Revista Chapingo Serie Ciencias Forestales y del Ambiente
Local-global and fixed-random parameters to model dominant height growthof Pinus pseudostrobus Lindley
ISSNe: 2007-4018   |   ISSN: 2007-3828
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Keywords

Site quality
dynamic equations
mixed effects
site index
dummy variable

How to Cite

García-Espinoza, G. G. ., Aguirre-Calderón, O. A. ., Quiñonez-Barraza, G., Alanís-Rodríguez, E., González-Tagle, M. A. ., & García-Magaña, J. J. . (2018). Local-global and fixed-random parameters to model dominant height growthof Pinus pseudostrobus Lindley. Revista Chapingo Serie Ciencias Forestales Y Del Ambiente, 25(1), 141–156. https://doi.org/10.5154/r.rchscfa.2018.06.047

##article.highlights##

  • Dynamic dominant height equations of Pinus pseudostrobus were compared.
  • Trees were obtained from commercial forest plantations in Michoacan.
  • Modeling approaches identified the dominant height growth of P. pseudostrobus.
  • The accuracy of the dummy variable approach was slightly higher than that of the mixed- effects models.
  • The generalized algebraic difference equation better described the growth pattern.

Abstract

Introduction:  Dominant height and site index (SI) models consider average parameters for asample or population. The dummy variable (DV) modeling approach generates global and localparameters, while mixed-effects models (MEM) generate fixed and random ones for each tree orplot.
Objective:  To fit and compare dynamic dominant height equations with the DV and MEMapproaches for Pinus pseudostrobus Lindley in commercial forest plantations in Nuevo San JuanParangaricutiro, Michoacán, Mexico.
Materials   and   methods:   Three   algebraic   difference   approach   (ADA)   equations   and   onegeneralized algebraic difference approach (GADA) equation, based on the Chapman-Richardsmodel, were fitted with the SI parameter associated as local or random for each tree. Thedatabase used considered stem analysis of 41 trees.
Results and discussion: The accuracy of the fitted equations with DV and MEM was similar,according to the fitting statistics and the trajectories of the SI curves at the base age of 20 years.In the ADA equations, the polymorphic curve showed greater statistical efficiency with bothapproaches when the growth rate parameter depended on the SI. However, the GADA equationgenerated curves that better described the growth pattern; the highest accuracy was obtained withthe DV approach.
Conclusions:  The use of the GADA equation with DV is an accurate tool for classifying theproductivity of commercial forest plantations, which will allow forest management planningbased on site quality.

https://doi.org/10.5154/r.rchscfa.2018.06.047
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References

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