云南松林分平均胸径生长模型及模型参数环境解释

云南松Pinus yunnanensis作为中国西南地区的主要建群树种，在西南地区占有重要地位，研建其林分生长模型以及对模型参数进行环境解释，可为气候变暖背景下研究云南松林分的生长动态提供经验模型。基于云南省森林资源连续清查数据和气象数据，以为云南松林为研究对象，结合6种基本理论方程，采用非线性回归方法构建林分平均胸径的生长模型，并对最优模型的参数进行环境解释。结果表明:①以决定系数（R2）和均方根误差（E_RMS）为指标，从6个基础模型中选定林分平均胸径最优生长模型为坎派兹（Gompertz）模型，R2达到0.648，E_RMS为3.384；②将各环境影响因子同时引入到2个参数组合位置上时的模型作为解释该环境因子对林分平均胸径生长模型影响的最佳模型形式；③各环境影响因子对林分胸径生长模型的影响程度大小排序为湿润指数 > 海拔 > 年平均降水量 > 潜在蒸散量 > 年平均气温 > 温暖指数 > 郁闭度 > 年均生物学温度 > 坡度。④地形因子和气候因子与林分平均胸径生长之间的关系有正有负，地形因子中的海拔因子对林分平均胸径的影响不大，气象因子中温度对林分平均胸径生长的影响是通过对降水的制约来实现的。

Average DBH growth model of a stand with environmental parameters for Pinus yunnanensis in central Yunnan,China

Pinus yunnanensis is the main dominant species and plays an important role in southwest China. An empirical model was provided to study growth dynamics of P. yunnanensis with global climate warming using a stand growth model and analyzing the relationship between parameters of an optimal model and a model with environmental impact factors. The growth model for average DBH of a stand was established with a nonlinear regression model. The model was based on data in the continuous forest inventories (CFI) for Yunnan Province along with meteorological data and then combined with six kinds of fundamental theoretical equations. Results showed: (1) the Gompertz Model was selected from the optimal model using the parameters of maximum coefficient of determination (R2=0.648) and the minimum root mean square error (R_MSE=3.384). (2) The degree of influence for environmental impact factors on the DBH growth model was humidity index > altitude > mean annual precipitation > potential evapotranspiration > mean annual temperature > warmth index > canopy density > soil thickness > slope. (3) The relationship of average DBH growth of the stand to topographic factors and climatic factors were positive or negative. Topographic factors, such as slope, had little effect on stand DBH growth. Also, temperature influenced mean DBH growth through control of precipitation. In conclusion, the best model introduced environmental factors as a combination of the two parameters (R2 and R_MSE) to explain the influence of environmental factors on average DBH of the growth model.