Using random intercept effects in DBH increment model of individual trees for fir plantation

In the paper, we developed a mixed model of random intercept effects for individual DBH increment, taking the example of four survey data of fir plantations in Jiangxi Province, eastern China. The model was defined as a linear mixed model with intercept effects of plot, area or plot and area simultaneous. The heteroscedasticity and autocorrelation matrix were added to the model when taking into account multilevel effects. In the end, mixed model calibration of DBH increment was carried out using the independent sampling. The results showed that total stand basal area, DBH of target tree, the ratio of basal area of larger trees to target tree DBH, and altitude were found to be significant effect on DBH increment. Both the simulation results and verified accuracy of the model indicated a substantial improvement compared with the conventional approach widely used in forest management. After adding to a reasonable variance function of heteroscedasticity and autocorrelation, the model showed better goodness of fit than taking into account random intercept effects only. The goodness of multilevel effects was better than that of individual-level effect in forest actual applied process.