Characterizing Diameter Distributions for Uneven-Aged Pine-Oak Mixed Forests in the Qinling Mountains of China

Shuaichao Sun,Quang V Cao,Tianjian Cao

doi:10.3390/f10070596

Abstract

Pine-oak mixed forests in the Qinling Mountains are an essential part of the ecosystem in Northwestern China. Diameter distribution models for four species groups of pine-oak mixed forests were developed using the Weibull function. Both moment and hybrid estimation approaches were used to predict the Weibull parameters. For each approach, three fitting methods (maximum likelihood estimator regression (MLER), cumulative distribution function regression (CDFR) and modified CDFR) were employed to obtain estimates for coefficients of regression equations to predict Weibull parameters. Overall results indicated that the Moment Estimation approach was better than the Hybrid approach, and that the CDFR method was superior to the MLER and modified CDFR methods. The combination of Moment Estimation and CDFR is recommended. The models constructed in this study enable the prediction of the diameter distribution of uneven-aged pine-oak mixed forests in the Qinling Mountains based on common stand-level information.

Highlights

As the major forest type at mid-elevation (1000–2300 m) in the Qinling Mountains, pine-oak mixed forests dominated by Pinus tabulaeformis, Pinus armandii and Quercus aliena var. acuteserrata have been considered as the cornerstone of the local ecosystem, which supports a huge variety of plants and wildlife
The objectives of this study were to: (1) develop diameter distribution evaluate two approaches to predict the parameters of the Weibull function for pine-oak forest models for uneven-aged pine-oak mixed forests in the Qinling Mountains of China; (2) evaluate two diameter distributions; and (3) evaluate three methods of model fitting for each of the above approaches to predict the parameters of the Weibull function for pine-oak forest diameter distributions; prediction approaches
The overall results indicated that the Moment Estimation approach was better than the Hybrid approach, and that the cumulative distribution function regression (CDFR) method was superior to the Maximum Likelihood Estimator Regression (MLER) and modified CDFR

Summary

Introduction

As the major forest type at mid-elevation (1000–2300 m) in the Qinling Mountains, pine-oak mixed forests dominated by Pinus tabulaeformis, Pinus armandii and Quercus aliena var. acuteserrata have been considered as the cornerstone of the local ecosystem, which supports a huge variety of plants and wildlife. As the major forest type at mid-elevation (1000–2300 m) in the Qinling Mountains, pine-oak mixed forests dominated by Pinus tabulaeformis, Pinus armandii and Quercus aliena var. The pine-oak forests in the Qinling Mountains were naturally regenerated after harvesting during the 1960s and 1970s. The pine-oak forests are mostly in the middle of a succession process. As the most direct and measurable factor, diameter is generally related to other important variables including basal area, density and volume. This makes the diameter distribution model a useful tool to provide more detailed information about the stand without additional inventory costs [1]. As a linkage between the whole stand model and the individual tree model, the diameter distribution model has been extensively explored by researchers and foresters [2,3,4]

Objectives

Methods

Results

Conclusion