Spatial modelling and drivers of soil organic carbon across successional communities in tropical deciduous forests: insights from Northwest Himalayan foothills

Abstract

Soil Organic Carbon (SOC), a key component of the global carbon cycle, remains poorly understood with respect to its linkage to ecological succession. The study aimed to unravel SOC dynamics during ecological succession in a tropical deciduous forest in the foothills of the northwest Himalaya (NWH), India. Ecological parameters derived from satellite remote sensing in conjunction with field sampled SOC was used to predict soil organic carbon density (SOCD) employing four techniques viz., multiple linear regression (MLR), random forest (RF), support vector machines (SVM), and extreme gradient boosting (XGBoost). Cross-validation with hundred replications was employed to evaluate the performance of different models. Significant variability in SOCD was observed across the study area varying from 2.7 t/ha to 65.7 t/ha. The RF model with RMSE of 12.17, R² of 0.81 and mean bias of 0.16 performed best among all the models. Vegetation parameters emerged as primary predictors, with SOC accumulation increasing alongside vegetation succession—from 24.7 t/ha in pioneer stages to 35.9 t/ha in climax community. The mature forests with dense, tall canopies and substantial biomass contribute significantly to soil carbon storage. For the majority of the tree community types, the uncertainty in predicted SOCD remained below 3 t/ha except for the post-climax community (6–9 t/ha) due to high SOCD and moisture. Study stresses on the roles of successional stages in carbon sequestration in tropical deciduous forests, underscore the importance of the protection of these communities to safeguard SOC stocks effectively.