Modelling Height-Diameter Allometry of Tectona grandis under Varying Site Quality in Tanzania

Single tree parameters, such as tree height (H) and diameter at breast height (D), are essential for the prediction of difficult-to-measure parameters, such as volume and biomass, which are critical for yield prediction and forest management planning. Yet direct H measurement is often demanding and challenging. While various H-D models have been developed, there is insufficient information on how site quality influences H-D allometry. This study developed generalized and site-quality-specific H-D models for Tectona grandis (teak) plantations in Longuza and Mtibwa forest plantations, Tanzania, using a large dataset comprising 7253 observations. The dataset was separated by site class (quality) using dominant height and stand age. Models were fitted using two commonly used non-linear model forms, i.e., the Weibull and Richards. The general H-D models included site classes as random effects. The model performance was assessed using goodness-of-fit statistics, bias, and repeated random holdout validation. Findings showed that site quality strongly influenced H-D allometry, with distinct model trajectories and asymptotic H values across site classes. Although the generalised mixed-effects model improved performance relative to the fixed-effects model, it exhibited increased bias at the extremes of site quality (site class I and III). In contrast, site-quality-specific models consistently produced lower bias when applied to their corresponding site classes. These findings demonstrate that having H-D models by site quality improves H prediction accuracy. It is recommended that site-quality-specific H-D models be used in operational inventories where site class information is available, while the general model provides a robust alternative for data-limited or preliminary assessments.