Editing IPCC:AR6/WGI/Chapter-5 (section)

=== 5.4.3 Climate Effect on Land Carbon Uptake ===

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The AR5 assessed with ''medium confidence'' that future climate change will decrease land carbon uptake relative to the case with constant climate, but with a poorly constrained magnitude (AR5 WGI, Chapter 6, Executive Summary). Ongoing uncertainty in the magnitude and geographic pattern of the feedbacks ( [[#5.4.5|Section 5.4.5]] ), continues to support a ''medium confidence'' assessment that future climate change will decrease land carbon uptake relative to the case with constant climate.

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==== 5.4.3.1 Plant Physiology ====

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Plant productivity is highly dependent on local climate. In cold environments, warming has generally led to an earlier onset of the growing season, and with it an increase in early season vegetation productivity (e.g., [[#Forkel--2016|Forkel et al., 2016]] ). However, this trend is affected by the adverse effects of climate variability, and other emerging limitations on vegetation production by water, energy and nutrients, which may gradually reduce the effects of warming ( [[#Piao--2017|Piao et al., 2017]] ; [[#Buermann--2018|Buermann et al., 2018]] ; [[#Liu--2019|Liu et al., 2019]] ). At centennial time scales, boreal forest expansion may act as a climate-driven carbon sink ( [[#Pugh--2018|Pugh et al., 2018]] ).

In tropical and temperate environments, temperature simultaneously affects the metabolic rates of photosynthetic processes within leaf tissues, as well as the vapour pressure deficit that drives transpiration, its control by leaf stomata, and the resulting soil and plant tissue water content. Thus the direct effect of warming on photosynthesis can be positive, negative, or invariant depending on the environmental context ( [[#Lin--2012|Lin et al., 2012]] ; [[#Yamori--2014|Yamori et al., 2014]] ; [[#Smith--2017|Smith and Dukes, 2017]] ; [[#Grossiord--2020|Grossiord et al., 2020]] ). Observations and models suggest that the vapour pressure deficit effects are stronger than direct temperature effects on enzyme activities ( [[#Smith--2020|Smith et al., 2020]] ), and that acclimation of photosynthetic optimal temperature may mitigate productivity losses of tropical forests under climate change ( [[#Kattge--2007|Kattge and Knorr, 2007]] ; [[#Tan--2017|Tan et al., 2017]] ; [[#Kumarathunge--2019|Kumarathunge et al., 2019]] ). Some models have begun to include these acclimation responses in photosynthesis and autotrophic respiration ( [[#Lombardozzi--2015|Lombardozzi et al., 2015]] ; [[#Smith--2015|Smith et al., 2015]] ; [[#Huntingford--2017|Huntingford et al., 2017]] ; [[#Mercado--2018|Mercado et al., 2018]] ).

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==== 5.4.3.2 Fire and Other Disturbances ====

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The SRCCL assessed that climate change is playing an increasing role in determining wildfire regimes alongside human activity ( ''medium confidence'' ), with future climate variability expected to enhance the recurrence and severity of wildfires in many biomes, such as tropical rainforests ( ''high confidence'' ). Projections of increased fire weather in a warmer climate are widespread ( [[IPCC:Wg1:Chapter:Chapter-12#12.3.2.8|Section 12.3.2.8]] ) and may drive increased fire frequency and severity in several regions, including Arctic and boreal ecosystems ( [[#Gauthier--2015|Gauthier et al., 2015]] ; X.J. [[#Walker--2019|]] [[#Walker--2019|Walker et al., 2019]] ), Mediterranean-type ecosystems ( [[#Turco--2014|Turco et al., 2014]] ; [[#Jin--2015|Jin et al., 2015]] ), degraded tropical forests ( [[#Aragão--2018|Aragão et al., 2018]] ), and tropical forest-savanna transition zones ( [[#Lehmann--2014|Lehmann et al., 2014]] ).

