2014
DOI: 10.5194/bg-11-2147-2014
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Bayesian calibration of a soil organic carbon model using Δ<sup>14</sup>C measurements of soil organic carbon and heterotrophic respiration as joint constraints

Abstract: Abstract. Soils of temperate forests store significant amounts of organic matter and are considered to be net sinks of atmospheric CO 2 . Soil organic carbon (SOC) turnover has been studied using the 14 C values of bulk SOC or different SOC fractions as observational constraints in SOC models. Further, the 14 C values of CO 2 that evolved during the incubation of soil and roots have been widely used together with 14 C of total soil respiration to partition soil respiration into heterotrophic respiration (HR) a… Show more

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Cited by 35 publications
(35 citation statements)
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“…More data on the fate of deposited SOC are necessary to investigate how both SOC burial and SOC response to management changes vary globally. In particular, more detailed information on SOC pools and isotopic composition [e.g., Ahrens et al, 2014;Skjemstad et al, 2004] could provide a more stringent test of model performance.…”
Section: 1002/2014gb004912mentioning
confidence: 99%
“…More data on the fate of deposited SOC are necessary to investigate how both SOC burial and SOC response to management changes vary globally. In particular, more detailed information on SOC pools and isotopic composition [e.g., Ahrens et al, 2014;Skjemstad et al, 2004] could provide a more stringent test of model performance.…”
Section: 1002/2014gb004912mentioning
confidence: 99%
“…Braakhekke et al (2014), using a soil profile model, found that the addition of SO 14 C data as a new constraint produced an increase in the uncertainty of the SOC stocks in the individual layers, while improved just marginally the total SOC stock estimate. Ahrens et al (2014) utilized SO 14 C data to constrain an isotopically explicit single layer model in a situation where data about SOC kinetics were scarce. In that case the problem of model initialization was partially solved with additional information coming from 14 C, but the high uncertainty of the considered system did not make it possible to determine if one site was losing or gaining carbon, and the strong interaction between MRT and deviation from the steady state made evident a trade-off between estimates with and without using SO 14 C data.…”
Section: Modeling the Kinetics Of Soc Poolsmentioning
confidence: 99%
“…One of the possible reasons for the recorded discrepancies in the estimates from models conditioned with and without SO 14 C data might be the absence of microbial dynamics in SOC stabilization (Riley et al, 2014). Ahrens et al (2015), with a rather mechanistic model, recently suggested that a control on biologically mediated depolymerization can explain alone some of the observed discrepancies. But the performances of structure IV and V on our data set, lower in terms of AIC compared to the simpler structures I and II, did not allow us to confirm such a hypothesis.…”
Section: Modeling the Kinetics Of Soc Poolsmentioning
confidence: 99%
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“…The definition of these rate coefficients and the functions that relate soil organic carbon (SOC) turnover to environmental conditions have typically been obtained by observations on changes in total carbon stocks [Katterer and Andren, 1999]. More recently, 14 C content of bulk SOC or different SOC fractions has been successfully used as additional observational constraints in SOC models to calculate turnover times of SOC [Ahrens et al, 2014;Trumbore, 1993]. Others have successfully related conceptual carbon pools to measurable carbon fractions under specific conditions [Skjemstad et al, 2004;Zimmermann et al, 2007].…”
Section: Introductionmentioning
confidence: 99%