Assessing fixed depth carbon stocks in soils with varying horizon depths and thicknesses, sampled by horizon

Abstract

Soil surveys for improving carbon (C) stock estimates frequently involve soil sampling by pre-determined regular depth-intervals, in order to enable more convenient computation of soil organic carbon (SOC) stocks. As a result, soil horizons are often neglected in these surveys, although they represent distinct components of the soil profile. When soil-horizon depths and thicknesses vary considerably within the same site, soil sampling by horizon with accompanying depth measurements may be more suitable. The main objective in this study was to investigate the potential differences in current SOC stocks in different afforested mineral soils, with varying horizon depths and thicknesses, and that were sampled by soil horizon, by using the trapezoidal SOC stock computing approach, and comparing it to the spline approach. An adaptation of the trapezoidal rule computation approach, enabling relatively simple crude estimations of the fixed depth-interval SOC stocks from horizon data, was developed. Estimations of SOC stocks for 18 sites located on three different afforested mineral soils (Gleys, Podzols and Cambisols, aged ≥ 20 years) were done for 0–30 cm, 30–60 cm and 0–60 cm fixed depth-intervals, excluding surface organic layers. The results indicate that the trapezoidal approach is likely to provide cruder estimates of SOC stocks than the spline approach, although no statistically significant differences were observed between the fixed depth-interval SOC stocks (for 0–30 cm and 30–60 cm) when computed by the two methods. Both methods showed a significant effect of horizon and soil group on SOC stocks. The soil below the 30 cm depth was estimated to store over 22% of the total SOC stocks to 60 cm depth. Gleys showed significantly greater mineral SOC stocks than Podzols, with differences mainly evident in the upper 30 cm, which was observed regardless of the computing methodology used (trapezoidal or spline). The adapted trapezoidal rule computing approach is hoped to facilitate the use of soil-horizon sampling in studies on SOC stocks.