Population-Specific Nonlinear Models for Predicting Height and Diameter Growth of Ficus variegata Blume Plantations in Indonesia

Ficus variegata Blume is a species that has the prospect of being developed for forest plantation. Its wood products can be used for woodworking, furniture, and light construction materials. This study aimed to develop models of height and diameter growth of this species based on age. In this study tree height was measured at 0.5; 1; 2; 3; 4 and 10 years, while stem diameter was measured at breast height (DBH) at 1; 2; 3; 4 and 10 years of age from 2 populations of F. variegata progeny trials with genetic material from the West Nusa Tenggara (WNT) population (n trees = 395) and the Cilacap-Pangandaran (C-P) (n trees = 393). Five nonlinear regression models were tested, with model accuracy verified by 4 criteria: root mean square error (RMSE), coefficient of determination (R2), adjusted coefficient of determination (adjusted R2), and Akaike Information Criterion (AIC). The Weibull (R2 = 0.881; RMSE =1.034) model was the best model for tree height estimation for WNT and Chapman Richards (R2 = 0.822; RMSE =1.288) for C-P. Weibull (R2 = 0.767; RMSE = 2.853) and Gompertz (R2 = 0.767; RMSE =2.853) models were the best models for tree diameter estimation for the WNT population, and Weibull (R2 = 0.765; RMSE = 2.834) and Logistic (R2 = 0.765; RMSE =2.835) for the C-P population. Our findings demonstrate that growth models are population-dependent, necessitating the use of distinct optimal models for reliable growth prediction and management in different genetic sources of F. variegata. ©2025 The authors.