <sup>[[#fn:r1601|1601]]</sup> ). At the same time, there is ''high confidence'' that methane fluxes at the ecosystem to regional scale have been under-observed, in part due to the low  solubility of methane in water leading to ebullution (bubbling) flux to the atmosphere that is heterogeneous in time and space. Some new quantifications include: cold-season methane emissions that can be &gt;50% of the annual budget of terrestrial ecosystems (Zona et al., 2016 <sup>[[#fn:r1602|1602]]</sup> ); geological methane seeps that may be climate sensitive if permafrost currently serves as a cap preventing atmospheric release (Walter Anthony et al., 2012 <sup>[[#fn:r1603|1603]]</sup> ; Ruppel and Kessler, 2016 <sup>[[#fn:r1604|1604]]</sup> ; Kohnert et al., 2017 <sup>[[#fn:r1605|1605]]</sup> ); estimates of shallow Arctic Ocean shelf methane emissions where the range of estimates based on methane concentrations in air and water has widened with more observations and now ranges from 3 Tg CH 4 yr –1 (Thornton et al., 2016 <sup>[[#fn:r1606|1606]]</sup> ) to 17 Tg CH 4 yr –1 (Shakhova et al., 2013 <sup>[[#fn:r1607|1607]]</sup> ). Observations such as these underlie the fact that source estimates for methane made from atmospheric observations are typically lower than methane source estimates made from upscaling of ground observations (e.g., Berchet et al., 2016), and this problem has not improved, even at the global scale, over several decades of research (Saunois et al., 2016 <sup>[[#fn:r1608|1608]]</sup> ; Crill and Thornton, 2017 <sup>[[#fn:r1609|1609]]</sup> ).

In many of the dynamical model projections previously discussed, methane release is not explicitly represented because fluxes are small even though higher global warming potential of methane makes these emissions relatively more important than on a mass basis alone. Global models that do include methane show that emissions may already (from 2000 to 2012) be increasing at a rate of 1.2 Tg CH 4 yr –1 in the northern region as a direct response to temperature (Riley et al., 2011 <sup>[[#fn:r1610|1610]]</sup> ; Gao et al., 2013 <sup>[[#fn:r1611|1611]]</sup> ; Poulter et al., 2017 <sup>[[#fn:r1612|1612]]</sup> ). A model intercomparison study forecast northern methane emissions to increase from 18 Tg CH 4 yr –1 to 42 Tg CH 4 yr –1 under RCP8.5 by 2100 largely as a result of an increase in wetland extent (Zhang et al., 2017 <sup>[[#fn:r1613|1613]]</sup> ). However, projected methane emissions are sensitive to changes in surface hydrology (Lawrence et al., 2015 <sup>[[#fn:r1614|1614]]</sup> ) and a suite of models that were thought to perform well in high-latitude ecosystems showed a general soil drying trend even as the overall water cycle intensified (McGuire et al., 2018 <sup>[[#fn:r1615|1615]]</sup> ). Furthermore, most models described above do not include many of the abrupt thaw processes that can result in lake expansion, wetland formation, and massive erosion and exposure to decomposition of previously frozen carbon-rich permafrost, leading to ''medium confidence'' in future model projections of methane. Recent studies that addressed some of these landscape controls over future emissions projected increases in methane above the current levels on the order 10–60 Tg CH 4 yr -1 under RCP8.5 by 2100 (Schuur et al., 2013 <sup>[[#fn:r1616|1616]]</sup> ; Koven et al., 2015 <sup>[[#fn:r1617|1617]]</sup> ; Lawrence et al., 2015 <sup>[[#fn:r1618|1618]]</sup> ; Schneider von Deimling et al., 2015 <sup>[[#fn:r1619|1619]]</sup> ; Walter Anthony et al., 2018 <sup>[[#fn:r1620|1620]]</sup> ). These additional methane fluxes are projected to cause 40–70% of total permafrost-affected radiative forcing in this century even though methane emissions are much less than CO 2 by mass (Schneider von Deimling et al., 2015 <sup>[[#fn:r1621|1621]]</sup> ; Walter Anthony et al., 2018 <sup>[[#fn:r1622|1622]]</sup> ). As with total carbon emissions, there is ''high confidence'' that mitigation of anthropogenic methane sources could help to dampen the impact of increased methane emissions from the Arctic and boreal regions (Christensen et al., 2019 <sup>[[#fn:r1623|1623]]</sup> ).

