基于湖南省150块杉木人工林样地数据,采用方差分析、回归分析、非线性混合效应模型、K-means聚类等方法,构建了含立地因子的杉木人工林断面积生长混合效应模型。结果显示:1)海拔(HB)、坡度(PD)、坡位(PW)、土壤厚度(TH)、土壤类型(TL)对林分断面积的生长具有显著影响,其显著性顺序为TL>TH>PD>PW>HB;2)在8种常用的理论生长方程中,Schumacher(M5)的确定系数最高(R²=0.7636),被选为林分断面积生长模拟的基础模型;3)将不同立地因子组合的107个立地类型(ST)作为随机效应,构建了非线性混合效应模型,其确定系数(R²)提高至0.895 1;4)将107个立地类型(ST)聚类为5个立地类型组(STG),进一步构建了杉木断面积生长混合效应模型,其确定系数(R²)提高至0.920 2。研究表明:基于立地因子的非线性混合效应模型,客观解释了立地因子对杉木人工林断面积生长的影响,提高了林分断面积生长模型的模拟精度。

Based on data of 150 Cunninghamia lanceolata Plantation plots in Central China's Hunan Province,this study attempt to construct a mixed effect model of Cunninghamia lanceolata Plantation growth with site factors through using methods such as variance analysis,regression analysis,nonlinear mixed effects model and K-means clustering.The results show that:(1)Altitude (HB),slope (PD),slope position (PW),soil thickness (TH) and soil type (TL)have a significant impact on the growth of the basal area,and the order of significance is TL>TH>PD> PW>HB.(2)Among the eight commonly used theoretical growth equations,Schumacher (M5)has the highest coefficient of determination (R²=0.7636),and was selected as the basic model for forest basal area growth simulation.(3)A nonlinear mixed effects model was constructed by taking 107 site types (ST)of different site factor combinations as random effects and the coefficient of determination (R²)increased to 0.895 1.(4)The 107 site types (ST)were clustered into 5 site type groups (STG),and the mixed effect model of Cunninghamia lanceolata cross-sectional basal area growth was further constructed,and the determination coefficient (R²)increased to 0.920 2.Studies have shown that the nonlinear mixed effect model based on site factors objectively explains the impact of site factors on the growth of Cunninghamia lanceolata Plantation,which helps improve the simulation accuracy of the stand growth model.