Wildfire is included in some CMIP6 ESMs (Table 5.4) and is thus only partially represented in estimates of carbon–climate feedbacks from these models. The CMIP5 ESMs that include fire project an 8–58% increase of fire carbon emissions under future scenarios, with higher emissions under higher warming scenarios; the ensemble spread is driven by differing factors such as population density, fire management, and other land-use processes ( [[#Kloster--2017|Kloster and Lasslop, 2017]] ). Fire dynamics in CMIP6 models, as evaluated in land-only configurations of CMIP6-generation land surface models, also show large variations but better agreement with observations ( [[#Teckentrup--2019|Teckentrup et al., 2019]] ; [[#Hantson--2020|Hantson et al., 2020]] ; [[#Lasslop--2020|Lasslop et al., 2020]] ).

Climate change also drives changes to vegetation composition and ecosystem carbon storage through other disturbances such as forest dieback that lead to biome shifts in tropical forests ( [[#Cox--2004|Cox et al., 2004]] ; [[#Jones--2009|Jones et al., 2009]] ; [[#Brando--2014|Brando et al., 2014]] ; [[#Le%20Page--2017|Le Page et al., 2017]] ; [[#Zemp--2017|Zemp et al., 2017]] ), and temperate and boreal regions ( [[#Joos--2001|Joos et al., 2001]] ; [[#Lucht--2006|Lucht et al., 2006]] ; [[#Scheffer--2012|Scheffer et al., 2012]] ; [[#Lasslop--2016|Lasslop et al., 2016]] ). The AR5 assessed that large-scale loss of tropical forests due to climate change is ''unlikely'' (WGI, Section 6.4.9). Newer ecosystem modelling approaches that include a greater degree of ecosystem heterogeneity and diversity show a reduced sensitivity of such forest dieback-type changes ( [[#Levine--2016|Levine et al., 2016]] ; [[#Sakschewski--2016|Sakschewski et al., 2016]] ), supporting the AR5 assessment ( [[#5.4.9|Section 5.4.9]] ). Beyond such biome shifts, observations of tropical forests also show that increasing tree mortality rates within tropical forests may reduce carbon turnover times and storage ( [[#Brienen--2015|Brienen et al., 2015]] ), that increased tree mortality rates in tropical forests and elsewhere are expected with increased temperatures and vapour pressure deficit (Cross-Chapter Box 5.1; [[#Allen--2015|Allen et al., 2015]] ; [[#McDowell--2018|McDowell et al., 2018]] ; [[#Grossiord--2020|Grossiord et al., 2020]] ), and that these processes are not well represented in ESMs ( [[#Powell--2013|Powell et al., 2013]] ; [[#Fisher--2018|Fisher et al., 2018]] ). An ensemble of land models that includes ecological processes such as forest demography shows that changes to mortality may be a more important driver of carbon dynamics than changes to productivity ( [[#Friend--2014|Friend et al., 2014]] ).

Overall, climate change will force widespread increases in fire weather throughout the world ( [[IPCC:Wg1:Chapter:Chapter-12#12.3.2.8|Section 12.3.2.8]] ). Because of incomplete inclusion of fire in ESMs, a separate compilation of fire-driven carbon–climate feedback estimates is shown in Figure 5.29, based on results from [[#Eliseev--2014a|Eliseev et al. (2014a)]] and [[#Harrison--2018|Harrison et al. (2018)]] . There is ''low agreement'' in magnitude and ''medium agreement'' in sign which leads to an assessment of ''medium confidence'' that fire represents a positive carbon–climate feedback, but ''very low confidence'' in the magnitude of that feedback. Other disturbances such as tree mortality will increase across several ecosystems ( ''medium agreement'' ) with decreased vegetation carbon ( ''medium confidence'' ). However, the lack of model agreement and key process representation in ESMs leads to a ''low confidence'' assessment in the projected magnitude of this feedback.

