, Volume 171, Issue 3, pp 721–732 | Cite as

Separating soil CO2 efflux into C-pool-specific decay rates via inverse analysis of soil incubation data

  • Christina SchädelEmail author
  • Yiqi Luo
  • R. David Evans
  • Shenfeng Fei
  • Sean M. Schaeffer
Special Topic: In Honor of Christian Körner


Soil organic matter (SOM) is heterogeneous in structure and has been considered to consist of various pools with different intrinsic turnover rates. Although those pools have been conceptually expressed in models and analyzed according to soil physical and chemical properties, separation of SOM into component pools is still challenging. In this study, we conducted inverse analyses with data from a long-term (385 days) incubation experiment with two types of soil (from plant interspace and from underneath plants) to deconvolute soil carbon (C) efflux into different source pools. We analyzed the two datasets with one-, two- and three-pool models and used probability density functions as a criterion to judge the best model to fit the datasets. Our results indicated that soil C release trajectories over the 385 days of the incubation study were best modeled with a two-pool C model. For both soil types, released C within the first 10 days of the incubation study originated from the labile pool. Decomposition of C in the recalcitrant pool was modeled to contribute to the total CO2 efflux by 9–11 % at the beginning of the incubation. At the end of the experiment, 75–85 % of the initial soil organic carbon (SOC) was modeled to be released over the incubation period. Our modeling analysis also indicated that the labile C-pool in the soil underneath plants was larger than that in soil from interspace. This deconvolution analysis was based on information contained in incubation data to separate carbon pools and can facilitate integration of results from incubation experiments into ecosystem models with improved parameterization.


SOC Labile C Recalcitrant C Data assimilation Parameter estimation 



We thank Ensheng Weng for help with model development. This study is financially supported by the Office of Science (BER), Department of Energy, under grant DE-SC0004601; US National Science Foundation (NSF) grants DEB 0444518, DEB 0743778, DEB 0840964, DBI 0850290, and EPS 0919466. The authors also gratefully acknowledge grant support from the Department of Energy’s Terrestrial Carbon Processes Program (DE-FG02-03ER63650, DEFG02-03ER63651) and the NSF Ecosystem Studies Program (DEB-98-14358 and 02-12819). In addition, we also gratefully acknowledge the DOE’s National Nuclear Security Administration for providing utility services and undisturbed land at the Nevada National Security Site (formerly Nevada Test Site) to conduct the FACE experiment.

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Christina Schädel
    • 1
    • 2
    Email author
  • Yiqi Luo
    • 2
  • R. David Evans
    • 3
  • Shenfeng Fei
    • 2
    • 4
  • Sean M. Schaeffer
    • 5
  1. 1.Department of BiologyUniversity of FloridaGainesvilleUSA
  2. 2.Department of Microbiology and Plant BiologyUniversity of OklahomaNormanUSA
  3. 3.School of Biological SciencesWashington State UniversityPullmanUSA
  4. 4.Department of Computer Science and EngineeringTexas A&M UniversityCollege StationUSA
  5. 5.Department of Biosystems Engineering and Soil ScienceUniversity of TennesseeKnoxvilleUSA

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