Abstract. Soil organic matter (SOM) turnover models predict changes
in SOM due to management and environmental factors. Their initialization
remains challenging as partitioning of SOM into different hypothetical pools
is intrinsically linked to model assumptions. Diffuse reflectance mid-infrared Fourier transform spectroscopy (DRIFTS) provides information on SOM
quality and could yield a measurable pool-partitioning proxy for SOM. This
study tested DRIFTS-derived SOM pool partitioning using the Daisy model. The
DRIFTS stability index (DSI) of bulk soil samples was defined as the ratio
of the area below the aliphatic absorption band (2930 cm−1) to the
area below the aromatic–carboxylate absorption band (1620 cm−1). For
pool partitioning, the DSI (2930 cm−1 ∕ 1620 cm−1) was set
equal to the ratio of fast-cycling ∕ slow-cycling SOM. Performance was tested by simulating long-term bare fallow plots from the Bad Lauchstädt extreme
farmyard manure experiment in Germany (Chernozem, 25 years), the Ultuna
continuous soil organic matter field experiment in Sweden (Cambisol, 50 years), and 7 year duration bare fallow plots from the Kraichgau and Swabian
Jura regions in southwest Germany (Luvisols). All experiments were
at sites that were agricultural fields for centuries before fallow establishment, so classical
theory would suggest that a steady state can be assumed for initializing SOM
pools. Hence, steady-state and DSI initializations were compared, using two
published parameter sets that differed in turnover rates and humification
efficiency. Initialization using the DSI significantly reduced Daisy model error
for total soil organic carbon and microbial carbon in cases where assuming
a steady state had poor model performance. This was irrespective of the
parameter set, but faster turnover performed better for all sites except for
Bad Lauchstädt. These results suggest that soils, although under
long-term agricultural use, were not necessarily at a steady state. In a next
step, Bayesian-calibration-inferred best-fitting turnover rates for Daisy
using the DSI were evaluated for each individual site or for all sites
combined. Two approaches significantly reduced parameter uncertainty and
equifinality in Bayesian calibrations: (1) adding physicochemical meaning
with the DSI (for humification efficiency and slow SOM turnover) and (2) combining all sites (for all parameters). Individual-site-derived turnover
rates were strongly site specific. The Bayesian calibration combining all
sites suggested a potential for rapid SOM loss with 95 % credibility
intervals for the slow SOM pools' half-life being 278 to 1095 years (highest
probability density at 426 years). The credibility intervals of this study
were consistent with several recently published Bayesian calibrations of
similar two-pool SOM models, i.e., with turnover rates being faster than
earlier model calibrations suggested; hence they likely underestimated
potential SOM losses.
Multidecadal persistence of organic matter in soils: investigations at the submicrometer scale
