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

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

Blog Article

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 Multi-Tools 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 Kratom Powder posterior distribution of parameters of self-thinning line.The research of self-thinning relationship could be benefit from the use of hierarchical Bayesian method.