Abstract. Changes in global soil carbon stocks have considerable potential to influence
the course of future climate change. However, a portion of soil organic
carbon (SOC) has a very long residence time (> 100 years) and may not
contribute significantly to terrestrial greenhouse gas emissions during the
next century. The size of this persistent SOC reservoir is presumed to be
large. Consequently, it is a key parameter required for the initialization of
SOC dynamics in ecosystem and Earth system models, but there is considerable
uncertainty in the methods used to quantify it. Thermal analysis methods
provide cost-effective information on SOC thermal stability that has been
shown to be qualitatively related to SOC biogeochemical stability. The
objective of this work was to build the first quantitative model of the size
of the centennially persistent SOC pool based on thermal analysis. We used a
unique set of 118 archived soil samples from four agronomic experiments in
northwestern Europe with long-term bare fallow and non-bare fallow treatments
(e.g., manure amendment, cropland and grassland) as a sample set for which
estimating the size of the centennially persistent SOC pool is relatively
straightforward. At each experimental site, we estimated the average
concentration of centennially persistent SOC and its uncertainty by applying
a Bayesian curve-fitting method to the observed declining SOC concentration
over the duration of the long-term bare fallow treatment. Overall, the
estimated concentrations of centennially persistent SOC ranged from 5 to
11 g C kg−1 of soil (lowest and highest boundaries of four 95 %
confidence intervals). Then, by dividing the site-specific concentrations of
persistent SOC by the total SOC concentration, we could estimate the
proportion of centennially persistent SOC in the 118 archived soil samples
and the associated uncertainty. The proportion of centennially persistent SOC
ranged from 0.14 (standard deviation of 0.01) to 1 (standard deviation of
0.15). Samples were subjected to thermal analysis by Rock-Eval 6 that
generated a series of 30 parameters reflecting their SOC thermal stability
and bulk chemistry. We trained a nonparametric machine-learning algorithm
(random forests multivariate regression model) to predict the proportion of
centennially persistent SOC in new soils using Rock-Eval 6 thermal parameters
as predictors. We evaluated the model predictive performance with two
different strategies. We first used a calibration set (n = 88) and a
validation set (n = 30) with soils from all sites. Second, to test the
sensitivity of the model to pedoclimate, we built a calibration set with soil
samples from three out of the four sites (n = 84). The multivariate
regression model accurately predicted the proportion of centennially
persistent SOC in the validation set composed of soils from all sites
(R2 = 0.92, RMSEP = 0.07, n = 30). The uncertainty of the
model predictions was quantified by a Monte Carlo approach that produced
conservative 95 % prediction intervals across the validation set. The
predictive performance of the model decreased when predicting the proportion
of centennially persistent SOC in soils from one fully independent site with
a different pedoclimate, yet the mean error of prediction only slightly
increased (R2 = 0.53, RMSEP = 0.10, n = 34). This model
based on Rock-Eval 6 thermal analysis can thus be used to predict the
proportion of centennially persistent SOC with known uncertainty in new soil
samples from different pedoclimates, at least for sites that have similar
Rock-Eval 6 thermal characteristics to those included in the calibration set.
Our study reinforces the evidence that there is a link between the thermal
and biogeochemical stability of soil organic matter and demonstrates that
Rock-Eval 6 thermal analysis can be used to quantify the size of the
centennially persistent organic carbon pool in temperate soils.
Supplementary material to "A model based on Rock-Eval thermal analysis to quantify the size of
the centennially persistent organic carbon pool in temperate soils"