Comprehensive forest carbon accounting requires reliable estimation of soil organic carbon (SOC) stocks. Despite being an important carbon pool, limited information is available on SOC stocks in global forests, particularly for forests in mountainous regions, such as the Central Himalayas. The availability of consistently measured new field data enabled us to accurately estimate forest soil organic carbon (SOC) stocks in Nepal, addressing a previously existing knowledge gap. Our method involved modelling plot-based estimates of forest SOC using covariates related to climate, soil, and topographic position. Our quantile random forest model resulted in the high spatial resolution prediction of Nepal's national forest SOC stock together with prediction uncertainties. Our spatially explicit forest SOC map showed the high SOC levels in high-elevation forests and a significant underrepresentation of these stocks in global-scale assessments. Our results offer an improved baseline on the distribution of total carbon in the forests of the Central Himalayas. The benchmark maps of predicted forest SOC and associated errors, along with our estimate of 494 million tonnes (SE = 16) of total SOC in the topsoil (0-30 cm) of forested areas in Nepal, carry important implications for understanding the spatial variability of forest SOC in mountainous regions with complex terrains.
© 2023. The Author(s).