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==== 5.4.3.3 Soil Carbon ====

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Changes to soil carbon stocks in response to climate change are a potentially strong positive feedback ( [[#Cox--2000|Cox et al., 2000]] ). Since AR5 (WGI, Section 6.4.2), progress has been made in understanding soil carbon dynamics, and associated feedbacks. Advances include: (i) an increased understanding of and ability to quantify high-latitude soil carbon feedbacks (Box 5.1); (ii) increased understanding of the causes responsible for soil carbon persistence on long time scales, particularly the interactions between decomposers and soil organic matter and mineral assemblages ( [[#Kleber--2007|Kleber et al., 2007]] ; [[#Schmidt--2011|Schmidt et al., 2011]] ; [[#Luo--2016|Luo et al., 2016]] ); and (iii) increased understanding of soil carbon dynamics in subsurface layers ( [[#Hicks%20Pries--2017|Hicks Pries et al., 2017]] ; [[#Balesdent--2018|Balesdent et al., 2018]] ).

CMIP6 ESMs predict losses of soil carbon with warming, which are larger than climate-driven vegetation carbon losses ( [[#Arora--2020|Arora et al., 2020]] ). As in CMIP5 ( [[#Todd-Brown--2013|Todd-Brown et al., 2013]] ), there is also a large CMIP6 ensemble spread in climate-driven soil carbon changes, partially driven by a large spread in the current soil carbon stocks predicted by the models. In CMIP5 ESMs, much of the soil carbon losses with warming can be traced to decreased carbon inputs, with a weaker contribution from changing soil carbon lifetimes due to faster decomposition rates ( [[#Koven--2015b|Koven et al., 2015b]] ), which may be an artefact of the lack of permafrost carbon (Box 5.1). Isotopic constraints suggest that CMIP5 ESMs systematically overestimated the transient sensitivity of soil <sup>14</sup> C responses to atmospheric <sup>14</sup> C changes, implying that the models respond too quickly to changes in either inputs or turnover times, and that therefore the soil contribution to all feedbacks may be weaker than currently projected ( [[#He--2016|He et al., 2016]] ). Using natural gradients of soil carbon turnover as a constraint on long-term responses to warming suggests that both CMIP5 and CMIP6 ESMs may systematically underestimate the temperature sensitivity at high latitudes, and may overestimate the temperature sensitivity in the tropics ( [[#Koven--2017|Koven et al., 2017]] ; [[#Wieder--2018|Wieder et al., 2018]] ; [[#Varney--2020|Varney et al., 2020]] ), although experimental soil warming in tropical forests suggest high sensitivity of decomposition to warming in those regions as well ( [[#Nottingham--2020|Nottingham et al., 2020]] ).

Peat soils, where thick organic layers build up due to saturated and anoxic conditions, represent another possible source of carbon to the atmosphere. Peats could dry, and decompose or burn as a result of climate change in both high ( [[#Chaudhary--2020|Chaudhary et al., 2020]] ) and tropical ( [[#Cobb--2017|Cobb et al., 2017]] ) latitudes, and in combination with anthropogenic drainage of peatlands ( [[#Warren--2017|Warren et al., 2017]] ). Peat carbon dynamics are not included in the majority of CMIP6 ESMs. Soil microbial dynamics shift in response to temperature, giving rise to complex longer-term trophic effects that are more complex than the short-term sensitivity of decomposition to temperature. Such responses are observed in response to long-term warming experiments ( [[#Melillo--2017|Melillo et al., 2017]] ). While most CMIP6 ESMs do not include microbial dynamics, simplified global soil models that do include such dynamics show greater uncertainty in projections of soil carbon changes, despite agreeing more closely with current observations, than the linear models used in most ESMs ( [[#Wieder--2013|Wieder et al., 2013]] ; [[#Guenet--2018|Guenet et al., 2018]] ).

In nutrient-limited ecosystems, prolonged soil warming can induce a fertilization effect through increased decomposition, which increases nutrient availability and thereby vegetation productivity ( [[#Melillo--2011|Melillo et al., 2011]] ). Models that include this process tend to show a weaker carbon–climate feedback than those that do not ( [[#Thornton--2009|Thornton et al., 2009]] ; [[#Zaehle--2010|Zaehle et al., 2010]] ; [[#Wårlind--2014|Wårlind et al., 2014]] ; [[#Meyerholt--2020|Meyerholt et al., 2020]] ). In CMIP6, six out of 11 ESMs include a representation of the nitrogen cycle, and the mean of those models predicts a weaker carbon–climate feedback than the overall ensemble mean ( [[#Arora--2020|Arora et al., 2020]] ; [[#5.4.8|Section 5.4.8]] ). These models only partly account for the interactions of nutrient effects with other processes, such as shifts of vegetation zones under climate changes ( [[#Sakaguchi--2016|Sakaguchi et al., 2016]] ) leading to either changes in species composition or changes in plant tissue nutrient to carbon ratios ( [[#Thomas--2015|Thomas et al., 2015]] ; [[#Achat--2016|Achat et al., 2016]] ; [[#Du--2019|Du et al., 2019]] ).

The ''high agreement'' and multiple lines of evidence that warming increases decomposition rates lead to ''high confidence'' that warming will, overall, result in carbon losses relative to a constant climate and contribute to the positive carbon–climate feedback ( [[#5.4.8|Section 5.4.8]] ). However, the wide spread in ESM projections and the lack of model representation of key processes that may amplify or mitigate soil carbon losses on longer time scales (including microbial dynamics, permafrost, peatlands, and nutrients) lead to ''low confidence'' in the magnitude of global soil carbon losses with warming.

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'''Box 5.1 | Permafrost Carbon and Feedb''' '''acks to Climate'''

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'''What is permafrost carbon and why should we be concerned about it?'''

Soils in the Arctic and other cold regions contain perennially frozen layers, known as permafrost. Soils in the northern permafrost region store a large amount of organic carbon, estimated at 1460–1600 PgC across surface soils and deeper deposits ( [[#Hugelius--2014|Hugelius et al., 2014]] ; [[#Strauss--2017|Strauss et al., 2017]] ; [[#Mishra--2021|Mishra et al., 2021]] ). Of that carbon, permafrost soils and deposits store 1070–1360 PgC, of which 300–400 PgC are in the first metre, and the rest at depth. The remaining 280–340 PgC are in permafrost-free soils within the permafrost region. These carbon deposits have accumulated over thousands of years due to the slow rates of organic matter decomposition in frozen and/or waterlogged soil layers, but these frozen soils are highly decomposable upon thaw ( [[#Schädel--2014|Schädel et al., 2014]] ).

'''Is permafrost carbon already thawing and emitting greenhouse gases?'''
The permafrost region was a historic carbon sink over centuries to millennia ( ''high confidence'' ) ( [[#Loisel--2014|Loisel et al., 2014]] ; [[#Lindgren--2018|Lindgren et al., 2018]] ). Currently though, thawing soils due to anthropogenic warming are losing carbon from the decomposition of old frozen organic matter, as found via carbon 14 ( <sup>14</sup> C) signature of respiration at sites undergoing rapid permafrost thaw ( [[#Hicks%20Pries--2013|Hicks Pries et al., 2013]] ), of dissolved organic carbon in rivers draining watersheds with permafrost thaw ( [[#Vonk--2015|Vonk et al., 2015]] ; [[#Wild--2019|Wild et al., 2019]] ), and of methane (CH <sub>4</sub> ) produced in thawing lakes ( [[#Walter%20Anthony--2016|Walter Anthony et al., 2016]] ).

Despite accumulating evidence of increased carbon losses, it is difficult to scale up site- and ecosystem-level measurements to assess the net carbon balance over the entire permafrost region, due to the high spatial heterogeneity, the strong seasonal cycles, and the difficulty in monitoring these regions consistently across the year. The Special Report on Ocean and the Cryosphere in a Changing Climte (SROCC) assessed with ''high confidence'' that ecosystems in the permafrost region act as carbon sinks during the summer growing season, and that wintertime carbon losses are significant, consistent with a multi-decadal small increase in CO <sub>2</sub> emissions during early winter at Barrow, Alaska ( [[#Sweeney--2016|Sweeney et al., 2016]] ; [[#Webb--2016|Webb et al., 2016]] ; [[#Meredith--2019|Meredith et al., 2019]] ). These findings have been further strengthened by recent comprehensive synthesis of in-situ wintertime flux observations that show large carbon losses during the non-growing season ( [[#Natali--2019|Natali et al., 2019]] ). Increased autumn and winter respiration are a key large-scale fingerprint of top-down permafrost thaw predicted by ecosystem models ( [[#Parazoo--2018|Parazoo et al., 2018]] ). However, the length of these wintertime observational records is too short to unequivocally determine whether winter carbon losses are higher now than they used to be. One study inferred a multi-year net CO <sub>2</sub> source for the tundra in Alaska ( [[#Commane--2017|Commane et al., 2017]] ), which is equivalent to 0.3 PgC yr <sup>–1</sup> when scaled up to the northern permafrost region ( ''low confidence'' ) ( [[#Meredith--2019|Meredith et al., 2019]] ).

