From static biogeographical model to dynamic global vegetation model: a global perspective on modelling vegetation dynamics

Predicting the potential effects of future climatic change and human disturbances on natural vegetation distribution requires large-scale biogeographical models. There have been two basic approaches to modelling vegetation response to changing climates: static (time-independent) or dynamic (time-dependent) biogeographical models. This paper reviews and compares two major types of static biogeographical models, climate–vegetation classification and plant functional type models, and the first generation of Dynamic Global Vegetation Models (DGVMs). These models have been widely used to simulate the potential response of vegetation to past and future climate change. Advantage and disadvantage of each type of model are discussed. Global vegetation modelling for investigations of climate change effects has progressed from empirical modelling to process-based equilibrium modelling to the first generation of DGVMs. Some DGVMs are able to capture the responses of potential natural vegetation to climate change with a strong orientation towards population processes. Nevertheless, the uncertainty around the quantitative simulated results indicates that DGVMs are still in the early stages of development. Validating and capturing disturbance-related effects are major challenges facing the developers of the next generation of DGVMs. In future, DGVMs will become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability.