Application of mixed-effects modelling approach in tree height prediction models
Abstract
In routine forest inventories, total tree height and diameter at breast height are very
important growth parameters assessed to describe and estimate the stand structure and
volume, respectively, of the forest. Height-diameter models are often used to predict the
height for trees where only diameter is measured for all trees in a plot and a few trees
measured for total height. This is because, tree diameter can be determined easily and
accurately at little cost and time, but total tree height is more difficult to measure, time
consuming and more costly. Africa has lagged behind in adopting modelling techniques
that can assist in estimating tree height with higher precision and accuracy than that
obtained using ordinary least squares and ordinary nonlinear least squares (which are
the commonly used approaches). A study was carried out to demonstrate the utility
of mixed-effects modelling approach in tree height prediction models. The ChapmanRichards
model was selected as base height-diameter model and was fitted to model data
using Ordinary Nonlinear Least Squares method. Using the same base model and fit
data, a mixed-effects model was constructed using mixed-effects modeling approach. The
two models were then compared in terms of predictive accuracy on independent data
set (as well as model fit data for comparison). The mixed-effects model had a better
predictive accuracy on both data sets, especially the independent data. Superiority of
the mixed-effects model was more clearer when the two models were compared on a
plot-by-plot basis. Forest modelers and managers in Africa should consider using mixedeffects
modelling approach in development and use of height-diameter models in order to
estimate tree heights with higher precision and accuracy.
Publisher
University of Nairobi