Since AR5, evidence of a more active carbon cycle in the northern high-latitude regions has also been observed through the increased amplitude of CO <sub>2</sub> seasonal cycles. However, the relative roles of local sources versus influence from mid-latitudes makes it difficult to infer changes to Arctic ecosystems from these observations ( [[#Graven--2013|Graven et al., 2013]] ; [[#Forkel--2016|Forkel et al., 2016]] ; [[#Takata--2017|Takata et al., 2017]] ; [[#Bruhwiler--2021|Bruhwiler et al., 2021]] ). Estimates of CO <sub>2</sub> fluxes with atmospheric inversion models showed an enhanced seasonal cycle amplitude but no significant trends in annual total fluxes, in agreement with flux tower measurements over one decade (2004–2013) ( [[#Welp--2016|Welp et al., 2016]] ; [[#Takata--2017|Takata et al., 2017]] ).

In addition to CO <sub>2</sub> , CH <sub>4</sub> emissions from the northern permafrost region contribute to the global methane budget, but evidence as to whether these emissions have increased from thawing permafrost is mixed. The SROCC assigned ''low confidence'' to the degree of recent additional CH <sub>4</sub> emissions from diverse sources throughout the permafrost region. These include observed regional lake area change, which suggest a 1.6–5 Tg CH <sub>4</sub> yr <sup>–1</sup> increase over the last 50 years ( [[#Walter%20Anthony--2016|Walter Anthony et al., 2016]] ), ice-capped geological sources ( [[#Walter%20Anthony--2012|Walter Anthony et al., 2012]] ; [[#Kohnert--2017|Kohnert et al., 2017]] ), and shallow Arctic Ocean shelves. The shallow subsea emissions are particularly uncertain due to the wide range of estimates (3 Tg CH <sub>4</sub> yr <sup>–1</sup> ( [[#Thornton--2016b|Thornton et al., 2016b]] ) <sup></sup> to 17 Tg CH <sub>4</sub> yr <sup>–1</sup> ( [[#Shakhova--2014|Shakhova et al., 2014]] )), and the lack of a baseline with which to infer any changes; however, the upper half of this range in flux estimates is inconsistent with the atmospheric inversions constrained by the pan-Arctic CH <sub>4</sub> concentration measurements ( [[#Berchet--2016|Berchet et al., 2016]] ).

Atmospheric measurements and inversions performed at the global and regional scales do not show any detectable trends in annual mean CH <sub>4</sub> emissions from the permafrost region over the past 30 years ( [[#Jackson--2020|Jackson et al., 2020]] ; [[#Saunois--2020|Saunois et al., 2020]] ; [[#Bruhwiler--2021|Bruhwiler et al., 2021]] ), consistent with atmospheric measurements in Alaska that showed no significant annual trends, despite significant increase in air temperature ( [[#Sweeney--2016|Sweeney et al., 2016]] ). Atmospheric inversions and biospheric models do not show any clear trends in CH <sub>4</sub> emissions for wetland regions of the high latitudes during the period 2000–2016 ( [[#Patra--2016|Patra et al., 2016]] ; [[#Poulter--2017|Poulter et al., 2017]] ; [[#Jackson--2020|Jackson et al., 2020]] ; [[#Saunois--2020|Saunois et al., 2020]] ). Large uncertainties on wetland extent and limited data constraints place ''low confidence'' in these modelling approaches.

