Models of the global carbon cycle and terrestrial biosphere have now been coupled to dynamical models of the atmosphere and ocean. The combination, often referred to as an earth system model (ESM), is used to predict future climate change. Together with many colleagues, we have developed one such model of the terrestrial biosphere, which is now part of the GFDL-NOAA- ESMs. I describe the structure of this terrestrial model, its biological rationale and some recent predictions of the full ESM, including the new prediction that failure to stabilize the atmospheric CO2 concentration below a doubling of the pre-industrial level would bring surprisingly severe risks.
Like other such models, this one divides the flora into a few discreet “functional types”. For example, all northern broadleaf tree species are assigned to one functional type with identical parameter values, as are all boreal evergreen conifers. However, temperature sensitivities of arctic birches and Gulf-coast gums are more different from one another than are the means of northern broadleaf and boreal conifer functional types. The implication is that biomes may respond to climate change more by species-replacements within the same functional type than by changes between functional types. Current global models, which allow only biome-boundary-moving changes in the global distribution of biodiversity, may thus be too sensitive to climate change, because they do not allow for within-biome competitive replacements.
and Results/Conclusions
To address this issue, we and many colleagues have developed the underpinnings of a global model with an infinite number of global plant species. It models a “species” as a unique combination of a few building blocks common to all species, such as C3 or C4 photosynthesis, fine roots, leaves, and wood. The model’s universe of possible species includes all possible combinations of these building blocks. We then use a recently developed mathematical technique called the perfect plasticity approximation to compete these plants against one another for light, water and/or nitrogen. We use adaptive dynamics to determine the competitive dominant as a function of climate and soils. Analytical results are possible for most important cases. To illustrate the approach, we use it to explain the global distribution of nitrogen fixing trees and changes in plant communities along nitrogen and rainfall gradients.