Growth prediction of sago palm (Metroxylon sagu) in Thailand using the Linear Mixed-effect model

Abstract

Abstract. Jariyapong M, Roongtawanreongsri S, Romyen A. Somboonsuke B, 2021. Growth prediction of sago palm (Metroxilon sagu) in Thailand using the Linear Mixed-effect model. Biodiversitas 22: 5293-5301. A living sago palm is a potential resource for carbon sequestration in peat swamp. It can provide benefits for agriculturists and environmental sustainability. This study’s aim is to create a growth prediction of sago palm size at individual ages using a linear mixed-effect model. The sample palms were selected from 43 sago palm parents which have been re-measured and recorded at intervals of 2-20 years. The experimental plot was on deep peat soil (with peat depth at over 2.5 m) at Phru Todaeng Swamp Forest, Southern Thailand. To find the best model for growth prediction, we used a traditional linear model (Model 1 and 4) and linear mixed-effect models (Model 2, 3, 5 and 6) to generate the relationship between age, diameter, and height. The best model was selected based on considering the smallest Akaike’s Information Criteria (AIC), the Bayes Information Criteria (BIC), and the absolute mean error (AME). The results showed the smallest values of AIC, BIC, and AME in Model 3 which produced the best model for predicting the total overall growth in sago palm. The age and diameter under the independent variable were statistically significant (? = 0.01); these two factors influenced the sago palm height rate. Hence, this model can be used to predict the overall growth of sago palms, which is useful for biomass estimation and calculating the carbon sequestration of planted sago palms. The carbon sequestration in living sago palm can be compared with other commercial crops for future benefit. This approach can lead to a future solution for wetland management and land-use changes.