Study On The Growth Model Of The Three Main Tree Species In North China

Poplar, pine and larch are the three main tree species in north China,there is a lack of growth researches on these species(especially the poplar in beijing). This paper took the analytic trees of Chinese white poplar、fast-growing poplar and Chinese pine in Beijing and North China larch in Inner Mongolia as the research data.Using the empirical model and theoretical model,including the two parabola model,log linear model,logistic model,Richards model,Korf model,Gompertz model and Mitscherlich model,the paper fit the relationship between DBH (D) and time(T),tree height(H) and time(T),tree volume(V)and time(T) to get the optimal growth model:(1)The optimal growth models about DBH、tree height、volume of artificial forest of Chinese white poplar are:D = 42.197 · e-3.333·e-0.13·t、H= 32.897 · e-2.359·e-0.142·t、V= 3.425 · e-8.17·e-0.104·t respectively;(2)The optimal growth models about DBH、tree height、volume of artificial forest of fast-growing poplar are:D=41.733 · (1-e-0.119·t)1.804、H=31.893/1+6.434-0.27·t、V= 2.312 · e-7.427·e-0.139·t respectively;(3)The optimal growth model about DBH、tree height、volume of mountain Chinese pine are: D=19.173 · (1-e-0.05·t)1.918、H=-63.274+16.803 · In(t+42.29)、V= 1.55 · e-8.454·e-0.032·t respectively;(4)The optimal growth models about DBH、tree height、volume of natural secondary forest of North China larch are:D=17.736 · e-39.426·t-1.359、H=14.931 · (1 e-0.094.t)2.455、V=0.108. e-12.519·e-0.12·t respectively.By testing the main statistical indexes of the models such as the total relative error, the average system error and prediction error, it is revealed that the fitting accuracy and general prediction of the optimal growth models of all species yield good results.This paper builds BP neural network models whose structure is 3:5:1 on single timber volume growth of Chinese white poplar and fast-growing poplar. The overall fitting accuracy of the sample data is 0.9259 and 0.9342 respectively, indicating that the model has a good predictive ability and can be used in forestry production and research.This article uses numerous mathematical models with a variety of statistical analysis software to simulate the growth of poplar (Chinese white poplar and poplar). pine. and North China larch in the study area. Thus we can have a better understanding of the three main species in North China growth rhythm and predict their future growth dynamics, which provides a theoretical basis for monitoring forest resources and taking reasonable management measures.