The SROCC also assessed with ''high confidence'' that CH <sub>4</sub> fluxes have been under-observed due to their high variability at multiple scales in both space and time, and that there is a persistent mismatch between top-down and bottom-up methane budgets, with emissions calculated by upscaling ground observations typically higher than emissions inferred from large-scale atmospheric observations ( [[#Thornton--2016a|Thornton et al., 2016a]] ; [[#Saunois--2020|Saunois et al., 2020]] ).

In conclusion, there is ''high confidence'' that the permafrost region has acted as a historic carbon sink over centuries to millennia, and ''high confidence'' that some permafrost regions are currently net sources of CO <sub>2</sub> . There is ''robust evidence'' that some CH <sub>4</sub> emissions sources for some regions have increased over the past decades ( ''medium confidence'' ). For the northern permafrost-wide region, no multi-decadal trend has been detected on CO <sub>2</sub> and CH <sub>4</sub> fluxes but, given the low resolution and sparse observations of current observations and modelling sytems, we place ''low confidence'' in this statement.

Since AR5, there have been new studies showing that permafrost thaw also leads to nitrous oxide (N <sub>2</sub> O) release from soil ( [[#Abbott--2015|Abbott and Jones, 2015]] ; [[#Karelin--2017|Karelin et al., 2017]] ; [[#Wilkerson--2019|Wilkerson et al., 2019]] ), a previously unaccounted source. However, this release is unquantified at the pan-Arctic scale.

'''What does the paleo record tell us?'''

Large areas of Alaska and Siberia are underlain by frozen, glacial-age, ice- and carbon-rich deposits, and many of these areas show evidence of thermokarst processes during Holocene warm periods. Rapid warming of high northern latitudes contributed to permafrost thaw, liberating labile organic carbon tothe atmosphere ( [[#Köhler--2014|Köhler et al., 2014]] ; [[#Crichton--2016|Crichton et al., 2016]] ; [[#Winterfeld--2018|Winterfeld et al., 2018]] ; [[#Meyer--2019|Meyer et al., 2019]] ), supporting the vulnerability of these areas to further warming ( [[#Strauss--2013|Strauss et al., 2013]] , 2017).

Radiogenic and stable isotopic measurements on CH <sub>4</sub> trapped in Antarctic ice support the view that CH <sub>4</sub> emissions from fossil carbon reservoirs, including permafrost and methane hydrates, remained small in response to the deglacial warming. Mass-balance calculations reveal that geological CH <sub>4</sub> emissions have not exceeded 19 Tg yr <sup>–1</sup> , highlighting that the deglacial increase in CH <sub>4</sub> emissions was predominantly related to contemporary CH <sub>4</sub> emissions from tropical wetlands and seasonally inundated floodplains ( [[#Bock--2017|Bock et al., 2017]] ; [[#Petrenko--2017|Petrenko et al., 2017]] ; [[#Dyonisius--2020|Dyonisius et al., 2020]] ). Isotopic constraints on CO <sub>2</sub> losses from permafrost with warming after the Last Glacial Maximum (LGM) are weaker than for CH <sub>4</sub> . While the biosphere as a whole held less carbon during the LGM than the pre-industrial, that change in stocks was smaller than the change in plant productivity, and so carbon losses at high latitudes may have been offset by increased tropical productivity in response to warming during the Last Deglacial Transition (LDT; [[#Ciais--2012|Ciais et al., 2012]] ). There is also paleoclimate evidence for processes that mitigate carbon losses with warming on longer time scales, such as longer-term carbon accumulation in lake deposits following thermokarst thaw ( [[#Walter%20Anthony--2014|Walter Anthony et al., 2014]] ), and long-term accumulation of carbon in permafrost soils following LDT carbon loss ( [[#Lindgren--2018|Lindgren et al., 2018]] ), particularly in peatlands which accumulated carbon at a slow but persistent rate in warm paleoclimates ( [[#Treat--2019|Treat et al., 2019]] ).

In conclusion, several independent lines of evidence indicate that permafrost thaw did not release vast quantities of fossil CH <sub>4</sub> associated with the transient warming events of the LDT. This suggests that large emissions of CH <sub>4</sub> from old carbon sources will not occur in response to future warming ( ''medi'' ''um confidence'' ).

