Articles | Volume 9, issue 7
https://doi.org/10.5194/gmd-9-2415-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-2415-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
22 Jul 2016
Development and technical paper |
| 22 Jul 2016
Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information
College of Engineering, Mathematics, and Physical Sciences, University
of Exeter, Exeter, UK
Peter M. Cox
College of Engineering, Mathematics, and Physical Sciences, University
of Exeter, Exeter, UK
Pierre Friedlingstein
College of Engineering, Mathematics, and Physical Sciences, University
of Exeter, Exeter, UK
Andy J. Wiltshire
Met Office Hadley Centre, Exeter, UK
Chris D. Jones
Met Office Hadley Centre, Exeter, UK
Stephen Sitch
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
Lina M. Mercado
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
Centre for Ecology and Hydrology, Wallingford, UK
Margriet Groenendijk
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
Eddy Robertson
Met Office Hadley Centre, Exeter, UK
Jens Kattge
Max Planck Institute for Biogeochemistry, Jena, Germany
Gerhard Bönisch
Max Planck Institute for Biogeochemistry, Jena, Germany
Owen K. Atkin
ARC Centre of Excellence in Plant Energy Biology, Research School of
Biology, Australian National University, Canberra, Australia
Michael Bahn
Institute of Ecology, University of Innsbruck, Austria
Johannes Cornelissen
Systems Ecology, Department of Ecological Science, Vrije Universiteit,
Amsterdam, the Netherlands
Ülo Niinemets
Institute of Agricultural and Environmental Sciences, Estonian
University of Life Sciences, Tartu, Estonia
Estonian Academy of Sciences, Tallinn, Estonia
Vladimir Onipchenko
Department of Geobotany, Moscow State University, Moscow 119234,
Russia
Josep Peñuelas
CSIC, Global Ecology Unit CREAF-CSIC-UAB, Cerdanyola del Vallès,
08193 Barcelona, Catalonia, Spain
CREAF, Cerdanyola del Vallès, 08193 Barcelona, Catalonia, Spain
Lourens Poorter
Forest Ecology and Forest Management Group, Wageningen University,
P.O. Box 6700 AA, Wageningen, the Netherlands
Peter B. Reich
Department of Forest Resources, University of Minnesota, Saint Paul, Minnesota, USA
Hawkesbury Institute for the Environment, University of Western
Sydney, Penrith, New South Wales, Australia
Nadjeda A. Soudzilovskaia
Institute of Environmental Sciences, Leiden University, Leiden, the
Netherlands
Peter van Bodegom
Institute of Environmental Sciences, Leiden University, Leiden, the
Netherlands
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Latest update: 07 Nov 2025
Short summary
Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to...
