Resumo

Soil organic carbon (SOC) is a key indicator for assessing pasture degradation. This study presents an integrated, field-based approach to analyzing SOC dynamics in pastures of Rio de Janeiro state (Brazil). Unlike methods based exclusively on remote sensing or modeling, our analysis is based on 350 georeferenced soil samples collected by Embrapa Solos and complemented by historical land use data, providing robust and reliable empirical evidence. Statistical methods (ANOVA, Tukey test), geostatistical interpolation (kriging), and unsupervised clustering (k-means) were used to characterize the spatiotemporal distribution of SOC. The results revealed patterns linked to both topographic and anthropogenic drivers, enabling the objective delineation of degraded versus non-degraded pastures. SOC levels below 40 g/kg in areas under 300 m elevation were strongly associated with degradation due to intensive use. In contrast, degradation at higher altitudes was primarily linked to sloping terrain more prone to water erosion. This methodological approach demonstrates the potential of combining field data with data mining tools to detect degradation patterns and inform targeted land management. The findings reaffirm SOC as a vital indicator of soil quality and highlight the importance of sustainable pasture practices in conserving carbon stocks and mitigating climate change. The proposed threshold-based method offers a practical foundation for diagnosing degraded pastures and identifying priority areas for restoration.