A Hierarchical Bayesian Model to Predict Self-Thinning Line for Chinese Fir in Southern China

Self-thinning is a dynamic equilibrium between forest growth and mortality at full site occupancy. Parameters of the self-thinning lines are often confounded by differences across various stand and site conditions. For overcoming the problem of hierarchical and repeated measures, we used hierarchica...

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Bibliographic Details
Published in:PloS one 2015-10, Vol.10 (10), p.e0139788-e0139788
Main Authors: Zhang, Xiongqing, Zhang, Jianguo, Duan, Aiguo
Format: Article
Language:English
Subjects:
Alnus rubra
Animals
Bayes Theorem
Bayesian analysis
China
Collaboration
Computer simulation
Cunninghamia - growth & development
Cunninghamia lanceolata
Ecology
Forest development
Forest growth
Forestry
Forests
Generalized linear models
Growth models
Laboratories
Mathematical models
Models, Theoretical
Mortality
Natural resources
Parameters
Plantations
Planting density
Principal components analysis
Pseudotsuga menziesii
Soil types
Statistical methods
Stochasticity
Thinning
Trees
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Summary:Self-thinning is a dynamic equilibrium between forest growth and mortality at full site occupancy. Parameters of the self-thinning lines are often confounded by differences across various stand and site conditions. For overcoming the problem of hierarchical and repeated measures, we used hierarchical Bayesian method to estimate the self-thinning line. The results showed that the self-thinning line for Chinese fir (Cunninghamia lanceolata (Lamb.)Hook.) plantations was not sensitive to the initial planting density. The uncertainty of model predictions was mostly due to within-subject variability. The simulation precision of hierarchical Bayesian method was better than that of stochastic frontier function (SFF). Hierarchical Bayesian method provided a reasonable explanation of the impact of other variables (site quality, soil type, aspect, etc.) on self-thinning line, which gave us the posterior distribution of parameters of self-thinning line. The research of self-thinning relationship could be benefit from the use of hierarchical Bayesian method.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0139788