<div id="section-3-4-3-1global-climate-feedbacks-block-2"></div>

<span id="energy-budget"></span>
===== 3.4.3.1.2 Energy budget =====

Warming induced reductions in the duration and extent of Arctic spring snow cover (Section 3.4.1.1) lower albedo because snow-free land reflects much less solar radiation than snow. The corresponding increase in net radiation absorption at the surface provides a positive feedback to global temperatures (Flanner et al., 2011 <sup>[[#fn:r1624|1624]]</sup> ; Qu and Hall, 2014 <sup>[[#fn:r1625|1625]]</sup> ; Thackeray and Fletcher, 2016 <sup>[[#fn:r1626|1626]]</sup> ) ( ''high confidence'' ). Estimates of increases in global net solar energy flux due to snow cover loss range from 0.10–0.22 W m –2 (± 50%; ''medium confidence'' ) depending on dataset and time period (Flanner et al., 2011 <sup>[[#fn:r1627|1627]]</sup> ; Chen et al., 2015 <sup>[[#fn:r1628|1628]]</sup> ; Singh et al., 2015 <sup>[[#fn:r1629|1629]]</sup> ; Chen et al., 2016b <sup>[[#fn:r1630|1630]]</sup> ). Sources of uncertainty include the range in observed spring snow cover extent trends (Hori et al., 2017 <sup>[[#fn:r1631|1631]]</sup> ) and the influence of clouds on shortwave feedbacks (Sedlar, 2018 <sup>[[#fn:r1632|1632]]</sup> ; Sledd and L’Ecuyer, 2019 <sup>[[#fn:r1633|1633]]</sup> ). Terrestrial snow changes also affect the longwave energy budget via altered surface emissivity (Huang et al., 2018 <sup>[[#fn:r1634|1634]]</sup> ). Climate model simulations show that changes in snow cover dominate land surface related positive feedbacks to atmospheric heating (Euskirchen et al., 2016 <sup>[[#fn:r1635|1635]]</sup> ), but regional variations in surface albedo are also influenced by vegetation (Loranty et al., 2014 <sup>[[#fn:r1636|1636]]</sup> ). There is evidence for positive sensitivity of surface temperatures to increased northern hemisphere boreal and tundra leaf area index, which contributes a positive feedback to warming (Forzieri et al., 2017 <sup>[[#fn:r1637|1637]]</sup> ).

<div id="section-3-4-3-2ecosystems-and-their-services"></div>

<span id="ecosystems-and-their-services"></span>
==== 3.4.3.2 Ecosystems and their Services ====

<div id="section-3-4-3-2ecosystems-and-their-services-block-1"></div>

<span id="vegetation"></span>
===== 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'' ).

<div id="section-3-4-3-2ecosystems-and-their-services-block-2"></div>

<span id="figure-3.11"></span>
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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>
<!-- IMG CAPTION -->
'''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 […]'''
<!-- IMG FILE -->
[[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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<div id="section-3-4-3-2ecosystems-and-their-services-block-3"></div>

<span id="wildlife"></span>
===== 3.4.3.2.2 Wildlife =====

Reindeer and caribou ( ''Rangifer tarandus'' ), through their numbers and ecological role as a large-bodied herbivores, are a key driver of Arctic ecology. The seasonal migrations that characterise ''Rangifer'' link the coastal tundra to the continental boreal forests for some herds, while others live year-round on the tundra. Population estimates and trends exist for most herds, and indicate that pan-Arctic migratory tundra ''Rangifer'' have declined from about 5 million in the 1990s to about 2 million in 2017 (Gunn, 2016 <sup>[[#fn:r1682|1682]]</sup> ; Fauchald et al., 2017a <sup>[[#fn:r1683|1683]]</sup> ) ( ''high confidence'' ). Numbers have recently increased for two Alaska herds and the Porcupine caribou herd straddling Yukon and Alaska is at a historic high.

