Using Ecosystem Experiments to Improve Vegetation Models
Ecosystem responses to rising carbon dioxide (CO2) concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model–Data Synthesis project aimed to use information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new ‘assumption-centred’ model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. By identifying and evaluating the main assumptions causing differences among models, the assumption-centred approach produced a clear roadmap for reducing model uncertainty. In a recent paper, researchers explained this approach and summarized the resulting research agenda. They encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.
Medlyn, B. E., S. Zaehle, M. G. De Kauwe, A. P. Walker, M. C. Dietze, P. J. Hanson, T. Hickler, A. K. Jain, Y. Luo, W. Parton, I. C. Prentice, P. E. Thornton, S. Wang, Y.-P. Wang, E. Weng, C. M. Iversen, H. R. McCarthy, J. M. Warren, R. Oren, and R. J. Norby. 2015. “Using Ecosystem Experiments to Improve Vegetation Models,” Nature Climate Change 5, 528–34. DOI: 10.1038/nclimate2621.