Site-Dependent Carbon Accumulation Dynamics in Taiwan’s Coniferous and Broad-Leaved Plantations: A Chapman–Richards Growth Modeling Approach

Accurate estimation of forest carbon storage is fundamental to climate change mitigation. However, the highly heterogeneous site conditions, together with the biological limitations of conventional linear and polynomial models, have posed considerable challenges for estimating carbon accumulation in voluntary carbon reduction projects. Based on data from 1190 permanent sample plots across Taiwan, this study developed a site-class-based carbon storage prediction model for coniferous and broad-leaved plantations in Taiwan by using the nonlinear Chapman–Richards growth function. The estimated model parameters indicated distinct carbon accumulation patterns for the two forest types. Coniferous plantations exhibited a higher model-estimated asymptotic carbon storage (1232.506 Mg CO2 ha−1), whereas broad-leaved plantations accumulated carbon more rapidly during the early stages of stand development. Because a single base model may produce substantial prediction errors when applied over large spatial scales, the stands were classified into high-, medium-, and low-site classes by using a reference age of 30 years. Site classification reduced the out-of-sample root mean square error by 56.8% for coniferous and 50.8% for broad-leaved plantations under nested cross-validation. The resulting site class models may provide useful quantitative tools for establishing baseline and project scenarios in voluntary forest carbon reduction projects.