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The oxidative ratio (OR) of the net ecosystem carbon balance is the ratio of net O2 and CO2 fluxes resulting from photosynthesis, respiration, decomposition, and other lateral and vertical carbon flows. The OR of the terrestrial biosphere must be well characterized to accurately estimate the terrestrial CO2 sink using atmospheric measurements of changing O2 and CO2 levels. To estimate the OR of the terrestrial biosphere, measurements are needed of changes in the OR of aboveground and belowground carbon pools associated with decadal timescale disturbances (e.g., land use change and fire). The OR of aboveground pools can be measured using conventional approaches including elemental analysis. However, measuring the OR of soil carbon pools is technically challenging, and few soil OR data are available. In this paper we test three solid-state nuclear magnetic resonance (NMR) techniques for measuring soil OR, all based on measurements of the closely related parameter, organic carbon oxidation state (Cox). Two of the three techniques make use of a molecular mixing model which converts NMR spectra into concentrations of a standard suite of biological molecules of known Cox. The third technique assigns Cox values to each peak in the NMR spectrum. We assess error associated with each technique using pure chemical compounds and plant biomass standards whose Cox and OR values can be directly measured by elemental analyses. The most accurate technique, direct polarization solid-state 13C NMR with the molecular mixing model, agrees with elemental analyses to ±0.036 Cox units (±0.009 OR units). Using this technique, we show a large natural variability in soil Cox and OR values. Soil Cox values have a mean of −0.26 and a range from −0.45 to 0.30, corresponding to OR values of 1.08 ± 0.06 and a range from 0.96 to 1.22. We also estimate the OR of the carbon flux from a boreal forest fire. Analysis of soils from nearby intact soil profiles imply that soil carbon losses associated with the fire had an OR of 1.091 (±0.003). Fire appears to be a major factor driving the soil C pool to higher oxidation states and lower OR values. Episodic fluxes caused by disturbances like fire may have substantially different ORs from ecosystem respiration fluxes and therefore should be better quantified to reduce uncertainties associated with our understanding of the global atmospheric carbon budget.

The benefits of sequestering carbon are many, including improved crop productivity, reductions in greenhouse gases, and financial gains through the sale of carbon credits. Achieving better understanding of the sequestration process has motivated many deterministic models of soil carbon dynamics, but none of these models address uncertainty in a comprehensive manner. Uncertainty arises in many ways-around the model inputs, parameters, and dynamics, and subsequently model predictions. In this paper, these uncertainties are addressed in concert by incorporating a physical-statistical model for carbon dynamics within a Bayesian hierarchical modelling framework. This comprehensive approach to accounting for uncertainty in soil carbon modelling has not been attempted previously. This paper demonstrates proof-of-concept based on a one-pool model and identifies requirements for extension to multi-pool carbon modelling. Our model is based on the soil carbon dynamics in Tarlee, South Australia. We specify the model conditionally through its parameters, soil carbon input and decay processes and observations of those processes. We use a particle marginal Metropolis-Hastings approach specified using the LibBi modelling language. We highlight how samples from the posterior distribution can be used to summarise our knowledge about model parameters, to estimate the probabilities of sequestering carbon and to forecast changes in carbon stocks under crop rotations not represented explicitly in the original field trials. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]