scholarly journals Review of "Apparent ecosystem carbon turnover time: uncertainties and robust features"

2020 ◽  
Keyword(s):  
Turnover Time ◽  
Carbon Turnover ◽  
Ecosystem Carbon

scholarly journals Apparent ecosystem carbon turnover time: uncertainties and robust features

2020 ◽  
Vol 12 (4) ◽  
pp. 2517-2536 ◽  
Author(s):  
Naixin Fan ◽  
Sujan Koirala ◽  
Markus Reichstein ◽  
Martin Thurner ◽  
Valerio Avitabile ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Land Surface ◽  
State Of The Art ◽  
Soil Depth ◽  
Turnover Time ◽  
Latitudinal Gradients ◽  
Climate Feedback ◽  
Carbon Turnover ◽  
Total Uncertainty ◽  
Ecosystem Carbon

Abstract. The turnover time of terrestrial ecosystem carbon is an emergent ecosystem property that quantifies the strength of land surface on the global carbon cycle–climate feedback. However, observation- and modeling-based estimates of carbon turnover and its response to climate are still characterized by large uncertainties. In this study, by assessing the apparent whole ecosystem carbon turnover times (τ) as the ratio between carbon stocks and fluxes, we provide an update of this ecosystem level diagnostic and its associated uncertainties in high spatial resolution (0.083∘) using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble of data, we estimated the global median τ to be 43-7+7 yr (median-difference to percentile 25+difference to percentile 75) when the full soil is considered, in contrast to limiting it to 1 m depth. Only considering the top 1 m of soil carbon in circumpolar regions (assuming maximum active layer depth is up to 1 m) yields a global median τ of 37-6+3 yr, which is longer than the previous estimates of 23-4+7 yr (Carvalhais et al., 2014). We show that the difference is mostly attributed to changes in global Csoil estimates. Csoil accounts for approximately 84 % of the total uncertainty in global τ estimates; GPP also contributes significantly (15 %), whereas Cveg contributes only marginally (less than 1 %) to the total uncertainty. The high uncertainty in Csoil is reflected in the large range across state-of-the-art data products, in which full-depth Csoil spans between 3362 and 4792 PgC. The uncertainty is especially high in circumpolar regions with an uncertainty of 50 % and a low spatial correlation between the different datasets (0.2<r<0.5) when compared to other regions (0.6<r<0.8). These uncertainties cast a shadow on current global estimates of τ in circumpolar regions, for which further geographical representativeness and clarification on variations in Csoil with soil depth are needed. Different GPP estimates contribute significantly to the uncertainties of τ mainly in semiarid and arid regions, whereas Cveg causes the uncertainties of τ in the subtropics and tropics. In spite of the large uncertainties, our findings reveal that the latitudinal gradients of τ are consistent across different datasets and soil depths. The current results show a strong ensemble agreement on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30–60∘ N) than in the subtropical and tropical zones (30∘ S–30∘ N). Additionally, while the strength of the τ–precipitation correlation was dependent on the Csoil data source, the latitudinal gradients also agree among different ensemble members. Overall, and despite the large variation in τ, we identified robust features in the spatial patterns of τ that emerge beyond the differences stemming from the data-driven estimates of Csoil, Cveg and GPP. These robust patterns, and associated uncertainties, can be used to infer τ–climate relationships and for constraining contemporaneous behavior of Earth system models (ESMs), which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback. The dataset of τ is openly available at https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).

scholarly journals The effects of carbon turnover time on terrestrial ecosystem carbon storage

2017 ◽  
Author(s):  
Yaner Yan ◽  
Xuhui Zhou ◽  
Lifeng Jiang ◽  
Yiqi Luo
Keyword(s):  
Carbon Storage ◽  
Terrestrial Ecosystem ◽  
Turnover Time ◽  
Carbon Turnover ◽  
C Storage ◽  
Ecosystem Carbon ◽  
Scale Temperature ◽  
Key Factor ◽  
The Difference ◽  
Definition Of

