Research On Picea Glauca (White Spruce) Growth Model Of Improved Population

White Spruce (Picea glauca) is widely distributed in frigid temperate zones of North America. It is a major timber tree in Canada. White Spruce is widely distributed with characteristics of abundant genetic variation.This study conducted in the four realized genetic gain experiment forests of white spruce, located in the New Brunswick, Canada. The experiment materials are from three groups of different levels genetic improved and two unimproved (i.e., nature) groups, which are from three experiments orchard, Clonal Seed Orchards (CSO), Clonal Seed Orchards with supplementary mass pollination (CSOSMP) and Ottawa Valley provenance seedling seed orchard (OVSSO).Linear and linear mixed model were used to analysis difference of the growth yields and preservation rate among different groups. It was also applied to estimate parameters of Weibull distribution and then analyze distribution of growth traits for different populations. Nonlinear mixed model was applied to build the growth models for different groups of white spruces and then analysis difference between groups. The generalized linear mixed model was used to analyze the count data such as resistance to diseases, insect, foliage chlorosis and death.The results showed that improved population had significant difference from unimproved ones. The means of height, Diameter at Breast Height (DBH) and Volume of improved were larger than that of unimproved ones. The genetic gains of individual’s volume for CSO, CSOSMP, and OVSSO were20.70%,9.05%and6.77%, respectively. The genetic gains of group’s volume for CSO, CSOSMP, and OVSSO were respective29.88%,17.55%and6.30%. In addition, the adaptability for genetic gains of improved groups was more pronounced in the better environment than worse one.This study indicated that the distribution of improved groups was significantly different from the unimproved group. The improved groups trended to be more consistent than unimproved group. which was beneficial to improve the utilization of timber.The study found that difference in resistance to pest and diseases of improved group was not pronounced to unimproved group, indicating that growth increment did not attenuate the resistance ability. The insect infestation burst about10years ago. Therefore, we should reinforce the field management to cope it.In this study, the R software with associated packages was used as the tool to analyze the data frame. The nonlinear mixed model growth yield model was developed for the white spruce in New Brunswick. The model was tested to be well-fitted.Compared the distinctions between the different groups for the models, the improved and unimproved groups models were significantly different. The STAMAN model was only suitable for growth yield prediction for unimproved group, while it turned out inappropriate for improved forest in terms of yield prediction. The established models can be applied for growth model prediction and management to genetic improved forest groups in CSO, CSOSMP and OVSSO.