|Ahrens, B; Reichstein, M; Borken, W; Muhr, J; Trumbore, SE; Wutzler, T: Bayesian calibration of a soil organic carbon model using Δ14C measurements of soil organic carbon and heterotrophic respiration as joint constraints, Biogeosciences, 11, 2147-2168 (2014), doi:10.5194/bg-11-2147-2014|
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 delta14C values of bulk SOC or different SOC fractions as observational constraints in SOC models. Further, the delta14 C values of CO2 evolved during the incubation of soil and roots have been widely used together with delta14C 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 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 delta14C of litterfall as driving variables. The É14C of the atmosphere with its prominent bomb peak was used as a proxy for the delta14C 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 delta14C, HR flux and its delta14C) helped to considerably narrow turnover times of the young pool (primarily by delta14C of HR) and the old pool (primarily by delta14C 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 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 delta14C data from more than one carbon pool or flux helps to better constrain SOC models.