Abstract. Carbon (C) turnover time is a key factor in determining C storage capacity in various plant and soil pools and the magnitude of terrestrial C sink in a changing climate. However, the effects of C turnover time on C storage have not been well quantified for previous researches. Here, we first analyzed the difference among different definition of mean turnover time (MTT) including ecosystem MTT(MTTEC) and soil MTT (MTTsoil) and its variability in MTT to climate changes, and then evaluated the changes of ecosystem C storage driven by MTT changes. Our results showed that total GPP-based ecosystem MTT (MTTEC_GPP : 25.0 ± 2.7 years) was shorter than soil MTT (35.5 ± 1.2 years) and NPP-based ecosystem MTT (MTTEC_NPP:50.8 ± 3 years) MTTEC_GPP = Cpool/GPP &amp; MTTsoil = Csoil/NPP &amp; MTTEC_NPP = Cpool/NPP, Cpool and Csoil referring as the ecosystem or soil carbon storage, respectively). At the biome scale, temperature is still the predictor for MTTEC (R2 = 0.77, p 

scholarly journals Supplementary material to "Apparent ecosystem carbon turnover time: uncertainties and robust features"

2020 ◽  
Author(s):  
Naixin Fan ◽  
Sujan Koirala ◽  
Markus Reichstein ◽  
Martin Thurner ◽  
Valerio Avitabile ◽  
...  
Keyword(s):  
Turnover Time ◽  
Carbon Turnover ◽  
Ecosystem Carbon ◽  
Supplementary Material

scholarly journals Ecosystem carbon transit versus turnover times in response to climate warming and rising atmospheric CO<sub>2</sub> concentration

2018 ◽  
Vol 15 (21) ◽  
pp. 6559-6572 ◽  
Author(s):  
Xingjie Lu ◽  
Ying-Ping Wang ◽  
Yiqi Luo ◽  
Lifen Jiang
Keyword(s):  
Steady State ◽  
Transit Time ◽  
Climate Warming ◽  
Age Structure ◽  
C Sequestration ◽  
Turnover Time ◽  
Atmospheric Co2 ◽  
Ecosystem Carbon ◽  
Subsequent Decrease ◽  
Diagnostic Time

Abstract. Ecosystem carbon (C) transit time is a critical diagnostic parameter to characterize land C sequestration. This parameter has different variants in the literature, including a commonly used turnover time. However, we know little about how different transit time and turnover time are in representing carbon cycling through multiple compartments under a non-steady state. In this study, we estimate both C turnover time as defined by the conventional stock over flux and mean C transit time as defined by the mean age of C mass leaving the system. We incorporate them into the Community Atmosphere Biosphere Land Exchange (CABLE) model to estimate C turnover time and transit time in response to climate warming and rising atmospheric [CO2]. Modelling analysis shows that both C turnover time and transit time increase with climate warming but decrease with rising atmospheric [CO2]. Warming increases C turnover time by 2.4 years and transit time by 11.8 years in 2100 relative to that at steady state in 1901. During the same period, rising atmospheric [CO2] decreases C turnover time by 3.8 years and transit time by 5.5 years. Our analysis shows that 65 % of the increase in global mean C transit time with climate warming results from the depletion of fast-turnover C pool. The remaining 35 % increase results from accompanied changes in compartment C age structures. Similarly, the decrease in mean C transit time with rising atmospheric [CO2] results approximately equally from replenishment of C into fast-turnover C pool and subsequent decrease in compartment C age structure. Greatly different from the transit time, the turnover time, which does not account for changes in either C age structure or composition of respired C, underestimated impacts of warming and rising atmospheric [CO2] on C diagnostic time and potentially led to deviations in estimating land C sequestration in multi-compartmental ecosystems.

Organic carbon turnover time in deep-sea benthos

1990 ◽  
Vol 24 (1-4) ◽  
pp. 141-160 ◽  
Author(s):  
Gilbert T Rowe ◽  
Myriam Sibuet ◽  
Jody Deming ◽  
John Tietjen ◽  
Alexis Khripounoff
Keyword(s):  
Organic Carbon ◽  
Deep Sea ◽  
Turnover Time ◽  
Carbon Turnover

scholarly journals Short organic carbon turnover time and narrow 14 C age spectra in early Holocene wetland paleosols

2017 ◽  
Vol 18 (1) ◽  
pp. 142-155 ◽  
Author(s):  
Lael Vetter ◽  
Brad E. Rosenheim ◽  
Alvaro Fernandez ◽  
Torbjörn E. Törnqvist
Keyword(s):  
Organic Carbon ◽  
Turnover Time ◽  
Early Holocene ◽  
Carbon Turnover

scholarly journals Understanding the uncertainty in global forest carbon turnover

