, Volume 108, Issue 1–3, pp 119–134 | Cite as

Inverse determination of heterotrophic soil respiration response to temperature and water content under field conditions

  • J. BauerEmail author
  • L. Weihermüller
  • J. A. Huisman
  • M. Herbst
  • A. Graf
  • J. M. Séquaris
  • H. Vereecken


Heterotrophic soil respiration is an important flux within the global carbon cycle. Exact knowledge of the response functions for soil temperature and soil water content is crucial for a reliable prediction of soil carbon turnover. The classical statistical approach for the in situ determination of the temperature response (Q10 or activation energy) of field soil respiration has been criticised for neglecting confounding factors, such as spatial and temporal changes in soil water content and soil organic matter. The aim of this paper is to evaluate an alternative method to estimate the temperature and soil water content response of heterotrophic soil respiration. The new method relies on inverse parameter estimation using a 1-dimensional CO2 transport and carbon turnover model. Inversion results showed that different formulations of the temperature response function resulted in estimated response factors that hardly deviated over the entire range of soil water content and for temperature below 25°C. For higher temperatures, the temperature response was highly uncertain due to the infrequent occurrence of soil temperatures above 25°C. The temperature sensitivity obtained using inverse modelling was within the range of temperature sensitivities estimated from statistical processing of the data. It was concluded that inverse parameter estimation is a promising tool for the determination of the temperature and soil water content response of soil respiration. Future synthetic model studies should investigate to what extent the inverse modelling approach can disentangle confounding factors that typically affect statistical estimates of the sensitivity of soil respiration to temperature and soil water content.


Heterotrophic soil respiration Temperature sensitivity Soil water content sensitivity Inverse parameter estimation SOILCO2/RothC SCE algorithm AIC 



This research was supported by the German Research Foundation DFG (Transregional Collaborative Research Centre 32—Patterns in Soil-Vegetation-Atmosphere systems: monitoring, modelling and data assimilation), TERENO (Terrestrial Environmental Observatories) of the Helmholtz Gemeinschaft and by the Hessian initiative for the development of scientific and economic excellence (LOEWE) at the Biodiversity and Climate Research Centre (BiK-F), Frankfurt/Main. We thank Axel Knaps and Rainer Harms for providing the climate data. The organic carbon content of the soil was analysed by the Central Division of Analytical Chemistry at the Forschungszentrum Jülich GmbH. We would like to thank Claudia Walraf and Stefan Masjoshustmann for the physical fractionation of the soil samples and Ludger Bornemann (Institute of Crop Science and Resource Conservation—Division of Soil Science, University of Bonn) for the analysis of black carbon. We are grateful to Horst Hardelauf for modifications of the model source code. Furthermore, we thank three anonymous reviewers for their helpful advices.


