| Based on the measurement of 955 branch samples of 65 Korean pine (Pinus koraiensis) trees in 12 plots from Mengjiagang forest farm, Heilongjiang Province. The research analyzed the quantity distribution regularities for first-order branch and second-order branch for Korean pine plantation. Poisson model and negative binomial model were introduced to develop the second-order branch count model for Korean pine plantation. AIC, Pseudo-R2, RMSE and Vuong test were selected to compare the goodness-of-fit statistics of the models. The results as follows:1. The first-order branch count in a whorl was 3 to 5, with mean value of 4. The quantity distributions of first-order branch had no significant correlation with trees variables and branches variables. The first-order branch count in a whorl for Korean pine plantation associated with its own characteristic. In a horizontal direction, the first-order branch presented a wave mode and conformed to the uniform distribution.2. The second-order branch had less quantity distribution in the upper crown for Korean pine plantation and concentrated distribution in the middle and lower crown. The higher-level of Korean pine plantation, the more capable of branching capability for second-order branch. The research of branching probability was 1:27, which mean every first-order branch have the ability to branching 27 second-order branch.3. The quantity distribution of second-order branch had significant correlation with RDINC, HT/DBH, CL and DBH variables. With the increase of HT/DBH, the quantity distribution of second-order branch decreased. With the increase of CL and DBH, the quantity distribution of second-order branch increased. With the increase of RDINC, the quantity distribution of second-order branch increased and then decreased. The quantity distribution of second-order branch had the maximum value.4. All subset regressions techniques were used to develop the second-order branch count model. The negative binomial regression model E(Y)=exp(β0+β1lnRDINC+β2RDINC2+β3HT/DBH+β4CL+β5DBH) was selected as the optimal second-order branch count model. Pseudo-R2 of the optimal model was 0.79, the mean error was close to 0 and the mean absolute error was less than 7. For the developed model, the parameter values of lnRDINC, CL and DBH were negative, the parameter values of RDINC2 and HT/DBH was positive. With the increase of RDINC, the number of second-order branch had peak value in the tree crown. On the whole, the precision of the second-order branch count model for Korean pine plantation was 96.36%.On the whole, the second-order branch count model constructed by this research would be suitable for predicting the second-order branch count for the study area and provide the theory basis for branch photosynthesis and biomass research. With the accumulation of data, we will further carry out the branch count model in macro region. |
