Improving taper equations of loblolly pine with crown dimensions in a mixed-effects modeling framework

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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Forest science 2004-04, Vol.50 (2), p.204-212
Hauptverfasser: Leites, L.P, Robinson, A.P
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
ISSN:0015-749X
1938-3738
DOI:10.1093/forestscience/50.2.204