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Bayesian calibration of a soil organic carbon model using delta14C measurements of soil organic carbon and heterotrophic respiration as joint constraints

MPG-Autoren
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Ahrens,  Bernhard
Soil Processes, Dr. Marion Schrumpf, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Reichstein,  Markus
Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Muhr,  Jan
Tree Reserve Carbon Pools, Dr. J. Muhr, Department Biogeochemical Processes, Prof. S. E. Trumbore, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Trumbore,  Susan E.
Department Biogeochemical Processes, Prof. S. E. Trumbore, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Wutzler,  Thomas
Soil Processes, Dr. Marion Schrumpf, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zitation

Ahrens, B., Reichstein, M., Borken, W., Muhr, J., Trumbore, S. E., & Wutzler, T. (2014). Bayesian calibration of a soil organic carbon model using delta14C measurements of soil organic carbon and heterotrophic respiration as joint constraints. Biogeosciences, 11(8), 2147-2168. doi:10.5194/bg-11-2147-2014.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0014-4C0C-6
Zusammenfassung
Soils of temperate forests store significant amounts of organic matter and are considered
to be net sinks of atmospheric CO2. Soil organic carbon (SOC) turnover has been
studied using the É14C values of bulk SOC or different SOC fractions as observational
constraints in SOC models. Further, the É14 5 C values of CO2 evolved during the incubation
of soil and roots have been widely used together with É14C of total soil respiration
to partition soil respiration into heterotrophic respiration (HR) and rhizosphere respiration.
However, these data have not been used as joint observational constraints to
determine SOC turnover times. Thus, we focus on: (1) how different combinations of
10 observational constraints help to narrow estimates of turnover times and other parameters
of a simple two-pool model, ICBM; (2) if a multiple constraints approach allows
determining whether the soil has been storing or losing SOC. To this end ICBM was
adapted to model SOC and SO14C in parallel with litterfall and the É14C of litterfall as
driving variables. The É14C of the atmosphere with its prominent bomb peak was used
15 as a proxy for the É14C of litterfall. Data from three spruce dominated temperate forests
in Germany and the USA (Coulissenhieb II, Solling D0 and Howland Tower site) were
used to estimate the parameters of ICBM via Bayesian calibration. Key findings are: (1)
the joint use of all 4 observational constraints (SOC stock and its É14C, HR flux and
its É14C) helped to considerably narrow turnover times of the young pool (primarily by
20 É14C of HR) and the old pool (primarily by É14C of SOC). Furthermore, the joint use all
observational constraints allowed constraining the humification factor in ICBM, which
describes the fraction of the annual outflux from the young pool that enters the old
pool. The Bayesian parameter estimation yielded the following turnover times (mean
± standard deviation) for SOC in the young pool: Coulissenhieb II 1.7±0.5 yr, Solling
25 D0 5.7±0.7yr and Howland Tower 1.1±0.5yr. Turnover times for the old pool were
380±61yr (Coulissenhieb II), 137±30yr (Solling D0) and 188±45yr (Howland Tower),
respectively. (2) At all three sites the multiple constraints approach was not able to determine if the soil has been losing or storing carbon. Nevertheless, the relaxed steady state assumption hardly introduced any additional uncertainty for the other parameter
estimates. Overall the results suggest that using É14C data from more than one carbon
pool or flux helps to better constrain SOC models.