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October 10, 2025Forest Science0 citations

Polymorphic Site Index Equations for Loblolly Pine Based on a Segmented Polynomial Differential Model

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JDJames S. DevanHBHarold E. Burkhart

Key Points

  • Using segmented regression, the model predicts site index more effectively than traditional equations.
  • Height increment submodels incorporating height, age, and age squared showed superior predictive accuracy.
  • Comparative analysis confirms the model's effectiveness using data from both parameter estimation and independent sources.
  • The methodology developed here may enable more precise forestry management practices and tree growth predictions.

Abstract

Abstract Site index equations for old-field plantations and natural stands of loblolly pine were produced from the integrated form of height increment models fitted by segmented regression techniques. After transforming the stem analysis data as the natural logarithm of height and the inverse of age, height increment submodels were fitted for various combinations of the independent variables height, age, and age squared for two segments with a join point being a function of age. Comparisons of the resultant curves indicated that the model having all three variables in both segments was superior to other forms and to published equations in predicting site index of trees both from the data used in parameter estimation and from an independent source. Forest Sci. 28:544-555.

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Cite This Study

Devan et al. (1982) studied this question.

synapsesocial.com/papers/68e865147ef2f04ca37e5221https://doi.org/10.1093/forestscience/28.3.544
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