Keywords
mixed effects
random effects
Tectona grandis
How to Cite
Abstract
The study assessed nonlinear mixed-effects height-diameter models with a view to developing a height diameter model, applying a nonlinear mixed effects height-diameter modeling method on asymptotic and Michaelis Menten models and examining the fixed and random effects estimates of the models for the management of Nasarawa State University Forestry Tectona grandis plantation. Thirty (30) temporary sample plots of 0.01 ha size were randomly selected from the sampling frame with 30% sampling intensity. Diameter at breast height (DBH) and total heights of the trees within each selected plot were measured. The result of nonlinear height diameter model revealed that model two (2) had the lowest AIC (-1168.253), BIC (-1157.469) and RSE (0.02738) of model selection indices when compared to other three (3) models applied. Model (2) was the best for predicting tree heights in the study area. The result of nonlinear mixed effect height diameter model showed that random effects produced a better line of best fit when compared with fixed effects line of best fit of the asymptotic and Michaelis Menten models. In addition, it indicated an increasing trend of deterministic line with minimal residuals better than fixed effects line of best fit. The Standardized residuals was plotted against the fitted values of asymptotic and Michaelis Menten models in order to test for the normality of the data set from the plantation. The result further showed that the Tectona grandis data set was evenly distributed around the deterministic line. Therefore, nonlinear mixed-effects height diameter model provides access to both fixed effects and random effect estimates of data set in which random effects estimate provided a better estimates for tree heights unlike the commonly used generalized ordinary least square height-diameter modeling method.
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