基于气候因子的杉木单木胸径生长模型构建

【目的】为准确预测湖南杉木的生长及制定经营管理措施，构建了考虑气候因子的杉木单木胸径生长混合效应模型。【方法】基于湖南省第七、八次全国森林资源连续清查中73块样地的3 638株杉木数据，运用多元逐步回归的方法，考虑林木大小、竞争、立地和其他林分因子以及气候因子对杉木胸径生长的影响，分别以5年胸径增长量(D₂-D₁)、5年胸径增长量的自然对数ln(D₂-D₁+1)]、5年胸径平方增长量的自然对数ln(D₂²-D₁²+1)]、胸径平方增长量(D₂²-D₁²)为因变量构建模型，选择最优基础模型。在最优模型的基础上，引入样地随机效应，构建单水平线性混合效应模型，并引入3种常用的异方差函数和3种常用的自相关结构来消除模型的异方差和自相关，最后采用十折交叉验证的方法对模型的预估效果进行检验。【结果】与其他3种因变量相比，因变量为ln(...

Study on increment model of individual-tree diameter of Cunninghamia lanceolata in consideration of climatic factors

【Objective】 To accurately predict growth and formulate forest management strategies for Cunninghamia lanceolata in Hunan Province, a mixed-effects individual tree diameter increment model for Cunninghamia lanceolata was developed considering climatic factors. 【Method】 Based on the data of 3 638 observations in 73 plots from the 7^th and 8^th Chinese National Forest Inventory in Hunan Province, this study used the multiple stepwise regression method to introduce tree size, competition, site conditions, other stand variables, and climate factors as independent variables, and developed and evaluated four different dependent variables: i.e. 5-year diameter increment (D₂-D₁), the natural logarithm of 5-year diameter increment ln(D²₂-D²₁+1)], the natural logarithm of 5-year squared diameter increment ln(D²₂-D²₁+1)], and 5-year squared diameter increment (D²₂-D²₁). An optimal basic model was selected. A linear mixed-effects model with sample plots as random effects was then fitted. In addition, three commonly used variance functions and correlation structures were introduced to remove the heteroscedasticity of the residuals and autocorrelation. Finally, the 10-fold cross-validation method was used to assess predictive ability. 【Result】 Compared with the other three dependent variables, the model performed best with ln(D²₂-D²₁+1) as the dependent variable. Therefore, the model in which the dependent variable was ln(D²₂-D²₁+1) was selected as the optimal basic model. According to the results of the optimal basic model, the initial diameter, the ratio of the sum of the basal area of trees with diameters larger than the subject tree’s diameter to the initial diameter, stand basal area per hectare, the product of the sine of the slope and the natural logarithm of the altitude, mean annual precipitation, and mean minimum temperature in January significantly affected the increase in the diamteter of Cunninghamia lanceolata. Compared with the optimal basic model, the mixed-effects model showed a significantly improved prediction accuracy. Additionally, the introduction of variance functions and correlation structures also significantly improved the model’s performance, of which the exponent function (exponent) and ARMA(1,1) performed the best. In the 10-fold cross-validation, the mixed-effects model also showed better performance. 【Conclusion】 Climatic factors have a significant effect on the increase of diameter in Cunninghamia lanceolata. Compared with the basic model, the linear mixed-effects model with sample plots as random effects could greatly improve the model’s performance, and we hope that the model could provide support for the scientific management of Cunninghamia lanceolata in Hunan Province.