SOC Fractions

Mapping soil organic carbon fractions for Australia, their stocks and uncertainty

 Mercedes Román Dobarco,, Alexandre M.J-C. Wadoux, Brendan Malone, Budiman Minasny, Alex B. McBratney, Ross Searle

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•          Spectroscopy is combined with digital soil mapping for mapping SOC fractions in the 0-30 cm. depth range

•          Climate and parent material were the most important soil-forming factors predicting the allocation of SOC among fractions.

•          The SOC stocks (0-30 cm) were estimated as 12.7 Pg MAOC, 2 Pg POC and 5.1 Pg PyOC.

•          TOC and the distribution among fractions were the most influential variables on SOC fraction uncertainty[AM1] 

Soil organic carbon (SOC) is the largest terrestrial carbon pool. SOC is composed of a continuum set of compounds with different chemical composition, origin and susceptibilities to decomposition, that are commonly separated into pools characterised by different responses to anthropogenic and environmental disturbance. Here we map the contribution of three SOC fractions to the total SOC content of Australia’s soils. The three SOC fractions: mineral-associated organic carbon (MAOC), particulate organic carbon (POC) and pyrogenic organic carbon (PyOC), represent SOC composition with distinct turnover rates, chemistry, and pathway formation. Data for MAOC, POC, and PyOC were obtained with near- and mid-infrared spectral models calibrated with measured SOC fractions. We transformed the data using an isometric log-ratio transformation (ilr) to account for the closed compositional nature of SOC fractions. The resulting , back-transformed ilr components were mapped across Australia. SOC fraction stocks for the 0-30 cm were derived with maps of total organic carbon concentration, bulk density, coarse fragments and soil thickness. Mapping was done by quantile regression forest fitted with the ilr transformed data and a large set of environmental variables as predictors. The resulting maps along with the quantified uncertainty show the unique spatial pattern of SOC fractions in Australia. MAOC dominated the total SOC with an average of 59% ±17.5%, whereas 28% ± 17.5% was PyOC and 13% ± 11.1% was POC. The allocation of TOC into the MAOC fractions increased with depth. SOC vulnerability (i.e., POC/[MAOC + PyOC]) was greater in areas with Mediterranean and temperate climate. TOC and the distribution among fractions were the most influential variables on SOC fraction uncertainty. Further, the diversity of climatic and pedological conditions suggests that different mechanisms will control SOC stabilisation and dynamics across the continent, as shown by the model covariates importance metric. We estimated the total SOC stocks (0-30 cm) to be 12.7 Pg MAOC, 2 Pg POC and 5.1 Pg PyOC, which is consistent with previous estimates. The maps of SOC fractions and their stocks can be used for modelling SOC dynamics and forecasting changes in SOC stocks as response to land use change, management, and climate change.

Figure 1:a) Composite of the contribution of the three SOC fractions to SOC for the depth intervals 0-5, 5-15, 15-30 cm. The colours indicate the dominant fractions with MAOC in red, POC in green and PyOC in blue. b) SOC vulnerability for the three depth intervals. SOC vulnerability is in the log10 scale for better differentiation.