  1. Abbaspour K, Kasteel R et al (2000) Inverse parameter estimation in a layered unsaturated field soil. Soil Sci 165(2):109–123CrossRefGoogle Scholar
  2. Ahrens B (2003) Evaluation of precipitation forecasting with the limited area model ALADIN in an alpine watershed. Meteorol Z 12(5):245–255CrossRefGoogle Scholar
  3. Akaike H (1974) New look at statistical-model identification. IEEE Trans Autom Control AC19(6):716–723CrossRefGoogle Scholar
  4. Allen RG, Pereira LS et al (1998) Crop evapotranspiration—Guidelines for computing crop water requirements. FAO irrigation and drainage paper 56. FAO—Food and Agriculture Organization of the United Nations, RomeGoogle Scholar
  5. Bahn M, Rodeghiero M et al (2008) Soil respiration in European grasslands in relation to climate and assimilate supply. Ecosystems 11(8):1352–1367CrossRefGoogle Scholar
  6. Bauer J, Herbst M et al (2008) Sensitivity of simulated soil heterotrophic respiration to temperature and moisture reduction functions. Geoderma 145(1–2):17–27CrossRefGoogle Scholar
  7. Boone RD, Nadelhoffer KJ et al (1998) Roots exert a strong influence on the temperature sensitivity of soil respiration. Nature 396(6711):570–572CrossRefGoogle Scholar
  8. Bornemann L, Welp G et al (2008) Rapid assessment of black carbon in soil organic matter using mid-infrared spectroscopy. Org Geochem 39(11):1537–1544CrossRefGoogle Scholar
  9. Cambardella CA, Elliott ET (1992) Particulate soil organic-matter changes across a grassland cultivation sequence. Soil Sci Soc Am J 56(3):777–783CrossRefGoogle Scholar
  10. Carvalhais N, Reichstein M et al (2008) Implications of the carbon cycle steady state assumption for biogeochemical modeling performance and inverse parameter retrieval. Glob Biogeochem Cycles 22(2):16CrossRefGoogle Scholar
  11. Chung SO, Horton R (1987) Soil heat and water-flow with a partial surface mulch. Water Resour Res 23(12):2175–2186CrossRefGoogle Scholar
  12. Coleman K, Jenkinson DS (1996) RothC-26.3—a model for the turnover of carbon in soil. In: Powlson DS, Smith P, Smith JU (eds) Evaluation of soil organic matter models using existing long-term datasets, vol 38. Springer-Verlag, Heidelberg, pp 237–246CrossRefGoogle Scholar
  13. Coleman K, Jenkinson DS (2005) ROTHC-26.3. A Model for the turnover of carbon in soil. Model description and Windows users guide. IACR-Rothamsted, HarpendenGoogle Scholar
  14. Coleman K, Jenkinson DS et al (1997) Simulating trends in soil organic carbon in long-term experiments using RothC-26.3. Geoderma 81(1–2):29–44CrossRefGoogle Scholar
  15. Davidson EA, Janssens IA (2006) Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440(7081):165–173CrossRefGoogle Scholar
  16. Davidson EA, Belk E et al (1998) Soil water content and temperature as independent or confounded factors controlling soil respiration in a temperate mixed hardwood forest. Glob Change Biol 4(2):217–227CrossRefGoogle Scholar
  17. Duan QY, Sorooshian S et al (1992) Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour Res 28(4):1015–1031CrossRefGoogle Scholar
  18. Duan QY, Sorooshian S et al (1994) Optimal use of the SCE-UA global optimization method for calibrating watershed models. J Hydrol 158(3–4):265–284CrossRefGoogle Scholar
  19. Falloon P, Smith P et al (1998) Estimating the size of the inert organic matter pool from total soil organic carbon content for use in the Rothamsted carbon model. Soil Biol Biochem 30(8–9):1207–1211CrossRefGoogle Scholar
  20. Fang C, Moncrieff JB (1999) A model for soil CO2 production and transport 1: model development. Agric For Meteorol 95(4):225–236CrossRefGoogle Scholar
  21. Fox A, Williams M et al (2009) The REFLEX project: comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data. Agric For Meteorol 149(10):1597–1615CrossRefGoogle Scholar
  22. Graf A, Weihermüller L et al (2008) Measurement depth effects on the apparent temperature sensitivity of soil respiration in field studies. Biogeosciences 5(4):1175–1188CrossRefGoogle Scholar
  23. Greaves JE, Carter EG (1920) Influence of moisture on the bacterial activities of the soil. Soil Sci 10(5):361–387CrossRefGoogle Scholar
  24. Heimovaara TJ, Bouten W (1990) A computer-controlled 36-channel Time Domain Reflectometry system for monitoring soil-water contents. Water Resour Res 26(10):2311–2316Google Scholar
