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Advancing Height–Diameter Modeling in Pine Stands: A Comparative Analysis of Mixed-Effects Allometry and Age-Dependent Covariates

DOI : https://doi.org/10.36349/easjals.2026.v09i05.001
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Accurate estimation of tree height from diameter at breast height (DBH) is essential for biomass estimation, productivity assessment, and carbon accounting. This study evaluated five modeling frameworks namely: linear, logarithmic, polynomial, fixed allometric, and mixed-effects allometric, using measurements from 432 pine trees collected across managed plantation plots in central Uganda. The dataset covered a wide DBH range (5.2–54.8 cm), ensuring representation across multiple growth stages. Among fixed-effects models, the polynomial structure achieved strong predictive performance (R² = 0.914). However, the age-integrated mixed-effects allometric model produced superior predictive reliability (R² = 0.932; RMSE = 1.48 m) and substantially reduced Akaike Information Criterion (AIC) values. Residual analysis indicated stable variance and absence of systematic error patterns. The integration of stand age therefore, significantly improved prediction accuracy and captured vertical growth differences among developmental stages / ages and subsequently offer practical benefits for forest inventory and carbon estimation programs.

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