There is ''low confidence'' in understanding the complex drivers of observed ''Rangifer'' changes. Hunting and predation (the latter exacerbated by modification of the landscape for exploration and resource extraction; Dabros et al., 2018 <sup>[[#fn:r1684|1684]]</sup> ) increase in importance as populations decline. Climate strongly influences productivity: extremes in heat, drought, winter icing and snow depth reduce ''Rangifer'' survival (Mallory and Boyce, 2017 <sup>[[#fn:r1685|1685]]</sup> ). Changes in the timing of sea ice formation have direct effects on risks during ''Rangifer'' migration via inter-island movement and connection to the mainland (Poole et al., 2010 <sup>[[#fn:r1686|1686]]</sup> ). Summer warming is changing the composition of tundra plant communities, modifying the relationship between climate, forage and ''Rangifer'' (Albon et al., 2017 <sup>[[#fn:r1687|1687]]</sup> ), which also impacts other Arctic species such as musk ox ( ''Ovibos moschatus)'' (Schmidt et al., 2015 <sup>[[#fn:r1688|1688]]</sup> ). As polar trophic systems are highly connected (Schmidt et al., 2017 <sup>[[#fn:r1689|1689]]</sup> ), changes will propagate through the ecosystem with effects on other herbivores such as geese and voles, as well as predators such as wolves (Hansen et al., 2013 <sup>[[#fn:r1690|1690]]</sup> ; Klaczek et al., 2016 <sup>[[#fn:r1691|1691]]</sup> ).

In northern Fennoscandia, there are approximately 600,000 semi-domesticated reindeer. Lichen rangelands are key to sustaining reindeer carrying capacity, with variable response to climate change: enhanced summer precipitation increases lichen biomass, while an increase in winter precipitation lowers it (Kumpula et al., 2014 <sup>[[#fn:r1692|1692]]</sup> ). Fire disturbance reduces the amount of pasture available for domestic reindeer and increases predation on herding lands (Lavrillier and Gabyshev, 2017 <sup>[[#fn:r1693|1693]]</sup> ). Later ice formation on waterbodies can impact herding activities (Turunen et al., 2016 <sup>[[#fn:r1694|1694]]</sup> ). Ice formation from rain-on-snow events is associated with population changes including cases of catastrophic mass starvation (Bartsch et al., 2010 <sup>[[#fn:r1695|1695]]</sup> ; Forbes et al., 2016 <sup>[[#fn:r1696|1696]]</sup> ), but there is no evidence of trends in rain-on-snow events (Cohen et al., 2015 <sup>[[#fn:r1697|1697]]</sup> ; Dolant et al., 2017 <sup>[[#fn:r1698|1698]]</sup> ).

Management of keystone species requires an understanding of pathogens and disease in the context of climate warming, but evidence of changing patterns across northern ecosystems (spanning terrestrial, aquatic, and marine environments) is hindered by an incomplete picture of pathogen diversity and distribution (Hoberg, 2013 <sup>[[#fn:r1699|1699]]</sup> ; Jenkins et al., 2013 <sup>[[#fn:r1700|1700]]</sup> ; Cook et al., 2017 <sup>[[#fn:r1701|1701]]</sup> ). Among ungulates, it is ''virtually certain'' that the emergence of disease attributed to nematode pathogens has accelerated since 2000 in the Canadian Arctic islands and Fennoscandia (Kutz et al., 2013 <sup>[[#fn:r1702|1702]]</sup> ; Hoberg and Brooks, 2015 <sup>[[#fn:r1703|1703]]</sup> ; Laaksonen et al., 2017 <sup>[[#fn:r1704|1704]]</sup> ; Kafle et al., 2018 <sup>[[#fn:r1705|1705]]</sup> ). Discovery of the pathogenic bacterium ''Erysipelothrix rhusiopathiae'' has been linked to massive and widespread mortality among muskoxen from the Canadian Arctic Archipelago; loss of &gt;50% of the population since 2010 may be attributable to disease interacting with extreme temperature events, although unequivocal links to climate have not been established (Kutz et al., 2015 <sup>[[#fn:r1706|1706]]</sup> ; Forde et al., 2016a <sup>[[#fn:r1707|1707]]</sup> ; Forde et al., 2016b <sup>[[#fn:r1708|1708]]</sup> ). Anthrax is projected to expand northward in response to warming, and resulted in substantial mortality events for reindeer on the Yamal Peninsula of Russia in 2016 with mobilisation of bacteria possibly from a frozen reindeer carcass or melting permafrost (Walsh et al., 2018 <sup>[[#fn:r1709|1709]]</sup> ). In concert with climate forcing, pathogens are ''very likely'' responsible for increasing mortality in Arctic ungulates (muskox, caribou/reindeer) and alteration of transmission patterns in marine food chains, broadly threatening sustainability of subsistence and commercial hunting and fishing and safety of traditional foods for northern cultures at high latitudes (Jenkins et al., 2013 <sup>[[#fn:r1710|1710]]</sup> ; Kutz et al., 2014 <sup>[[#fn:r1711|1711]]</sup> ; Hoberg et al., 2017 <sup>[[#fn:r1712|1712]]</sup> ).

