Allometric models for estimating above-ground biomass and carbon stock of major shrub species in Northern dry mixed deciduous forest in Shivalik foothills, India

This study aimed to develop allometric models for estimating above-ground biomass (AGB) and carbon stocks (ACS) in three dominant shrub species- Lantana camara , Justicia adhatoda , and Murraya koenigii -within the Northern Dry Mixed Deciduous Forest of the Shivalik foothills, India. Species were selected based on density, basal area, and importance value index. Biometric variables including diameter at ground level (D 0 ), diameter at 15 cm (D 15 ), height (H), and crown area (CA) were recorded and used individually or in combination as predictors in two forms of power equations. Forty-eight fixed 5 m × 5 m quadrats were randomly sampled post-rainy season (September–November) for phytosociological assessment; destructive biomass sampling was conducted in 36 of them. Model parameters were estimated using a weighted maximum likelihood non-linear fixed effects approach and validated using Monte Carlo cross-validation. Species-specific models using D 0 and H for M. koenigii and L. camara , as well as CA and H for J. adhatoda , were found most effective. A multi-species model using D 15 and H also performed reliably. Estimated total AGB and ACS were 5.24 ± 0.55 Mg ha −1 and 2.49 ± 0.26 Mg ha −1 , respectively, with L. camara contributing 72.50 %, M. koenigii 25.60 %, and J. adhatoda 1.90 %. Therefore, the models offer a non-destructive solution to longstanding challenges in estimating the AGB of the shrub species grown under similar conditions and also emphasizing the critical role of shrubs in overall forest carbon storage. These models provide robust estimates of biomass and carbon stock, supporting their application in carbon credit monitoring and assessment. • L. camara had highest carbon (0.46–0.49), above J. adhatoda and M. koenigii . • D 0 for M. koenigii , D 15 for L. camara , and height for J. adhatoda best predict AGB. • D 15 emerged as the most suitable predictor in the multi-species model. • Three-parameter AGB models beat two-parameter for all three species. • Total density: 15,167 shrubs ha −1 ; AGB: 5.24 ± 0.55 Mg ha −1 ; ACS: 2.49 ± 0.26 Mg ha −1