Study On Pinus Tabulaeformis Carr. Artificial Forest Individual Tree Growth Model And Biomass Model In Daqing Mountains Of Inner Mongolia

This paper study on single tree growth models and the biomass model of the Pinus tabulaeformis Carr artificial forest in Inner Mongolia Daqing mountain with the survey data in Pinus tabulaeformis Carr plantation of Daqing mountain in Inner Mongolia. The results are as follows:1. According to the condition of pinus tabulaeformis Carr tree height, DBH stemflow volume and the corresponding growth and peak in successive years of growth, the biggest is the downhill slope, the smallest is the uphill slope,in between the minimum up between them.2. Fitting different site conditions inPinus tabulaeformis Car plantations of the tree height, diameter at breast height and volume of the growth process with the Logistic model y = k / (1 + e^a-rt) ,different site conditions in different parameter values, model fitting precision were more than 0.90.3. Basted on the Logistic model with three derivatives d³y/dt³=kr3e^a-rt(e²lna-2rt-4e^a-rt+1)(1+e^a-r)^-4 ,Different site conditions under the tree height, DBH of Pinus tabulaeformis Car plantation and volume of each stage, the results showed that the effects to downhill before entering the shortest, slow periods of time after the late period of slower, fast-growing longest period, Before going into the longest period of slower and slower period of time after the shortest duration, fast-growing periods, In between the slope between them. In general, Inner Mongolia daqing mountain plantations growing period of quick-grow pinus tabulaeformis trees for 7 19high time for 19 age, DBH 8-24 ages, volume for 14 30 ages.4. The total biomass pinus tabulaeformis Carr plantation, trunk, branches, leaves, crown, lumber, bark, each component and tree height and diameter of biomass, volume, long, crown, volume of linear correlation between closely, As the variable volume will introduce standing tree biomass of estimating model, which can solve the problem of compatible problem between them. Using the method of the nonlinear joint estimation can solve the incompatible problem between the total biomass model and the incompatibility of various models, which obtain the biomass model.