All applications of bioclimatic models in assessing the effects of climate changes have advantages and disadvantages (Elith et al. 2006; Hijmans and Graham 2006). For example, statistical models are the most widely used and are user-friendly and users are not required to consider biological processes, genetics, and physiology; however, they lack explanatory power for the research results and have a limited scopes of applications. Statistical models generally can not be applied to research on the effects on large areas of vegetation variations. Mechanistic models yield the highest explanatory power for the effects of climate changes, and thus have optimal assessment effectiveness. However, uncertainty of species’ physiological mechanisms is a constraining factor of using such models. For instance, users may be uncertain regarding what model to use to assess the effects of climate changes on the dormancy of Sassafras randaiense Hay. Rehder because the bud dormancy and physiology of the plant species have not yet been thoroughly investigated. Regarding the research on bioclimatic models for exploring the effects of climate changes, the successful application of models is determined by the user’s understanding of each model. Only by selecting suitable models can reliable assessment on the effects of climate changes be conducted and accurate results be attained.