Application of Dynamic Vegetation Models for Climate Change Impact Studies

The Earth’s climate and its interactions with vegetation have become a major focus of contemporary climate change research. Hence, climate change is associated with widespread implications for the structure and function of vegetation all over the world. In particular, for terrestrial ecosystems where changes are likely to become increasingly prominent in the coming decade, to advise important societal decisions, understanding ecosystem behavior to changing climate is crucial. For this aim, integrated model-based approaches have been widely adopted. For example, the development of models for simulating the response of vegetation to climate and other associated growth variables have recently highlighted key processes that control the composition and functioning of forest ecosystems. Dynamic vegetation models simulate the spatially explicit response of land surface and terrestrial vegetation processes to climate change across the time slices ranging from seconds to multi-decades. Employing different process configurations and assumptions, different dynamic vegetation models can also be used to probe the inherent uncertainty related to our current scientific understanding of vegetation processes and their model formulation. Uncertainty in understanding impacts using these models is often introduced by the climate forcing, adding elements of scenario, the inherent uncertainty of model, and natural variabilities. For this reason, validation of dynamic vegetation models against ground observations is essential for ensuring confidence in the results of climate change impact studies. In the following, we present a coherent view on how to apply dynamic vegetation models for assessing the climate change impact on forests.