Using Ecosystem Experiments to Improve Vegetation Models
Abstract
Ecosystem responses to rising 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 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. Identifying and evaluating the main assumptions caused differences among models, and the assumption-centered approach produced a clear roadmap for reducing model uncertainty. 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.
- Authors:
-
- Macquarie Univ., NSW (Australia). Dept. of Biological Sciences; Univ. of Western Sydney, NSW (Australia). Hawkesbury Inst. for the Environment
- Max Planck Society, Jena (Germany). Max Planck Inst. for Biogeohemistry
- Macquarie Univ., NSW (Australia). Dept. of Biological Sciences
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Div. and Climate Change Science Inst.
- Boston Univ., MA (United States). Dept. of Earth and Environment
- Biodiversity and Climate Research Centre and Senchenbert Gessellschaft fuer Naturforschung, Frankfurt (Germany); Goethe Univ., Frankfurt (Germany). Dept. of Physical Geography
- Univ. of Illinois, Urbana, IL (United States)
- Univ. of Oklahoma, Norman, OK (United States). Dept. of Microbiology and Plant Biology
- Colorado State Univ., Fort Collins, CO (United States). Natural Resource Ecology Lab.
- Natural Resources Canada, Ottawa, ON (Canada). Canada Centre for Remote Sensing (CCRS)
- Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale VIC (Australia). Ocean and Atmosphere Flagship
- Princeton Univ., NJ (United States). Dept. of Ecology and Evolutionary Biology
- Duke Univ., Durham, NC (United States). Div. of Environmental Science and Policy, Nicholas School of the Environment; Swedish Univ. of Agricultural Sciences (SLU), Umea (Sweden)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge National Environmental Research Park
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1209205
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Nature Climate Change
- Additional Journal Information:
- Journal Volume: 5; Journal Issue: 6; Journal ID: ISSN 1758-678X
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Medlyn, Belinda, Zaehle, S, DeKauwe, Martin G., Walker, Anthony P., Dietze, Michael, Hanson, Paul J., Hickler, Thomas, Jain, Atul, Luo, Yiqi, Parton, William, Prentice, I. Collin, Thornton, Peter E., Wang, Shusen, Wang, Yingping, Weng, Ensheng, Iversen, Colleen M., McCarthy, Heather R., Warren, Jeffrey, Oren, Ram, and Norby, Richard J. Using Ecosystem Experiments to Improve Vegetation Models. United States: N. p., 2015.
Web. doi:10.1038/nclimate2621.
Medlyn, Belinda, Zaehle, S, DeKauwe, Martin G., Walker, Anthony P., Dietze, Michael, Hanson, Paul J., Hickler, Thomas, Jain, Atul, Luo, Yiqi, Parton, William, Prentice, I. Collin, Thornton, Peter E., Wang, Shusen, Wang, Yingping, Weng, Ensheng, Iversen, Colleen M., McCarthy, Heather R., Warren, Jeffrey, Oren, Ram, & Norby, Richard J. Using Ecosystem Experiments to Improve Vegetation Models. United States. https://doi.org/10.1038/nclimate2621
Medlyn, Belinda, Zaehle, S, DeKauwe, Martin G., Walker, Anthony P., Dietze, Michael, Hanson, Paul J., Hickler, Thomas, Jain, Atul, Luo, Yiqi, Parton, William, Prentice, I. Collin, Thornton, Peter E., Wang, Shusen, Wang, Yingping, Weng, Ensheng, Iversen, Colleen M., McCarthy, Heather R., Warren, Jeffrey, Oren, Ram, and Norby, Richard J. Thu .
"Using Ecosystem Experiments to Improve Vegetation Models". United States. https://doi.org/10.1038/nclimate2621. https://www.osti.gov/servlets/purl/1209205.
@article{osti_1209205,
title = {Using Ecosystem Experiments to Improve Vegetation Models},
author = {Medlyn, Belinda and Zaehle, S and DeKauwe, Martin G. and Walker, Anthony P. and Dietze, Michael and Hanson, Paul J. and Hickler, Thomas and Jain, Atul and Luo, Yiqi and Parton, William and Prentice, I. Collin and Thornton, Peter E. and Wang, Shusen and Wang, Yingping and Weng, Ensheng and Iversen, Colleen M. and McCarthy, Heather R. and Warren, Jeffrey and Oren, Ram and Norby, Richard J},
abstractNote = {Ecosystem responses to rising 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 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. Identifying and evaluating the main assumptions caused differences among models, and the assumption-centered approach produced a clear roadmap for reducing model uncertainty. 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.},
doi = {10.1038/nclimate2621},
journal = {Nature Climate Change},
number = 6,
volume = 5,
place = {United States},
year = {Thu May 21 00:00:00 EDT 2015},
month = {Thu May 21 00:00:00 EDT 2015}
}
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- Schaphoff, Sibyll; Forkel, Matthias; Müller, Christoph
- Geoscientific Model Development, Vol. 11, Issue 4
The multi-assumption architecture and testbed (MAAT v1.0): R code for generating ensembles with dynamic model structure and analysis of epistemic uncertainty from multiple sources
journal, January 2018
- Walker, Anthony P.; Ye, Ming; Lu, Dan
- Geoscientific Model Development, Vol. 11, Issue 8
The quasi-equilibrium framework revisited: analyzing long-term CO2 enrichment responses in plant–soil models
journal, January 2019
- Jiang, Mingkai; Zaehle, Sönke; De Kauwe, Martin G.