  25. Herbst M, Hellebrand HJ et al (2008) Multiyear heterotrophic soil respiration: evaluation of a coupled CO2 transport and carbon turnover model. Ecol Model 214(2–4):271–283CrossRefGoogle Scholar
  26. Ise T, Moorcroft PR (2006) The global-scale temperature and moisture dependencies of soil organic carbon decomposition: an analysis using a mechanistic decomposition model. Biogeochemistry 80(3):217–231CrossRefGoogle Scholar
  27. IUSS Working Group WRB (2007) World reference base for soil resources 2006, First update 2007. World soil resources reports 103. FAO—Food and Agriculture Organization of the United Nations, RomeGoogle Scholar
  28. Jenkinson DS (1990) The turnover of organic-carbon and nitrogen in soil. Philos Trans R Soc Lond B Biol Sci 329(1255):361–368CrossRefGoogle Scholar
  29. Jenkinson DS, Coleman K (1994) Calculating the annual input of organic-matter to soil from measurements of total organic-carbon and radiocarbon. Eur J Soil Sci 45(2):167–174CrossRefGoogle Scholar
  30. Johnson IR, Thornley JHM (1985) Temperature-dependence of plant and crop processes. Ann Bot 55(1):1–24Google Scholar
  31. Kirschbaum MUF (2000) Will changes in soil organic carbon act as a positive or negative feedback on global warming? Biogeochemistry 48(1):21–51CrossRefGoogle Scholar
  32. Kirschbaum MUF (2006) The temperature dependence of organic-matter decomposition—still a topic of debate. Soil Biol Biochem 38(9):2510–2518CrossRefGoogle Scholar
  33. Köhler B, Zehe E et al (2010) An inverse analysis reveals limitations of the soil-CO2 profile method to calculate CO2 production and efflux for well-structured soils. Biogeosciences 7(8):2311–2325CrossRefGoogle Scholar
  34. Larionova AA, Yevdokimov IV et al (2007) Temperature response of soil respiration is dependent on concentration of readily decomposable C. Biogeosciences 4(6):1073–1081CrossRefGoogle Scholar
  35. Lee MS, Nakane K et al (2003) Seasonal changes in the contribution of root respiration to total soil respiration in a cool-temperate deciduous forest. Plant Soil 255(1):311–318CrossRefGoogle Scholar
  36. Leifeld J, Fuhrer J (2005) The temperature response of CO2 production from bulk soils and soil fractions is related to soil organic matter quality. Biogeochemistry 75(3):433–453CrossRefGoogle Scholar
  37. Madsen H, Wilson G et al (2002) Comparison of different automated strategies for calibration of rainfall-runoff models. J Hydrol 261(1–4):48–59CrossRefGoogle Scholar
  38. Mahecha MD, Reichstein M et al (2010) Global convergence in the temperature sensitivity of respiration at ecosystem level. Science 329(5993):838–840CrossRefGoogle Scholar
  39. Matzner E, Borken W (2008) Do freeze-thaw events enhance C and N losses from soils of different ecosystems? A review. Eur J Soil Sci 59(2):274–284CrossRefGoogle Scholar
  40. Mertens J, Madsen H et al (2005) Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective, laboratory and in situ estimates. Hydrol Process 19(8):1611–1633CrossRefGoogle Scholar
  41. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I—a discussion of principles. J Hydrol 10(3):282–290CrossRefGoogle Scholar
  42. Nelder JA, Mead R (1965) A simplex-method for function minimization. Comput J 7(4):308–313Google Scholar
  43. O’Connell AM (1990) Microbial decomposition (respiration) of litter in eucalypt forests of south-western Australia—an empirical-model based on laboratory incubations. Soil Biol Biochem 22(2):153–160CrossRefGoogle Scholar
  44. Pal D, Broadbent FE (1975) Influence of moisture on rice straw decomposition in soils. Soil Sci Soc Am J 39(1):59–63CrossRefGoogle Scholar
  45. Parton WJ, Schimel DS et al (1987) Analysis of factors controlling soil organic-matter levels in Great-Plains grasslands. Soil Sci Soc Am J 51(5):1173–1179CrossRefGoogle Scholar
  46. Patwardhan AS, Nieber JL et al (1988) Oxygen, carbon-dioxide, and water transfer in soils—mechanisms and crop response. Trans ASAE 31(5):1383–1395Google Scholar
  47. Pavelka M, Acosta M et al (2007) Dependence of the Q10 values on the depth of the soil temperature measuring point. Plant Soil 292(1–2):171–179CrossRefGoogle Scholar
  48. Peters A, Durner W (2008) Simplified evaporation method for determining soil hydraulic properties. J Hydrol 356(1–2):147–162CrossRefGoogle Scholar
