Effects of carbon turnover time on terrestrial ecosystem carbon storage

Yan, Yaner; Zhou, Guiyao; Jiang, Lifeng; Luo, Yiqi

doi:10.5194/bg-14-5441-2017

Cited by 35 publications

(44 citation statements)

References 60 publications

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“…Under global warming and changes in precipitation regimes (IPCC, ), the underestimated response of MTT to climate will apparently underestimate the spatial and temporal changes in MTT, thereby underestimating the change in predicted global NEP. Here, the exchange of space for time to interpret the sensitivity of MTT to climate could cause some degree of bias, as such inference cannot include certain processes like acclimation of microbial respiration to warming or shifts in plant species over time (e.g., Koven et al., ; Yan et al., ). Nonetheless, the present‐day spatial correlation between climate and MTT approximated the temporal correlation between these variables (Figure S5) and well supported this inference.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, identifying the relative contribution of this highly uncertain ecosystem trait to C sequestration has become a hot topic in C cycle research (Carvalhais et al, 2014;Todd-Brown et al, 2013;Yan, Zhou, Jiang, & Luo, 2017). We employed a systematic framework and quantified that the deviation in MTT when improperly invoking SSA directly results in a pronounced underestimation of ecosystem NEP (4.83-fold) in this large C uptake region.…”

Section: Mtt For C Cycle Researchmentioning

confidence: 99%

“…However, it is inappropriate to invoke the ideal SSA in ecosystems at dynamic disequilibrium, with the MTTs underestimated to a greater extent in young and middle-aged forests (by more than 50%) than mature forests (<20% Koven et al, 2017;Yan et al, 2017).…”

Section: Mtt For C Cycle Researchmentioning

confidence: 99%

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Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long‐term data assimilation

Ren

et al. 2019

Global Change Biology

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It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model‐data fusion framework and systematically analyzed the SSA‐induced biases using time‐series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83‐fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA‐induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young‐aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long‐term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C‐climate feedback.

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Section: Discussionmentioning

confidence: 99%

Section: Mtt For C Cycle Researchmentioning

confidence: 99%

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Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long‐term data assimilation

Ren

et al. 2019

Global Change Biology

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“…At the ecosystem scale, F out estimates can be based on R e (Carvalhais et al, 2014;Reichstein et al, 2005;Wu et al, 2018;Yan, Zhou, Jiang, & Luo, 2017), which can be further partitioned to its autotrophic and heterotrophic components (R e = R a + R h ; e.g., Grünzweig et al, 2009;Maseyk et al, 2008;Qubaja, Tatarinov, Rotenberg, & Yakir, 2019). If C removals can be accounted for (e.g., thinning and mortality records) or considered negligible (e.g., VOC flux is small), C turnover at the ecosystem (τ eco ), tree (τ tree ), and soil (τ soil ) scales in nonsteady-state systems could be estimated by inserting R e , R a , and R h , respectively, as F out in…”

Section: Fluxe S Inventory and Turnover Time Ba S I C Smentioning

confidence: 99%

Evidence for large carbon sink and long residence time in semiarid forests based on 15 year flux and inventory records

Qubaja

Grünzweig

Rotenberg

et al. 2019

Global Change Biology

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The rate of change in atmospheric CO2 is significantly affected by the terrestrial carbon sink, but the size and spatial distribution of this sink, and the extent to which it can be enhanced to mitigate climate change are highly uncertain. We combined carbon stock (CS) and eddy covariance (EC) flux measurements that were collected over a period of 15 years (2001–2016) in a 55 year old 30 km2 pine forest growing at the semiarid timberline (with no irrigating or fertilization). The objective was to constrain estimates of the carbon (C) storage potential in forest plantations in such semiarid lands, which cover ~18% of the global land area. The forest accumulated 145–160 g C m−2 year−1 over the study period based on the EC and CS approaches, with a mean value of 152.5 ± 30.1 g C m−2 year−1 indicating 20% uncertainty in carbon uptake estimates. Current total stocks are estimated at 7,943 ± 323 g C/m2 and 372 g N/m2. Carbon accumulated mostly in the soil (~71% and 29% for soil and standing biomass carbon, respectively) with long soil carbon turnover time (59 years). Regardless of unexpected disturbances beyond those already observed at the study site, the results support a considerable carbon sink potential in semiarid soils and forest plantations, and imply that afforestation of even 10% of semiarid land area under conditions similar to that of the study site, could sequester ~0.4 Pg C/year over several decades.

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“…By expressing models in this general and compact form, it is possible to better understand holistic behaviors of terrestrial carbon cycle models. For instance, the framework can be applied to better trace different components of the carbon cycle (Xia et al, ), determine timescales of different processes (Huang et al, ; Yan et al, ), determine the predictability and dynamic disequilibrium of the carbon cycle (Luo et al, ; Luo & Weng, ), and assess carbon storage capacity and potential (Jiang et al, ; Luo et al, ; Luo & Weng, ).…”

Section: Carbon Cycle Models As Dynamical Systemsmentioning

confidence: 99%

Representing and Understanding the Carbon Cycle Using the Theory of Compartmental Dynamical Systems

Sierra

Ceballos-Núñez

Metzler

et al. 2018

J Adv Model Earth Syst

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Models representing exchange of carbon between the atmosphere and the terrestrial biosphere include a large variety of processes and mechanisms, and have increased in complexity in the last decades. These models are no exception of the simulation versus understanding conundrum previously articulated for models of the physical climate, which states that increasing detail in process representation in models, and the simulations they produce, hinders understanding of holistic system behavior. However, recent theoretical progress on the mathematical representation of the carbon cycle in ecosystems may help to provide a general framework for the qualitative understanding of models without compromising detail in process representation. Here we (1) briefly review recent ideas on the theory of transient dynamics of the terrestrial carbon cycle and its matrix representation, pointing out issues of interpretation, (2) show that these ideas can be further generalized in the mathematical concept of nonautonomous compartmental systems, and (3) provide thoughts on how this framework can be used to address a new set of questions in carbon cycle science.

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Effects of carbon turnover time on terrestrial ecosystem carbon storage

Cited by 35 publications

References 60 publications

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long‐term data assimilation

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long‐term data assimilation

Evidence for large carbon sink and long residence time in semiarid forests based on 15 year flux and inventory records

Representing and Understanding the Carbon Cycle Using the Theory of Compartmental Dynamical Systems

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