Different plant bioclimatic models combined with various plant physiological types must be calculated using different methods. For example, when thermal time models are used to predict plant flowering on the sequential model, the plant chilling requirements must be calculated and satisfied before the growth-accumulated temperature of plants is calculated. If parallel models are used, chilling accumulated temperature and forcing accumulated temperature must also be calculated to predict bioclimatic events. Hence, dozens of model combinations for predicting plant flowering or sprouting by using the thermal time model are available. The high degree of plant bioclimatic and physiological diversity contributes to the complex development of bioclimatic models. The complexity of bioclimatic model development, to a certain degree, effectively increases the accuracy of bioclimatic prediction; however, such complexity also impedes the promotion and application of the models. To simplify the application of bioclimatic models, Chuine (2000) combined numerous major mechanistic models and developed a set of unified bioclimatic model calculation methods, which comprises two formulas to calculate the forcing and chilling requirements of plants. Through the adjustment of various parameters in the model, Chuine fitted the plant differences resulting from physiological responses, phenological phases, regions, and latitudes. Subsequently, Chuine and Beaubien (2001) further argued that the distribution of woody plants is primarily determined by the degree of fitness of the plant bioclimatology to the local climates. Thus, they integrated other models, such as those of freeze injury and fruit ripening, to develop a bioclimatic model based on biological processes, which they referred to as the PHENOFIT model. The model uses bioclimatic observation data for parameter fitting of bioclimatic models and meteorological variable map layers provided by Environment Canada, Climate Archives, the National Climatic Data Center, and the World Radiation Center to determine species distribution according to the fitting degree of the species bioclimatology to the local climates. Because the PHENOFIT model combines multiple bioclimatic models, the calculation formula is complex. Nevertheless, the PHENOFIT model requires the input of only five variables to obtain 12 variables that explain the effects of climates on species. These resulting variables altogether can determine the distribution appropriateness of species. The PHENOFIT model uses climatic data from various geographic regions to infer the distribution of numerous temperate perennial woody plants. The results indicated that the outcomes inferred using the model highly corresponded to the actual distribution of the target species.