2020 ◽  
Vol 17 (15) ◽  
pp. 3961-3989 ◽  
Author(s):  
Thomas A. M. Pugh ◽  
Tim Rademacher ◽  
Sarah L. Shafer ◽  
Jörg Steinkamp ◽  
Jonathan Barichivich ◽  
...  
Keyword(s):  
Large Scale ◽  
Tree Mortality ◽  
Forest Biomass ◽  
Turnover Time ◽  
Biomass Carbon ◽  
Carbon Turnover ◽  
Turnover Rates ◽  
Wide Range ◽  
The Future ◽  
Total Turnover

Abstract. The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985–2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth.

scholarly journals Pervasive decreases in living vegetation carbon turnover time across forest climate zones

2019 ◽  
Vol 116 (49) ◽  
pp. 24662-24667 ◽  
Author(s):  
Kailiang Yu ◽  
William K. Smith ◽  
Anna T. Trugman ◽  
Richard Condit ◽  
Stephen P. Hubbell ◽  
...  
Keyword(s):  
Tree Mortality ◽  
Temporal Trends ◽  
Turnover Time ◽  
Forest Carbon ◽  
Cold Climate ◽  
Forest Plot ◽  
Carbon Turnover ◽  
Climate Zones ◽  
Vegetation Carbon

Forests play a major role in the global carbon cycle. Previous studies on the capacity of forests to sequester atmospheric CO2 have mostly focused on carbon uptake, but the roles of carbon turnover time and its spatiotemporal changes remain poorly understood. Here, we used long-term inventory data (1955 to 2018) from 695 mature forest plots to quantify temporal trends in living vegetation carbon turnover time across tropical, temperate, and cold climate zones, and compared plot data to 8 Earth system models (ESMs). Long-term plots consistently showed decreases in living vegetation carbon turnover time, likely driven by increased tree mortality across all major climate zones. Changes in living vegetation carbon turnover time were negatively correlated with CO2 enrichment in both forest plot data and ESM simulations. However, plot-based correlations between living vegetation carbon turnover time and climate drivers such as precipitation and temperature diverged from those of ESM simulations. Our analyses suggest that forest carbon sinks are likely to be constrained by a decrease in living vegetation carbon turnover time, and accurate projections of forest carbon sink dynamics will require an improved representation of tree mortality processes and their sensitivity to climate in ESMs.

A spatial emergent constraint on the sensitivity of soil carbon turnover time to global warming

2020 ◽  
Author(s):  
Rebecca Varney ◽  
Peter Cox ◽  
Sarah Chadburn ◽  
Pierre Friedlingstein ◽  
Eleanor Burke ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Soil Carbon ◽  
Turnover Time ◽  
Carbon Turnover ◽  
Climate Change Projections ◽  
Emergent Constraint ◽  
Earth System Models ◽  
Soil Carbon Turnover ◽  
Effective Sensitivity

&lt;p&gt;Carbon cycle feedbacks represent large uncertainties on climate change projections, and the response&lt;br&gt;of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil&lt;br&gt;carbon depend on changes in litter and root inputs from plants, and especially on reductions in the&lt;br&gt;turnover time of soil carbon (&amp;#964;&lt;sub&gt;s&lt;/sub&gt;) with warming. The latter represents the change in soil carbon&lt;br&gt;due to the response of soil turnover time (&amp;#8710;C&lt;sub&gt;s,&amp;#964;&lt;/sub&gt;), and can be diagnosed from projections made with&lt;br&gt;Earth System Models (ESMs). It is found to span a large range even at the Paris Agreement Target&lt;br&gt;of 2&lt;sup&gt;&amp;#9702;&lt;/sup&gt;C global warming. We use the spatial variability of &amp;#964;&lt;sub&gt;s&lt;/sub&gt; inferred from observations to obtain a&lt;br&gt;constraint on &amp;#8710;C&lt;sub&gt;s,&amp;#964;&lt;/sub&gt; . This spatial emergent constraint allows us to greatly reduce the uncertainty in&lt;br&gt;&amp;#8710;C&lt;sub&gt;s,&amp;#964;&lt;/sub&gt; at 2&lt;sup&gt;&amp;#9702;&lt;/sup&gt;C global warming. We do likewise for other levels of global warming to derive a best&lt;br&gt;estimate for the effective sensitivity of &amp;#964;&lt;sub&gt;s&lt;/sub&gt; to global warming, and derive a q10 equivalent value for&lt;br&gt;heterotrophic respiration.&lt;/p&gt;

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