<div id="section-3-4-3-2ecosystems-and-their-services-block-4"></div>

<span id="freshwater"></span>
===== 3.4.3.2.3 Freshwater =====

Climate-driven changes in seasonal ice and permafrost conditions influence water quality ( ''high confidence'' ). Shortened duration of freshwater ice cover (more light absorption, increased nutrient input) is expected to result in higher primary productivity (Hodgson and Smol, 2008 <sup>[[#fn:r1713|1713]]</sup> ; Vincent et al., 2011 <sup>[[#fn:r1714|1714]]</sup> ; Griffiths et al., 2017b <sup>[[#fn:r1715|1715]]</sup> ) and may also encourage greater methane emissions from Arctic lakes (Greene et al., 2014 <sup>[[#fn:r1716|1716]]</sup> ; Tan and Zhuang, 2015 <sup>[[#fn:r1717|1717]]</sup> ). Thaw slumps, active layer detachments and peat plateau collapse affect surface water connectivity (Connon et al., 2014 <sup>[[#fn:r1718|1718]]</sup> ) and enhance sediment, particulate and solute fluxes in river and stream networks (Kokelj et al., 2013 <sup>[[#fn:r1719|1719]]</sup> ). The transfer of enhanced nutrients from land to water (driven by active layer thickening and thermokarst processes; Abbott et al., 2015 <sup>[[#fn:r1720|1720]]</sup> ; Vonk et al., 2015 <sup>[[#fn:r1721|1721]]</sup> ) has been linked to heightened autotrophic productivity in freshwater ecosystems (Wrona et al., 2016 <sup>[[#fn:r1722|1722]]</sup> ). Still, there is ''low confidence'' in the influence of permafrost changes on dissolved organic carbon, because of competing mechanisms that influence carbon export. Permafrost thaw could contribute to the mobilisation of previously frozen organic carbon (Abbott et al., 2014 <sup>[[#fn:r1723|1723]]</sup> ; Wickland et al., 2018 <sup>[[#fn:r1724|1724]]</sup> ; Walvoord et al., 2019 <sup>[[#fn:r1725|1725]]</sup> ) thereby enhancing both particulate and dissolved organic carbon export to aquatic systems. Increased delivery of this dissolved carbon from enhanced river discharge to the Arctic Ocean (Section 3.4.3.1.2) can exacerbate regionally extreme aragonite undersaturation of shelf waters (Semiletov et al., 2016 <sup>[[#fn:r1726|1726]]</sup> ) driven by ocean uptake of anthropogenic CO 2 (Section 3.2.1.2.4). Conversely, reduced dissolved organic carbon export could accompany permafrost thaw as (1) water infiltrates deeper and has longer residence times for decomposition (Striegl et al., 2005 <sup>[[#fn:r1727|1727]]</sup> ) and (2) the proportion of groundwater (typically lower in dissolved organic carbon and higher in DIC than runoff) to total streamflow increases (Walvoord and Striegl, 2007 <sup>[[#fn:r1728|1728]]</sup> ). Increased thermokarst also has the potential to impact freshwater cycling of inorganic carbon (Zolkos et al., 2018 <sup>[[#fn:r1729|1729]]</sup> ).

Enhanced subsurface water fluxes resulting from permafrost degradation has consequences for inorganic natural and anthropogenic constituents. Emerging evidence suggests large natural stores of mercury (Schuster et al., 2018 <sup>[[#fn:r1730|1730]]</sup> ; St Pierre et al., 2018 <sup>[[#fn:r1731|1731]]</sup> ) and other trace elements in permafrost (Colombo et al., 2018 <sup>[[#fn:r1732|1732]]</sup> ) may be released upon thaw, thereby having effects (largely unknown at this point) on aquatic ecosystems. In parallel, increased development activity in the Arctic is ''likely'' to lead to enhanced local sources of anthropogenic chemicals of emerging Arctic concern, including siloxanes, parabens, flame retardants, and per- and polyfluoroalkyl substances (AMAP, 2017c <sup>[[#fn:r1733|1733]]</sup> ). For legacy pollutants, there is ''high confidence'' that black carbon and persistent organic pollutants (e.g., hexachlorocyclohexanes, polycyclic aromatic hydrocarbons, and polychlorinated biphenyls) can be transferred downstream and affect water quality (Hodson, 2014 <sup>[[#fn:r1734|1734]]</sup> ). Lakes can become sinks of these contaminants, while floodplains can be contaminated (Sharma et al., 2015).

