Biomass equations and annual growth of various Eucalyptus clones in commercial plantations across Thailand

Abstract

Plantation forestry is pivotal in meeting global timber and fiber demands while promoting sustainable practices. Eucalyptus plantations, renowned for their rapid growth and adaptability, have significantly expanded in tropical regions such as Thailand. Improved Eucalyptus clones have enhanced productivity, emphasizing the role of genetic improvement programs. Accurate biomass estimation in these plantations is crucial for sustainable management and bioenergy production. This study employs a nonlinear mixed model approach to evaluate tree variables combined with rotation, clones, and region on aboveground biomass (AGB) estimation. The results showed that the "rotation, clones, region" model emerged as the most precise, achieving the highest R² and the lowest SEE, ASE, and MPSE values. However, over-parameterization is a concern. The more straightforward "clone" model performed well, achieving a high R² and relatively low prediction error, with no systematic bias and comparable ASE, MPE, and MPSE values, making it a strong choice when fewer predictor variables are preferred. Our results revealed that clones H4 and K7 for the northeastern region and K58 for the eastern region show the highest annual productivity, with growth rates up to 20 t ha−1 year−1. The rapid AGB increment in clones K58, K62, and K7 during the first rotation suggests improved performance in subsequent rotations. As in eastern Thailand, selecting less arid sites can enhance these clones' AGB productivity. Additionally, intensive silvicultural practices could further boost their productive efficiency.