| Eucalyptus (Eucalyptus grandis×Eucalyptus urophylla) is one of important fast-growing and high-yield tree species in south China. In this study, GreenLab model was applied to develop the functional-structural model and the stochastic morphologic model based on morphologic and biomass data of 16 eucalyptus trees. The main contents of the thesis are listed as the following:(1) The allometric model of single leaf of eucalyptus was developed, which provided a simple method for estimating leaf area used in the functional-structural model of eucalyptus. The measured data showed strong linear relationship between leaf area and fresh leaf weight of eucalyptus. Since there were significant differences in fresh weight between young and mature leaves, the models between leaf area and leaf weight were developed for them separately. After model evaluation through average relative error, total relative error, average absolute relative error, root mean square error and predicted precision, models y=53.299x0.891 and y=-0.004+48.632x were selected for mature leaf and young leaf area estimation, respectively, where y is leaf area, x is leaf fresh weight. The predicted precisions were 97.2% for mature leaves and 98.6% for young leaves.(2) The deterministic functional-structural model (GL1) was calibrated of for eucalyptus. Direct parameters were attained from the measurement data. The hidden parameters of the model were calibrated using the generalized nonlinear least squares method through Digiplante software. The study tested part hypothesis of GreenLab model and evaluated the fitting results. The results showed that: the fitting was good for total biomass of each order branch and leaves. The relative errors of total biomass of branches were 1.49%,-13.41% and -18.80% for PA1,PA2,PA3 and 1.25%,8.24%,2.40% for total leaf biomass, respectively, whereas the fitting for diameter and length of internodes were not as good as total biomass. The average relative errors were 19.71% and 48.74%, respectively. The secondary growth mainly followed common pool mode.(3) The stochastic morphologic model was established. The phenomenon of growth delay during the growing process was found through analyzing the morphological characteristics of eucalyptus. The phenomenon could be described by the stochastic models. The stochastic equations of bud growth probability, growth rhythm ratio, branching probability and bud survival probability were developed, and the corresponding morphologic parameters of 1-year-old and 2-year-old eucalyptus were attained. Based on the assumption that growth rhythm equals one, the average growth probability of trunk were 0.82 and 0.78 for 1-year-old and 2-year-old eucalyptus, respectively; the average growth probability of 1st order branch were 0.41 and 0.68; and the branching probabilities on trunk were close to 1.These parameters and stochastic models could be used to simulate the morphologic structure of eucalyptus canopy.The study results provided the method and basis for understanding the structure change, growth process and biological-driven three-dimensional visualization for eucalyptus.
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