The prediction results of bioclimatic modeling or the models themselves can be integrated with other models with various purposes to conduct research on the effects of climate changes (Halofsky et al. 2013). For example, Bonan (1998) used the monthly leaf area indices predicted using the land surface model of the National Center for Atmospheric Research as model parameters and applied the parameters to the grids of the Community Climate Model to facilitate global climate change research. Kaduk and Heimann (1996) determined the precautionary and mechanical structures that identify bioclimatology phases in environmental conditions and applied the structure to land carbon cyclic model research. Botta et al. (2000) used remote sensing data to estimate leaf sprouting time and developed empirical prediction formulas to predict leaf bioclimatology dynamics and propose a global bioclimatology precautionary structure. In addition, other professional bioclimatic models of climate change for large-scale structures based on biospheres or ecological systems exist, such as the Frankfurt biosphere model established based on the carbon equilibrium structure; the Lund-Potsdam-Jena dynamic global vegetation model, which assesses ecological system dynamics, plant geography, and land field carbon cycles (Sitch et al. 2003); the Canadian Centre for Climate Modeling and Analysis integrated biosphere simulator model, which predicts leaf bioclimatology based on light and temperature functions (Foley et al. 1996); and the forest carbon model based on photosynthesis and transpiration (Chiang and Brown 2007). These models have been widely applied in large-scale climate change research in recent years.