Abstract

This study focuses on two ecologically and economically important tree species of the Western Himalayas—Ficus auriculata and Phyllanthus emblica—to develop an improved hybrid methodology for volume estimation. Ficus auriculata is highly valued for its use as fodder and in ethnomedicine, with fruit rich in bioactive compounds exhibiting antioxidant and therapeutic properties. Phyllanthus emblica (commonly known as amla) is renowned for its medicinal fruit, widely used in traditional health systems and vital to the biodiversity of dry forest ecosystems. Using GPS and GIS tools, sampling plots were geolocated and mapped across varying altitudes to ensure spatial accuracy. More than 100 individual trees of each species were sampled, with detailed biometric data collected—including girth, height, branching patterns, and frustum dimensions. A hybrid volume estimation method was developed by integrating Smalian’s and Huber’s formulas. This non-distructive approach minimizes bias inherent in using either method independently and is particularly effective for trees with irregular taper or frustum shapes. Regression models for volume estimation were developed and validated, followed by the derivation of biomass and carbon stock using species-specific allometric equations. Equations were formulated using diameter at breast height (DBH) alone and in combination with height, and evaluated using statistical criteria such as R², RMSE, and AIC. This research presents a scientifically robust and field-applicable methodology for accurate estimation of tree volume, biomass, and carbon stock. The proposed hybrid method offers a practical and precise alternative for forest inventory and carbon sequestration assessments in complex Himalayan ecosystems.