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Tree Size Distribution Modelling : Moving from Complexity to Finite Mixture

초록

영어

Tree size distribution modelling is an integral part of forest management. Most distribution yield systems rely on some flexible probability models. In this study, a simple finite mixture of two components two-parameter Weibull distribution was compared with complex four-parameter distributions in terms of their fitness to predict tree size distribution of teak (Tectona grandis Linn f) plantations. Also, a system of equation was developed using Seemingly Unrelated Regression wherein the size distributions of the stand were predicted. Generalized beta, Johnson’s SB, Logit-Logistic and generalized Weibull distributions were the four-parameter distributions considered. The Kolmogorov-Smirnov test and negative log-likelihood value were used to assess the distributions. The results show that the simple finite mixture outperformed the four-parameter distributions especially in stands that are bimodal and heavily skewed. Twelve models were developed in the system of equation-one for predicting mean diameter, seven for predicting percentiles and four for predicting the parameters of the finite mixture distribution. Predictions from the system of equation are reasonable and compare well with observed distributions of the stand. This simplified mixture would allow for wider application in distribution modelling and can also be integrated as component model in stand density management diagram.

목차

Abstract
Introduction
Materials and Methods
Data
Four-parameter distribution models
Finite mixture (FM) distribution
Fitting and evaluation
Modelling the diameter distribution with stand variables
Result and Discussion
Fits of the distribution
Modeling the diameter distribution with FM
Conclusion
References

저자정보

  • Friday Nwabueze Ogana Department of Social and Environmental Forestry, University of Ibadan, Ibadan 200284, Nigeria
  • Onyekachi Chukwu Department of Social and Environmental Forestry, University of Ibadan, Ibadan 200284, Nigeria
  • Samuel Ajayi Department of Forestry and Wildlife Resources Management, Cross River University of Technology, Obubra 5511114, Nigeria

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