Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions

TLDR: The direct correlation of rC with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa, and the complex interconnections in regulating SOC dynamics are revealed.

Abstract: Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (rC, Mg C ha−1 yr−1) Among these variables, we found that the most influential variables on rC were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on rC, followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24% Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining rC The direct correlation of rC with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models