Predictive models of forest dynamics.
Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.
Purves
Drew
D
Computational Ecology and Environmental Science Group, Microsoft Research, Cambridge, UK.
Pacala
Stephen
S
D044822:Biodiversity; D002980:Climate; D017753:Ecosystem; D005544:Forecasting; D008027:Light; D008433:Mathematics; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D014197:Trees / Q000254:growth & development / Q000502:physiology