Simulation Of Growth Dynamics Of Main Forest Types In Northeast Natural Forest

As one of the most important ecosystems on earth,forest is of important ecological and economic value,and contribute greatly to the global carbon balance.Therefore,it is of great significance to understand the forest growth process.In this study,the natural forests in northeast China were used as the research object.A network of 457 survey plots was established on 8 mountains in the natural forests of Inner Mongolia,Heilongjiang,Jilin and Liaoning provinces,with a total area of 45.7 ha.Based on field surveys and sampling data of 36,145 target trees,(1)the growth drivers for individual tree of the 18 main species in northeast China were analyzed;(2)developed stand productivity models for five main forest types in Northeast China and evaluate the predictive strengths of these models;(3)studied the path and size of the effects of species diversity and structure diversity on forest growth under large-scale conditions,and analyzed the driving mechanisms of environmental factors such as temperature,precipitation and site quality on forest growth.The main findings and conclusions are as follows:1.In the study of individual-tree growth model,the tree size,competition factors and abiotic factors have significant impacts on the volume increment of all tree species.The effects of growth season temperature and growth season precipitation,dominant height on the growth of individual-tree are interactive.Except for the consistent effect of the breast height diameter and the basal area of the larger trees on all tree species,the influence of other factors on the individual-tree growth is of tree species heterogeneity.The growth season temperature,precipitation,and dominant height reflecting site conditions are included in the optimal model of most tree species,and these three abiotic factors interactively affect individual tree volume growth,and affect each other's intensity.This study emphasizes the importance of considering multiple driving factors and their interactions when predicting individualtree volume increment,reflecting the changing trend of volume growth of different tree species under global warming conditions,which is of great significance for the targeted management of different tree species in Northeast China.2.In the study of the stand productivity estimation model,based on the data under large-scale conditions,a base model and three extended models were developed.All three of the extended models increased the accuracy of the predictions at varying degrees for various natural forest types of northeastern China.The inclusion of dominant height and two climate factors in the base model resulted in the best performance for almost every equation of all the forest types.On average,the root mean square values(RMSE)were reduced by 13.0% when compared with the base model,and the independent sample test and sensitivity analysis results of the optimal model also show its good prediction superiority.The inclusion of climatic factors into the traditional model improves the prediction ability of the model and can be used to estimate the growth dynamics of forest resources of different forest types under specific climate conditions.3.In the study of the relationship between stand structure and forest productivity,both species diversity and structure diversity showed positive correlations with forest productivity,and these two factors were strongly correlated.Temperature and precipitation have no direct impact on productivity,but instead influence productivity by adjusting structure diversity and species diversity.Site quality put impacts on productivity also by adjusting forest structure and showed stronger influence than temperature and precipitation.This indicates that structure diversity and species diversity are direct driving factors for forest productivity in natural forests in Northeast China,while climatic factors and dominant height of stand affect forest productivity by influencing forest structure.