- Geoscientific Model Development, Vol. 12, Issue 5
Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables
text, January 2019
- Paula, Mateus Dantas De; Giménez, Marta Gómez; Niamir, Aidin
- Taylor & Francis
Bayesian Methods for Quantifying and Reducing Uncertainty and Error in Forest Models
journal, September 2017
- van Oijen, Marcel
- Current Forestry Reports, Vol. 3, Issue 4
Recent increases in terrestrial carbon uptake at little cost to the water cycle
journal, July 2017
- Cheng, Lei; Zhang, Lu; Wang, Ying-Ping
- Nature Communications, Vol. 8, Issue 1
Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity
journal, August 2016
- Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.
- Proceedings of the National Academy of Sciences, Vol. 113, Issue 36
Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables
journal, March 2019
- Dantas de Paula, Mateus; Gómez Giménez, Marta; Niamir, Aidin
- International Journal of Digital Earth
Reducing uncertainty in projections of terrestrial carbon uptake
journal, April 2017
- Lovenduski, Nicole S.; Bonan, Gordon B.
- Environmental Research Letters, Vol. 12, Issue 4
Using models to guide field experiments: a priori predictions for the CO 2 response of a nutrient- and water-limited native Eucalypt woodland
journal, May 2016
- Medlyn, Belinda E.; De Kauwe, Martin G.; Zaehle, Sönke
- Global Change Biology, Vol. 22, Issue 8
Advancing global change biology through experimental manipulations: Where have we been and where might we go?
journal, November 2019
- Hanson, Paul J.; Walker, Anthony P.
- Global Change Biology, Vol. 26, Issue 1
Globally consistent influences of seasonal precipitation limit grassland biomass response to elevated CO2
text, January 2019
- Hovenden, Mark J.; Leuzinger, Sebastian; Newton, Paul C. D.
- Nature Publishing Group
Reliable, robust and realistic: the three R's of next-generation land-surface modelling
journal, January 2015
- Prentice, I. C.; Liang, X.; Medlyn, B. E.
- Atmospheric Chemistry and Physics, Vol. 15, Issue 10
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
posted_content, February 2015
- Vermeulen, M. H.; Krujit, B. J.; Hickler, T.
- Earth System Dynamics
Effect of changing vegetation and precipitation on denudation – Part 1: Predicted vegetation composition and cover over the last 21 thousand years along the Coastal Cordillera of Chile
journal, January 2018
- Werner, Christian; Schmid, Manuel; Ehlers, Todd A.
- Earth Surface Dynamics, Vol. 6, Issue 4
A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996)
journal, January 2019
- Thum, Tea; Caldararu, Silvia; Engel, Jan
- Geoscientific Model Development, Vol. 12, Issue 11
The effect of climate type on timescales of drought propagation in an ensemble of global hydrological models
journal, January 2018
- Gevaert, Anouk I.; Veldkamp, Ted I. E.; Ward, Philip J.
- Hydrology and Earth System Sciences, Vol. 22, Issue 9
A Large Committed Long-Term Sink of Carbon due to Vegetation Dynamics
text, January 2018
- Pugh, Thomas; Jones, C. D.; Huntingford, C.
- Karlsruhe
A Combined Tree Ring and Vegetation Model Assessment of European Forest Growth Sensitivity to Interannual Climate Variability
text, January 2018
- Klesse, S.; Babst, F.; Lienert, S.
- American Geophysical Union
Ozone effects on European forest growth-Towards an integrative approach
journal, February 2018
- Cailleret, Maxime; Ferretti, Marco; Gessler, Arthur
- Journal of Ecology, Vol. 106, Issue 4
Global change pressures on soils from land use and management
journal, December 2015
- Smith, Pete; House, Joanna I.; Bustamante, Mercedes
- Global Change Biology, Vol. 22, Issue 3
Model-data synthesis for the next generation of forest free-air CO 2 enrichment (FACE) experiments
journal, August 2015
- Norby, Richard J.; De Kauwe, Martin G.; Domingues, Tomas F.
- New Phytologist, Vol. 209, Issue 1
A Combined Tree Ring and Vegetation Model Assessment of European Forest Growth Sensitivity to Interannual Climate Variability
text, January 2018
- Klesse, Stefan; Babst, Flurin; Lienert, Sebastian
- ETH Zurich
Climate–vegetation modelling and fossil plant data suggest low atmospheric CO2 in the late Miocene
posted_content, June 2015
- Forrest, M.; Eronen, J. T.; Utescher, T.
- Climate of the Past
ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation
journal, January 2018
- Guimberteau, Matthieu; Zhu, Dan; Maignan, Fabienne
- Geoscientific Model Development, Vol. 11, Issue 1
The handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx)
text, January 2020
- Halbritter, Aud H.; De Boeck, Hans J.; Eycott, Amy E.
- Wiley-Blackwell Publishing, Inc.
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
journal, January 2015
- Vermeulen, M. H.; Kruijt, B. J.; Hickler, T.
- Earth System Dynamics, Vol. 6, Issue 2
The handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx)
journal, October 2019
- Halbritter, Aud H.; De Boeck, Hans J.; Eycott, Amy E.
- Methods in Ecology and Evolution, Vol. 11, Issue 1
A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change
text, January 2019
- Song, Jian; Wan, Shiqiang; Piao, Shilong
- Springer Nature
Thinning Can Reduce Losses in Carbon Use Efficiency and Carbon Stocks in Managed Forests Under Warmer Climate
text, January 2018
- Collalti, Alessio; Trotta, Carlo; Keenan, Trevor F.
- Karlsruhe
Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation
journal, January 2018
- Fer, Istem; Kelly, Ryan; Moorcroft, Paul R.
- Biogeosciences, Vol. 15, Issue 19
Decadal fates and impacts of nitrogen additions on temperate forest carbon storage: a data–model comparison
journal, January 2019
- Cheng, Susan J.; Hess, Peter G.; Wieder, William R.
- Biogeosciences, Vol. 16, Issue 13
Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables
text, January 2019
- Paula, Mateus Dantas De; