Relationship between Modelling Accuracy and Inflection Point Attributes of Several Equations while Modelling Stand Diameter Distributions

PLoS One. 2015 May 27;10(5):e0126831. doi: 10.1371/journal.pone.0126831. eCollection 2015.

Abstract

In this study, seven popular equations, including 3-parameter Weibull, 2-parameter Weibull, Gompertz, Logistic, Mitscherlich, Korf and R distribution, were used to model stand diameter distributions for exploring the relationship between the equations' inflection point attributes and model accuracy. A database comprised of 146 diameter frequency distributions of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantations was used to demonstrate model fitting and comparison. Results showed that the inflection points of the stand diameter cumulative percentage distribution ranged from 0.4 to 0.6, showing a 1/2 close rule. The equation's inflection point attribute was strongly related to its model accuracy. Equation with an inflection point showed much higher accuracy than that without an inflection point. The larger the effective inflection point interval of the fitting curve of the equation was, and the closer the inflection point was to 0.5 for the equations with fixed inflection points, the higher the equation's accuracy was. It could be found that the equation's inflection point had close relationship with skewness of diameter distribution and stand age, stand density, which provided a scientific basis for model selection of a stand diameter distribution for Chinese fir plantations and other tree species.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Cunninghamia* / anatomy & histology
  • Databases, Factual
  • Forests
  • Models, Biological*
  • Models, Theoretical*

Grants and funding

This study was supported by the Scientific and Technological Task in China (No. 2015BAD09B01, 2012BAD01B01), the National Natural Science Foundation of China (31370629) and Collaborative Innovation Center of Sustaintable Forestry in Southern China, Nanjing Forestry University.