Construction of mixed effect model of height-diameter at breast height of Cunninghamia lanceolata plantation in Xiangxi Tujia and Miao Autonomous Prefecture
This study aimed to establish a model for height-diameter at breast height relationship of Cunninghamia lanceolata plantaion in Xiangxi Tujia and Miao Autonomous Prefecture,analyzed the influences of both quantitative factor and qualitative factor on the height growth of forest stands,and provided a model and theoretical basis for regional-scale height estimation.The study focused on C.lanceolata plantations in seven counties of Xiangxi Tujia and Miao Autonomous Prefecture.Based on the data collected from 55 sample plots in C.lanceolata plantations,the random forest method was employed to select significant influencing factors as reparameterization variables and random effects.Among six basic height-diameter models,the best-fitting function was chosen as the optimal base model.The optimal reparameterization model,incorporating the variable SD/1000 to represent stand densitywas constructed.On the basis of the optimal reparameterization model,the significant qualitative factors influencing the height of C.lanceolata plantations were analyzed by a mixed effects model,leading to the establishment of the optimal mixed effects model for C.lanceolata plantations in Xiangxi Tujia and Miao Autonomous Prefecture.The results showed that the significant factors influencing the height of C.lanceolata plantations in Xiangxi Tujia and Miao Autonomous Prefecture included diameter at breast height(P＜0.01),age group(P＜0.01)and stand density(P＜0.05).Among the six candidate models,the Näslund model(Model 1)was found to be the optimal candidate with the smallest AIC and BIC values of 154.741 7 and 159.654 4,respectively and R2 =0.572 7.Its parameters a and b were extremely significant and had statistical significance.The optimal reparametrization model(Model1.1)has a determined coefficient of R2 =0.620 2 and a root mean square error of RMSE = 1.615 9.The three mixed effect models which contain qualitative factors were found to be the optimal models and have better goodness-of-fit performance than the previous models.The nlme 1.1 model and nlme 1.3 model had the best performance with an increase of 19.6%and 10.4%in the R2 and a decrease of 14.1%and 8.9%in the RMSE compared to the optimal baseline model,respectively.Considering the simplicity of the model,the nlme 1.1 was chosen as the optimal mixed effects model for C.lanceolate plantations in Xiangxi Tujia and Miao Autonomous Prefecture.Compared with traditional regression models,the tree height-diameter model fitted using reparameterization and nonlinear mixed effects methods has superior predictive performance,it was higher model accuracy,and smaller errors.This study provided theoretical bases for forestry management and practice in Xiangxi Tujia and Miao Autonomous Prefecture.
Cunninghamia lanceolataplantationtree height-diameter modelreparametrizationmixed effect model
NETL
NSTL
万方数据
