Crown width model of Chinese fir plantation based on mixed effect
Constructing a single tree crown width model for Chinese fir(Cunninghamia lanceolata)artificial forests can improve the prediction accuracy of Chinese fir crown width and provide a reference basis for the scientific management of artificial Chinese fir forests.The basic model was extended,and a nonlinear mixed effect model of crown width was constructed,including stand and individual tree factors and using data from 7 198 individual trees in 57 plots of Chinese fir plantations in Chongyi County,Jiangxi Province.Using a 10-fold cross-validation method,adjusted coefficient of determination(R2adj),root mean square error(ERMS),and mean absolute error(EMA)were used as model evaluation indicators to evaluate the predictive performance of each model.The results indicate that:(1)The logistic model had the best fitting and prediction performance among the candidate models.(2)In addition to the diameter at breast height,there were 6 indicators that had significant effects on crown width(P<0.05).And,the six indexes were site index,stand age,Gini coefficient,stand density index,height to crown base and basal area of trees larger than the subject tree.The generalized model constructed with covariates added was more effective than the basic model;R2adj increased by 28.53％,whereas ERMS and EMA decreased by 17.80％and 15.72％,respectively.(3)The mixed effects model that considered the random effects at the sampling site level was better than the generalized model;R2adj increased by 27.86％,whereas ERMS and EMA decreased by 35.73％and 51.87％,respectively.The addition of covariates and random effects could effectively improve the prediction accuracy of crown width models,and the Gini coefficient,which reflects the diversity of tree size,performed well in crown width simulations.It is worth exploring the application of this type of indicator in other types of artificial forest simulations.
Chinese fircrown width modelnonlinear mixed effect modelGini coefficientdiversity of tree size
万方数据
维普