  49. Reichstein M, Beer C (2008) Soil respiration across scales: the importance of a model-data integration framework for data interpretation. J Plant Nutr Soil Sci 171(3):344–354CrossRefGoogle Scholar
  50. Rixon AJ, Bridge BJ (1968) Respiratory quotient arising from microbial activity in relation to matric suction and air filled pore space of soil. Nature 218(5145):961–962CrossRefGoogle Scholar
  51. Rovira AD (1953) Use of the Warburg apparatus in soil metabolism studies. Nature 172(4366):29–30CrossRefGoogle Scholar
  52. Scharnagl B, Vrugt JA et al (2010) Information content of incubation experiments for inverse estimation of pools in the Rothamsted carbon model: a Bayesian perspective. Biogeosciences 7(2):763–776CrossRefGoogle Scholar
  53. Schlesinger WH, Andrews JA (2000) Soil respiration and the global carbon cycle. Biogeochemistry 48(1):7–20CrossRefGoogle Scholar
  54. Seifert J (1961) Influence of moisture and temperature on number of bacteria in soil. Folia Microbiol 6(4):268–272CrossRefGoogle Scholar
  55. Šimůnek J, Suarez DL (1993) Modeling of carbon dioxide transport and production in soil: 1. Model development. Water Resour Res 29(2):487–497CrossRefGoogle Scholar
  56. Skjemstad JO, Spouncer LR et al (2004) Calibration of the Rothamsted organic carbon turnover model (RothC ver. 26.3), using measurable soil organic carbon pools. Aust J Soil Res 42(1):79–88CrossRefGoogle Scholar
  57. Skopp J, Jawson MD et al (1990) Steady-state aerobic microbial activity as a function of soil-water content. Soil Sci Soc Am J 54(6):1619–1625CrossRefGoogle Scholar
  58. Sophocleous M (1979) Analysis of water and heat-flow in unsaturated-saturated porous-media. Water Resour Res 15(5):1195–1206CrossRefGoogle Scholar
  59. Suarez DL, Simunek J (1993) Modeling of carbon-dioxide transport and production in soil 2. Parameter selection, sensitivity analysis, and comparison of model predictions to field data. Water Resour Res 29(2):499–513CrossRefGoogle Scholar
  60. Trudinger CM, Raupach MR et al (2007) OptIC project: an intercomparison of optimization techniques for parameter estimation in terrestrial biogeochemical models. J Geophys Res Biogeosci 112(G2):17CrossRefGoogle Scholar
  61. van Genuchten MT (1980) A closed form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am J 44(5):892–898CrossRefGoogle Scholar
  62. Wang YP, Trudinger CM et al (2009) A review of applications of model-data fusion to studies of terrestrial carbon fluxes at different scales. Agric For Meteorol 149(11):1829–1842CrossRefGoogle Scholar
  63. Weihermüller L, Huisman JA et al (2007) Mapping the spatial variation of soil water content at the field scale with different ground penetrating radar techniques. J Hydrol 340(3–4):205–216CrossRefGoogle Scholar
  64. Weihermüller L, Huisman JA et al (2009) Multistep outflow experiments to determine soil physical and carbon dioxide production parameters. Vadose Zone J 8(3):772–782CrossRefGoogle Scholar
  65. Williams M, Richardson AD et al (2009) Improving land surface models with FLUXNET data. Biogeosciences 6(7):1341–1359CrossRefGoogle Scholar
  66. Xu M, Qi Y (2001) Spatial and seasonal variations of Q(10) determined by soil respiration measurements at a Sierra Nevadan forest. Glob Biogeochem Cycle 15(3):687–696CrossRefGoogle Scholar
  67. Yasuda Y, Ohtani Y et al (2008) Development of a CO2 gas analyzer for monitoring soil CO2 concentrations. J For Res 13(5):320–325CrossRefGoogle Scholar
  68. Zhou T, Shi PJ et al (2009) Global pattern of temperature sensitivity of soil heterotrophic respiration (Q(10)) and its implications for carbon-climate feedback. J Geophys Res Biogeosci 114:9Google Scholar
  69. Zimmermann M, Leifeld J et al (2007) Measured soil organic matter fractions can be related to pools in the RothC model. Eur J Soil Sci 58(3):658–667CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • J. Bauer
    • 1
    • 2
    Email author
  • L. Weihermüller
    • 1
  • J. A. Huisman
    • 1
  • M. Herbst
    • 1
  • A. Graf
    • 1
  • J. M. Séquaris
    • 1
  • H. Vereecken
    • 1
  1. 1.Institute of Bio- and Geosciences—Agrosphere, IBG-3Forschungszentrum Jülich GmbHJülichGermany
  2. 2.Institute for Atmospheric and Environmental SciencesGoethe University Frankfurt am MainFrankfurt am MainGermany

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