Predicting Models Of Diameter Distribution Dynamic For Larch Plantation

Diameter distribution of trees in forest management planning and silvicultural techniques play an important role in guiding, and its dynamic distribution is more conducive to sustainable forest management. In this paper,102 plots of interval of 10 years for Larch pure plantation which are located in Xiaoxing’an Mountains and Changbai Mountains, and match the Weibull distribution are used to establish the relationships with the parameter b1 of the initial data and the forest factors of initial data by parameter prediction method (PPM), and the relationships with two parameters b1 and C1, b2 and b1 and the forest factors of initial data and remeasured data, c2 and b2. The models coefficients were simultaneously estimated using seemly unrelated regression (SUR).The model included the simple model and the complex model The model fitting indicate that:To the simple model:all the parameter prediction models obtain good model fitting and prediction performance, of which the model Ra2 was 0.428-0.897, and RMSE are small (0.37-0.94), dynamic diameter distribution models have a good prediction performance. In addition, we use the The relative biases (%Biasc), the error index (EI), the mean relative error (ME%),the mean absolute relative error (MAE%), the precision (P%) to evaluate the validation statistics of dynamic parameter prediction equations, respectively. The results show that the dynamic diameter distribution models have good precision (-10 %<ME%<-2%, P%>95%), and can predict the diameter distribution of Larch plantation in future (%Bias0=4.38%,%Bias1=12.38%, EI=524).To the complex model:all the parameter prediction models obtain good model fitting and prediction performance, of which the model Ra2 was 0.454-0.889,and RMSE are small (0.32-1.77), dynamic diameter distribution models have a good prediction performance. In addition, the relative biases (%Biasc), the error index (EI), the mean relative error (ME%), the mean absolute relative error (MAE%), the precision (P%) were used to evaluate the validation statistics of dynamic parameter prediction equations, respectively. The results show that the dynamic diameter distribution models have good precision (-6%<ME%<-1%, P%>96%), and can predict the diameter distribution of Larch plantation in future (%Bias0=1.16%,%Bias1=4.96%, EI=525).Overall, the dynamic diameter distribution models(the simple one and the complex one) can provide the scientific monitoring and forest protection of plantation resources, and all can be applied to the actual production of Larch Plantation.