There is ''high confidence'' that habitat loss or change due to climate change impact Arctic fishes. Thinning ice on lakes and streams changes the overwintering habitat for aquatic fauna by impacting winter water volumes and dissolved oxygen levels (Leppi et al., 2016 <sup>[[#fn:r1735|1735]]</sup> ). Surface water loss, reduced surface water connectivity among aquatic habitats, and changes to the timing and magnitude of seasonal flows (Section 3.4.1.2) result in a direct loss of spawning, feeding, or rearing habitats (Poesch et al., 2016 <sup>[[#fn:r1736|1736]]</sup> ). Changes to permafrost landscapes have reduced freshwater habitat available for fish and other aquatic biota, including aquatic invertebrates upon which the fish depend for food (Chin et al., 2016 <sup>[[#fn:r1737|1737]]</sup> ). Gullying deepens channels (Rowland et al., 2011 <sup>[[#fn:r1738|1738]]</sup> ; Liljedahl et al., 2016 <sup>[[#fn:r1739|1739]]</sup> ) that otherwise may connect lake habitats occupied by fishes. This can lead to the loss of surface water connectivity, limit fish access to key habitats, and lower fish diversity (Haynes et al., 2014 <sup>[[#fn:r1740|1740]]</sup> ; Laske et al., 2016 <sup>[[#fn:r1741|1741]]</sup> ). Small connecting stream channels, which are vulnerable to drying, provide necessary migratory pathways for fishes, allowing them to access spawning and summer rearing grounds (Heim et al., 2016 <sup>[[#fn:r1742|1742]]</sup> ; McFarland et al., 2017 <sup>[[#fn:r1743|1743]]</sup> ).

Changes to the timing, duration and magnitude of high surface flow events in early and late summer threaten Arctic fish dispersal and migration activities (Heim et al., 2016 <sup>[[#fn:r1744|1744]]</sup> ) ( ''high confidence'' ). Timing of important life history events such as spawning can become mismatched with changing stream flows (Lique et al., 2016 <sup>[[#fn:r1745|1745]]</sup> ). There is regional evidence that migration timing has shifted earlier and winter egg incubation temperature has increased for pink salmon ( ''Oncorhynchus gorbuscha'' ), directly related to warming (Taylor, 2007 <sup>[[#fn:r1746|1746]]</sup> ). While long-term, pan-Arctic data on run timing of fishes are limited, phenological shifts could create mismatches with food availability or habitat suitability in both marine and freshwater environments for anadromous species, and in freshwater environments for freshwater resident species. Changes to the Arctic growing season (Xu et al., 2013a <sup>[[#fn:r1747|1747]]</sup> ) increase the risk of drying of surface water habitats and pose a potential mismatch in seasonal availability of food in rearing habitats.

Freshwater systems across the Arctic are relatively shallow, and thus are expected to warm ( ''high confidence'' ). This may make some surface waters inhospitably warm for cold water species such as Arctic Grayling ( ''Thymallus arcticus'' ) and whitefishes ( ''Coregonus spp'' .), or may increase the risk of ''Saprolegnia'' ''fungus'' that appears to have recently spread rapidly, infecting whitefishes at much higher rates in Arctic Alaska than noted in the past (Sformo et al., 2017 <sup>[[#fn:r1748|1748]]</sup> ). High infection rates may be driven by stress or nutrient enrichment from thawing permafrost, which increases pathogen virulence with fish (Wedekind et al., 2010 <sup>[[#fn:r1749|1749]]</sup> ). Warmer water and longer growing seasons will also affect food abundance because invertebrate life histories and production are temperature and degree-day dependent (Régnière et al., 2012 <sup>[[#fn:r1750|1750]]</sup> ). Increased nutrient export from permafrost loss (Frey et al., 2007 <sup>[[#fn:r1751|1751]]</sup> ), facilitated by warmer temperatures, will ''likely'' increase food resources for consumers, but the impact on lower trophic levels within food webs is not clearly understood.

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