'''What level of emissions do we expect in the future?'''

Near-surface permafrost is projected to decrease significantly under future global warming scenarios ( ''high confidence'' ) ( [[IPCC:Wg1:Chapter:Chapter-9#9.5.2|Section 9.5.2]] ), thus creating the potential for releasing CO <sub>2</sub> and CH <sub>4</sub> to the atmosphere, and act as a positive carbon–climate feedback.

The processes that govern permafrost carbon loss are grouped into gradual and abrupt mechanisms. Gradual processes include the deepening of the seasonally thawed active layer into perennially frozen permafrost layers and lengthening of the thawed season within the active layer, which increases the amount of organic carbon that is thawed and the duration of thaw. Abrupt thaw processes include ice-wedge polygon degradation, hillslope collapse, thermokarst lake expansion and draining, all of which are processes largely occurring in regions with very high soil carbon content ( [[#Olefeldt--2016a|Olefeldt et al., 2016a]] , b). Abrupt thaw processes can contribute up to half of the total net greenhouse gas release from permafrost loss, the rest attributed to gradual thaw ( [[#Schneider%20von%20Deimling--2015|Schneider von Deimling et al., 2015]] ; [[#Turetsky--2020|Turetsky et al., 2020]] ). Increased fire frequency and severity ( [[#Hu--2010|Hu et al., 2010]] ) also contributes to abrupt emissions and the removal of the insulating cover which leads to an acceleration of permafrost thaw ( [[#Genet--2013|Genet et al., 2013]] ). Ecological feedbacks can both mitigate and amplify carbon losses: nutrient release from increased organic matter decomposition can drive vegetation growth that partially offsets soil carbon losses ( [[#Salmon--2016|Salmon et al., 2016]] ), but also lead to biophysical feedbacks that further amplify warming ( [[#Myers-Smith--2011|Myers-Smith et al., 2011]] ).

Through the Coupled Model Intercomparison Project Phase 5 (CMIP5), Earth system models (ESMs) had not included permafrost carbon dynamics. This remains largely true in Coupled Model Intercomparison Project Phase 6 (CMIP6), with most models not representing permafrost carbon processes, a small number representing the active-layer thickening effect on decomposition (Table 5.4), and no ESMs representing thermokarst or fire-permafrost-carbon interactions. The CMIP6 ensemble mean predicts a negative carbon–climate feedback in the permafrost region. However, those that do include permafrost carbon show a positive carbon–climate feedback in the permafrost region (Figure 5.27). Given the current limited ESM capacity to assess permafrost feedbacks, estimates in this report are based on published permafrost-enabled land surface model results.

The SROCC assessed that warming under a high-emissions scenario (RCP8.5 or similar) would result in a loss of permafrost carbon by 2100 of 10s to 100s of PgC, with a maximum estimate of 240 PgC and a best estimate of 92 ± 17 PgC ( [[#Meredith--2019|Meredith et al., 2019]] ; SROCC, Figure 3.11). Under lower emissions scenarios, [[#Schneider%20von%20Deimling--2015|Schneider von Deimling et al. (2015)]] estimated permafrost feedbacks of 20–58 PgC of CO <sub>2</sub> by 2100 under an RCP2.6 scenario, and 28–92 PgC of CO <sub>2</sub> under an RCP4.5 scenario.

This new assessment, based on studies included in or published since SROCC ( [[#Schaefer--2014|Schaefer et al., 2014]] ; [[#Koven--2015c|Koven et al., 2015c]] ; [[#Schneider%20von%20Deimling--2015|Schneider von Deimling et al., 2015]] ; [[#Schuur--2015|Schuur et al., 2015]] ; [[#MacDougall--2016a|MacDougall and Knutti, 2016a]] ; [[#Gasser--2018|Gasser et al., 2018]] ; [[#Yokohata--2020|Yokohata et al., 2020]] ), estimates that the permafrost CO <sub>2</sub> feedback per degree of global warming (Figure 5.29) is 18 [3.1 to 41, 5–95% range] PgC °C <sup>–1</sup> . The assessment is based on a wide range of scenarios evaluated at 2100, and an assessed estimate of the permafrost CH <sub>4</sub> -climate feedback at 2.8 [0.7 to 7.3] PgCeq °C <sup>–1</sup> (Figure 5.29). This feedback affects the remaining carbon budgets for climate stabilization and is included in their assessment ( [[#5.5.2|Section 5.5.2]] ).

