Abstract:

The paper selected twenty mixed stands of Larix olgensis, Abies nephrolepis and Picea jezoensis plots as studys example establishing in Forestry Center of Jingouling in Wangqing Forest Bureau of Jilin Province. At first, four nonlinear basal area equations were evaluated using ordinary regression analysis to develop a local model with better precision. The nonlinear mixed model was constructed based on the local model and simulated data. Taking into account different plot effect, the convergence mixed model, in which the values of -2log Likelihood, AIC and BIC are the smallest, was considered as the best model in fitting process with SAS software. Then, within-plot time series error autocorrelation of basal area data and cutting intensity which were expressed with dummy variable were taken into account in mixed model. Finally, the precision of mixed models was compared with the precision of conventional nonlinear ordinary regression analysis method based on validation data. The study showed that the precision of Schumacher form model was higher than that of the other three models due to the consideration of stand density index. The fitted effects of mixed model approach were better than that of ordinary regression analysis. First-order autoregressive error model in explaining time series error autocorrelation of basal area not only improved simulated precision, but also described error distribution of sequence observation data. The precision of mixed model considering plot random effects, time series error autocorrelation and cutting intensity is better than that of ordinary regression analysis method.

Key words: mixed model, basal area, Larix olgensis, cutting, time series error autocorrelation