, Volume 11, Issue 2, pp 250-269

First online:

Integration of Process-based Soil Respiration Models with Whole-Ecosystem CO2 Measurements

  • J. M. ZobitzAffiliated withDepartment of Mathematics, University of UtahDepartment of Mathematics, Augsburg College Email author 
  • , D. J. P. MooreAffiliated withNational Center for Atmospheric ResearchDepartment of Geography, King’s College London
  • , W. J. SacksAffiliated withCenter for Sustainability and the Global Environment, Nelson Institute for Environmental Studies, University of Wisconsin-Madison
  • , R. K. MonsonAffiliated withDepartment of Ecology and Evolutionary Biology (EEB), University of Colorado
  • , D. R. BowlingAffiliated withDepartment of Biology, University of Utah
  • , D. S. SchimelAffiliated withNational Center for Atmospheric Research

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access


We integrated soil models with an established ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to investigate the influence of soil processes on modelled values of soil CO2 fluxes (R Soil). Model parameters were determined from literature values and a data assimilation routine that used a 7-year record of the net ecosystem exchange of CO2 and environmental variables collected at a high-elevation subalpine forest (the Niwot Ridge AmeriFlux site). These soil models were subsequently evaluated in how they estimated the seasonal contribution of R Soil to total ecosystem respiration (TER) and the seasonal contribution of root respiration (R Root) to R Soil. Additionally, these soil models were compared to data assimilation output of linear models of soil heterotrophic respiration. Explicit modelling of root dynamics led to better agreement with literature values of the contribution of R Soil to TER. Estimates of R Soil/TER when root dynamics were considered ranged from 0.3 to 0.6; without modelling root biomass dynamics these values were 0.1–0.3. Hence, we conclude that modelling of root biomass dynamics is critically important to model the R Soil/TER ratio correctly. When soil heterotrophic respiration was dependent on linear functions of temperature and moisture independent of soil carbon pool size, worse model-data fits were produced. Adding additional complexity to the soil pool marginally improved the model-data fit from the base model, but issues remained. The soil models were not successful in modelling R Root/R Soil. This is partially attributable to estimated turnover parameters of soil carbon pools not agreeing with expected values from literature and being poorly constrained by the parameter estimation routine. We conclude that net ecosystem exchange of CO2 alone cannot constrain specific rhizospheric and microbial components of soil respiration. Reasons for this include inability of the data assimilation routine to constrain soil parameters using ecosystem CO2 flux measurements and not considering the effect of other resource limitations (for example, nitrogen) on the microbe biomass. Future data assimilation studies with these models should include ecosystem-scale measurements of R Soil in the parameter estimation routine and experimentally determine soil model parameters not constrained by the parameter estimation routine.


model-data fusion net ecosystem exchange ecosystem model parameter estimation eddy covariance heterotrophic respiration