A simple soil organic carbon level metric beyond the organic carbon-to-clay ratio

Soil is a precious and non-renewable resource that is under increasing pressure and the development of indicators to monitor its state is pivotal. Soil organic carbon (SOC) is important for key physical, chemical and biological soil properties and thus a central indicator of soil quality and soil health. The content of SOC is driven by many abiotic factors, such as texture and climate, and is therefore strongly site-specific, which complicates, for example, the search for appropriate threshold values to differentiate healthy from less healthy soils. The SOC:clay ratio has been introduced as a normalized SOC level metric to indicate soils' structural condition, with classes ranging from degraded (<1:13) to very good (>1:8). This study applied the ratio to 2958 topsoils (0–30 cm) in the German Agricultural Soil Inventory and showed that it is not a suitable SOC level metric since strongly biased, misleading and partly insensitive to SOC changes. The proportion of soils with SOC levels classified as degraded increased exponentially with clay content, indicating the indicator's overly strong clay dependence. Thus, 94% of all Chernozems, which are known to have elevated SOC contents and a favourable soil structure, were found to have either degraded (61%) or moderate (33%) normalized SOC levels. The ratio between actual and expected SOC (SOC:SOCexp) is proposed as an easy-to-use alternative where expected SOC is derived from a regression between SOC and clay content. This ratio allows a simple but unbiased estimate of the clay-normalized SOC level. The quartiles of this ratio were used to derive threshold values to divide the dataset into the classes degraded, moderate, good and very good. These classes were clearly linked to bulk volume (inverse of bulk density) as an important structural parameter, which was not the case for classes based on the SOC:clay ratio. Therefore, SOC:SOCexp and its temporal dynamic are proposed for limited areas such as regions, states or pedoclimatic zones, for example, in a soil health monitoring context; further testing is, however, recommended.