DRIFTS peaks as measured pool size proxy to reduce parameter uncertainty of soil organic matter models

Abstract

<p><strong>Abstract.</strong> The initialization of soil organic matter (SOM) turnover models has been a challenge for decades. Instead of using laborious and error prone size-density fractionation SOM pool partitioning, we propose the inexpensive, rapid, and non destructive Diffuse reflectance mid infrared Fourier transform spectroscopy (DRIFTS) technique on bulk soil samples to gain information on SOM pool partitioning from the spectra. Specifically, the DRIFTS stability index, defined as the ratio of aliphatic C-H (2930 cm<sup>−1</sup>) to aromatic C=C (1620 cm<sup>−1</sup>) stretching vibrations, was used to divide SOM into fast and slow cycling pools in the soil organic module of the DAISY model. Long-term bare fallow plots from Bad Lauchstädt (Chernozem, 25 years) and the Ultuna frame trial in Sweden (Cambisol, 50 years) were combined with bare fallow plots of 7 years duration in the Kraichgau and Swabian Jura region in Southwest Germany (Luvisols). All fields had been in agricultural use for centuries before fallow establishment, so classical theory would suggest an initial steady state of SOM, which was hence used to compare the performance of DAISY initializations against the newly established DRIFTS stability index. The test was done using two different published parameter sets (2.7 × 10<sup>−6</sup> d<sup>−1</sup>, 1.4 × 10<sup>−4</sup> d<sup>−1</sup>, 0.1 compared to 4.3 × 10<sup>−5</sup> d<sup>−1</sup>, 1.4 × 10<sup>−4</sup> d<sup>−1</sup>, 0.3 for the turnover rates of slow pool, fast pool and humification efficiency, respectively). The DRIFTS initialization of SOM pools significantly reduced model errors of poor performing model runs assuming steady state, irrespective of the turnover rates used, but the faster turnover parameter set fit better to all sites except Bad Lauchstädt. This suggests that soils under long-term agricultural use were not necessarily at steady state. A Bayesian calibration was applied in a next step to identify the best-fitting turnover rates for the DRIFTS stability index in DAISY, both for each site individually and for a combination of all sites. The two approaches which significantly reduced parameter uncertainty and equifinality were: (1) the addition of the physico-chemically based DRIFTS stability index, and (2) combining several sites into one Bayesian calibration, as derived turnover rates can be strongly site specific. The combination of all four sites showed that SOM is likely lost at relatively fast turnover rates with the 95 % credibility intervals of the slow SOM pools half life ranging from 278 to 1095 years, with 426 years as a value of highest probability density. The credibility intervals of this study were consistent with several recently published Bayesian calibrations of similar SOM models, all turnover rates were considerably faster than earlier models suggested. It is therefore likely that published turnover rates understimate the potential loss of SOM.</p>