MIXED-EFFECTS MODELS FOR PREDICTING EARLY HEIGHT GROWTH OF FOREST TREES PLANTED IN SARAWAK, MALAYSIA

Authors

  • WM Wan Razali
  • T Abdul Razak
  • Mohamad Azani
  • K Kamziah

Keywords:

Akaike Information Criterion, Bayesian Information Criterion, indigenous timber species, rehabilitation programme

Abstract

Total height growth models as a function of basal tree diameter at 10 cm above ground (D10) for five indigenous species in Sarawak, namely, Calophyllum sclerophyllum, Dryobalanops beccarii, Shorea mecistopteryx, Shorea leprosula and Shorea brunnescens, were developed using mixed-effects models. A mixed-effects model is an extension of a random-coefficient regression in which fixed-effect coefficients are included to account for variations between and correlations within tree species, and is known to produce consistent estimates of the fixed coefficients and their standard errors. Linear, nonlinear, logistic and Chapman–Richards mixed-effects models were used to fit total tree height to D10. Species were treated as random-effect and D10 fixed-effect in the models. Based on smallest value of Akaike Information Criterion and Bayesian Information Criterion, the linear model H = (β0 + b0) + (β1 + b1) D10 indicated the best fit for all five species. Availability of height growth model helps in the early stage of species selection, whereby height growth is a dominant factor in
choosing a species for rehabilitation programme, thus ensuring high species productivity and increased financial viability of the programme.

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Published

2015-04-30

How to Cite

WM Wan Razali, T Abdul Razak, Mohamad Azani, & K Kamziah. (2015). MIXED-EFFECTS MODELS FOR PREDICTING EARLY HEIGHT GROWTH OF FOREST TREES PLANTED IN SARAWAK, MALAYSIA. Journal of Tropical Forest Science (JTFS), 27(2), 267–276. Retrieved from https://jtfs.frim.gov.my/jtfs/article/view/917

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