Improving Taper Equations of Loblolly Pine with Crown Dimensions in a Mixed-Effects Modeling Framework

By L. Leites, Andrew P. Robinson. Forestry sciences, 2004

88 citations recorded by the source corpus.

A mixed-effects modeling framework was applied to Max and Burkhart's (1976) (MB) taper equation for loblolly pine (Pinus taeda L.). The advantages of such a strategy over ordinary least squares were: (1) more accurate specification of the correlation structure of the data and (2) the ability to assess the potentially explainable variation at the tree level. Significant relationships were established between tree-level crown dimensions and parameter estimates. The study data comprised 197 plantation-grown loblolly pine trees of 10 different ages in Uruguay. Four versions of MB were evaluated: (1) the original equation, (2) the original equation fitted with mixed effects, and two adapted versions: (3) the first included crown variables and fixed effects, (4) the second included crown variables and mixed effects. The crown variables were tree-level crown length and crown length ratio. The best of the four competing equations included both of the crown variables as well as tree-level random effects, suggesting that some linear tree-level variability may yet be explained by variables not considered in this study. Testing on an independent validation data set did not show over-fitting problems. For prediction purposes, the equations with added crown variables were more precise but not less biased. FOR. SCI. 50(2):204–212.

Subfields: Ecology, Nature and Landscape Conservation, Plant Science

View Paper: https://www.semanticscholar.org/paper/5b9c5ceb1fbf52a8b9fa6d832075059bf3f5ce28

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Citations in the corpus

Estimating and predicting bark thickness for seven conifer species in the Acadian Region of North America using a mixed-effects modeling approach: comparison of model forms and subsampling strategies (2011, background): “…height–age relationships (Fang and Bailey 2001; Wang et al. 2007; Zhao et al. 2005; Calegario et al. 2005), individual tree taper profiles (Garber and Maguire 2003; Leites and Robinson 2004; Li and Weiskittel 2010), and various other attributes (Gregoire et al. 1995; Hall and Clutter 2004).”
Modeling Forest Trees and Stands (2012, methodology): “Leites and Robinson (2004) also used the Max and Burkhart (1976) segmented taper equation to explore relationships between taper parameters and crown variables.”
Nonlinear mixed-effects modeling of variable-exponent taper equations for lodgepole pine in Alberta, Canada (2009, background): “Data required for fitting taper equations are mostly hierarchical, with multiple measurements along the stem taken on each sample tree (Leites and Robinson 2004).”
Forest Growth and Yield Modeling (2011, background): “…basal area (Gregoire et al., 1995) and dominant height growth (Fang and Bailey, 2001; Wang et al., 2007b), stem taper (Garber and Maguire, 2003; Leites and Robinson, 2004), individual tree increment (Calegario et al., 2005; Weiskittel et al., 2007a), cumulative bole volume (Gregoire and…”
Calibrating fixed- and mixed-effects taper equations (2011, methodology): “…mixedeffects models have been applied to predict tree taper because they take into account the correlation among multiple diameter measurements on an individual stem (Garber and Maguire, 2003; Leites and Robinson, 2004; Trincado and Burkhart, 2006; Lejeune et al., 2009; Yang et al., 2009).”