### Abstract

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.

Original language | English (US) |
---|---|

Pages (from-to) | 204-212 |

Number of pages | 9 |

Journal | Forest Science |

Volume | 50 |

Issue number | 2 |

State | Published - Apr 1 2004 |

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### All Science Journal Classification (ASJC) codes

- Forestry
- Ecology
- Ecological Modeling

### Cite this

*Forest Science*,

*50*(2), 204-212.

}

*Forest Science*, vol. 50, no. 2, pp. 204-212.

**Improving taper equations of loblolly pine with crown dimensions in a mixed-effects modeling framework.** / Leites, Laura P.; Robinson, Andrew P.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Improving taper equations of loblolly pine with crown dimensions in a mixed-effects modeling framework

AU - Leites, Laura P.

AU - Robinson, Andrew P.

PY - 2004/4/1

Y1 - 2004/4/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=2642585888&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=2642585888&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:2642585888

VL - 50

SP - 204

EP - 212

JO - Forest Science

JF - Forest Science

SN - 0015-749X

IS - 2

ER -