Drivers of soil organic carbon from temperate to alpine forests: a model-based analysis of the Swiss forest soil inventory with Yasso20

Predicting soil organic carbon (SOC) stocks and their dynamics in forest ecosystems is crucial for assessing forest C balance, but the relative importance of key controls – litter inputs, climate, and soil properties – remains uncertain. Here, we linked SOC stocks at 556 old-growth Swiss forest sites from 350 to 2000 m a.s.l. to a comprehensive set of environmental variables, encompassing climate (mean annual precipitation, MAP: 700–2100 mm, mean annual temperature, MAT: 0–12 °C), soil properties, and forest types. In addition, we compared measured SOC stocks with stocks simulated by the Yasso20 model, which is widely used for reporting SOC stock changes. Since Yasso20 is driven solely by litter inputs and climate, deviations between modeled and measured stocks can reveal the significance of additional factors such as organo-mineral interactions that we hypothesized to be crucial for SOC stocks. Total SOC stocks exhibited distinct regional patterns, with the highest values in the Southern Alps, where soils are rich in Fe and Al oxides and receive high MAP. On average, total SOC stocks simulated by Yasso20 aligned well with measured SOC stocks (13.7 vs. 13.2 kg C m−2). However, the model did not capture regional SOC variability, underestimating SOC stocks by up to 7 kg C m−2 in the Southern Alps. The underestimation was primarily explained by soil mineral properties, with their influence depending on soil pH. In soils with pH ≤ 5, exchangeable Fe had the strongest effect on Yasso20 deviations from measured stocks, while in soils with pH > 5, exchangeable Ca had the strongest effect on model deviations. Beyond Fe and Ca, MAP emerged as an important driver of total SOC stocks, with SOC stocks increasing with MAP. At higher elevations, this coincided with low MAT and a high share of conifers. While Yasso20 accounted for MAT, Yasso20 underestimated SOC stocks for MAP > 1400 mm. Overall, our results indicate that mineral-driven SOC stabilization and climate are the primary drivers of Yasso20 deviations from measured SOC stocks. Incorporating mineral-driven soil organic matter stabilization and coupling to a soil water model can improve the modeling of SOC stocks. However, further studies are needed to verify how C stabilization mechanisms and soil moisture can be included in model-based estimates of SOC stock changes, which is the primary application of Yasso in greenhouse gas inventories.