Carbon stock quantification holds vital significance in evaluating the climate change mitigation potential and carbon management of forest ecosystems. The current study was designed to quantify the biomass carbon stocks in the lesser Himalayan subtropical broadleaf forests of the Kashmir region. Primary data about the structural attributes and species composition of the local forests was collected through quadrat-based sampling followed by the application of allometric equations for the estimation of forest biomass. The biomass carbon stocks were calculated as 135.2 Mg ha-1 ranging from a maximum of 226.64 Mg ha-1 to a minimum of 11.83 Mg ha-1. The tree layer contributed a biomass carbon content of 134.67 Mg ha-1 making up to 99% share in the total forest biomass as compared to the shrub and herb layers with a very low biomass carbon value of 0.37 Mg ha-1 and 0.17 Mg ha-1 respectively. Dalbergia sissoo was recorded as the most dominant tree species with a biomass carbon stock value of 40.70 Mg ha-1 followed by Mallotus philippensis (30.09 Mg ha-1) and Ficus palmata (20.11 Mg ha-1). Principal Component Analysis revealed that the variations in the local carbon stocks were significantly correlated with the distribution pattern of the dominant tree species. Generalized Linear models showed a strong affinity of biomass carbon reserves with the structural attributes of the forest stands. This study generated a standard scientific dataset of the local biomass carbon stocks in the subtropical broadleaf forests with dynamic implications in sustainable forestry and carbon pool management in the region.
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