Beyond 2100, models suggest that the magnitude of the permafrost carbon feedback strengthens considerably over the period 2100–2300 under a high-emissions scenario ( [[#Schneider%20von%20Deimling--2015|Schneider von Deimling et al., 2015]] ; [[#McGuire--2018|McGuire et al., 2018]] ). [[#Schneider%20von%20Deimling--2015|Schneider von Deimling et al. (2015)]] estimated that thawing permafrost could release 20–40 PgC of CO <sub>2</sub> in the period from 2100 to 2300 under an RCP2.6 scenario, and 115–172 PgC of CO <sub>2</sub> under an RCP8.5 scenario. The multi-model ensemble ( [[#McGuire--2018|McGuire et al., 2018]] ) projects a much wider range of permafrost soil carbon losses of 81–642 PgC (mean 314 PgC) for an RCP8.5 scenario from 2100 to 2300, and of a gain of 14 PgC to a loss of 54 PgC (mean loss of 17 PgC) for an RCP4.5 scenario over the same period.

Methane release from permafrost thaw (including abrupt thaw) under a high-warming RCP8.5 scenario has been estimated at 836–2614 Tg CH <sub>4</sub> over the 21st century and 2800–7400 Tg CH <sub>4</sub> from 2100–2300 ( [[#Schneider%20von%20Deimling--2015|Schneider von Deimling et al., 2015]] ), and as 5300 Tg CH <sub>4</sub> over the 21st century and 16,000 Tg CH <sub>4</sub> from 2100–2300 ( [[#Turetsky--2020|Turetsky et al., 2020]] ). For RCP4.5, these numbers are 538–2356 Tg CH <sub>4</sub> until 2100 and 2000–6100 Tg CH <sub>4</sub> from 2100–2300 ( [[#Schneider%20von%20Deimling--2015|Schneider von Deimling et al., 2015]] ), and 4100 Tg CH <sub>4</sub> until 2100 and 10,000 Tg CH <sub>4</sub> from 2100–2300 ( [[#Turetsky--2020|Turetsky et al., 2020]] ).

A key uncertainty is whether permafrost carbon feedbacks scale roughly linearly with warming ( [[#Koven--2015c|Koven et al., 2015c]] ), or instead scale at a greater ( [[#MacDougall--2016b|MacDougall and Knutti, 2016b]] ; [[#McGuire--2018|McGuire et al., 2018]] ) or smaller rate (e.g., CH <sub>4</sub> emissions estimated by [[#Turetsky--2020|Turetsky et al., 2020]] ). It alsoremains unclear whether the permafrost carbon pool represents a coherent global tipping element of the Earth system with a single abrupt threshold ( [[#Drijfhout--2015|Drijfhout et al., 2015]] ) at a given level of global warming, or a local scale tipping point without abrupt thresholds when aggregated across the pan-Arctic region, as is suggested by recent model results (e.g., [[#Koven--2015a|Koven et al., 2015a]] ; [[#McGuire--2018|McGuire et al., 2018]] ).

In conclusion, thawing terrestrial permafrost will lead to carbon release under a warmer world ( ''high confidence'' ). However, there is ''low confidence'' on the timing, magnitude and linearity of the permafrost climate feedback owing to the wide range of published estimates and the incomplete knowledge and representation in models of drivers and relationships. It is projected that CO <sub>2</sub> released from permafrost will be 18 (3.1–41) PgC °C <sup>–1</sup> by 2100, with the relative contribution of CO <sub>2</sub> vs CH <sub>4</sub> remaining poorly constrained. Permafrost carbon feedbacks are included among the under-represented feedbacks quantified in Figure 5.29.

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