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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