Estimating Mineral-Associated Organic Carbon Deficits in Soils of the Okanagan Valley: A Regional Study With Broader Implications

To successfully reduce atmospheric CO2 by sequestering additional soil carbon, it is essential to understand the potential of a given soil to store carbon in a stable form. Carbon that has formed organo-mineral complexes with silt and clay particles is believed to be less susceptible to decay than non-complexed, or particulate, organic carbon. Using direct measurements of mineral associated organic matter (MAOC) on a subset of samples, and an approach developed previously for primarily allophanic soils, we took a modeling approach to estimate MAOC for 537 samples of much coarser and younger soils from 99 non-cultivated and agricultural sites in the Okanagan Valley, British Columbia, Canada. Using specific surface area (SSA) or soil texture as indicators of the mineral surface area available for sorption of organic matter, we used both Random Forest (RF) and Stepwise Multiple Regression with Akaike Information Criterion (SMR) to determine a best fit model for predicting MAOC. Random Forest modeling using SSA in addition to total SOC, exchangeable calcium, exchangeable potassium, and soil pH performed better than SMR for determining MAOC in these soils (R2: 0.790 for RF; R2: 0.713 for SMR). To determine if a MAOC deficit existed for these soils, we then applied a quantile regression approach wherein the predicted 90th quantile of MAOC represents the MAOC formation capacity. We determined that MAOC deficits were present in all soils and increased with depth. Moreover, clay rich soils had greater MAOC deficits (1.62 g kg-1 for 0-15 cm, 4.01 g kg-1 for 15-30 cm, and 5.80 g kg-1 for 30-60 cm), than sandier soils (1.01 g kg-1 for 0-15 cm, 2.72 g kg-1 for 15-30 cm, and 3.69 g kg-1 for 30-60 cm). Furthermore, the upper 30 cm of these soils have the potential to increase MAOC stocks by 29% (48.0 million kg of MAOC over 8,501 ha) before they reach formation capacity. This study highlights the variability in MAOC formation capacity of soils with different physicochemical properties and provides a framework for estimating MAOC concentrations and deficits for soils with a wide range of physicochemical properties.