Using ecosystem experiments to improve vegetation models

Belinda E. Medlyn*, Sönke Zaehle, Martin G. De Kauwe, Anthony P. Walker, Michael C. Dietze, Paul J. Hanson, Thomas Hickler, Atul K. Jain, Yiqi Luo, William Parton, I. Colin Prentice, Peter E. Thornton, Shusen Wang, Ying Ping Wang, Ensheng Weng, Colleen M. Iversen, Heather R. Mccarthy, Jeffrey M. Warren, Ram Oren, Richard J. Norby

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

175 Citations (Scopus)

Abstract

Ecosystem responses to rising CO 2 concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO 2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model-Data Synthesis project aimed to use the 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. Here, we explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.

Original languageEnglish
Pages (from-to)528-534
Number of pages7
JournalNature Climate Change
Volume5
Issue number6
DOIs
Publication statusPublished - 26 Jun 2015

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