An exponential change decline function to estimate soil organic carbon stocks and their changes from topsoil measurements

摘要: Soil organic carbon (SOC) stocks and their changes are important indicators in ecosystem service assessments. Routine soil inventories often limited to the topsoil, even though a non-negligible fraction of SOC is known be stored deeper horizons. To assess upper metre profile, vertical extrapolation topsoil measurements necessary. The commonly used exponential decline function not valid, however, for types which subsurface horizons with larger content (‘anomalies’) occur. Here, we propose an change account these profile anomalies. Therefore, applied difference between recent (2008–11) historical (1947–74) contents compared results those derived by original method. We 54 041 agricultural land units (7159 km2) Flanders (Belgium) were able model specific characteristics such as spodic horizons, plaggic peat substrates. For particular units, underestimated stocks; therefore, it compromised in-depth assessment over time. This study shows that promising certain will contribute more accurate indicators. In addition, emphasize need detailed descriptions subsoil reference profiles, sampled pedogenetic horizon rather than fixed depth interval optimize calibration functions. Highlights When sampling needed stocks. We modified SOC-rich integration legacy data. An appropriate approach essential assessments. Detailed data functions.