In the context of rapid global change and increasing anthropogenic pressures on ecosystems, robust monitoring of soil health and ecosystem functioning is essential to support evidence-based and data-driven management. Among soil functions, the capacity to store and cycle carbon is critical, both for climate regulation and broader ecosystem service provision. However, quantifying soil organic carbon (SOC) dynamics across spatial and temporal scales remains challenging due to the cost, labour intensity, and limited spatial coverage of conventional sampling approaches.

This study explores the potential of combining digital soil mapping (DSM) approaches with spectroscopic techniques (NIRS and MIRS) as scalable tools for monitoring soil carbon dynamics and identifying SOC hotspots. We define hotspots as areas with either high carbon stocks or pronounced susceptibility to change under management or disturbance. Using datasets from ongoing monitoring initiatives in Flanders and across Europe—including SOB4ES, INFORMA, LEGACY and AARDEWERK—we assess how integrated data-driven approaches can improve the spatial targeting and temporal tracking of management and disturbances on soil carbon.
Case studies span forest ecosystems, grasslands and peatlands, focusing on the effects of management interventions and disturbances such as drainage, rewetting, eutrophication and fire. Spectroscopic methods enable rapid, cost-effective estimation of SOC, while DSM integrates environmental covariates to extrapolate these observations across landscapes. Together, these approaches provide a framework for identifying priority areas for intervention and for evaluating management outcomes.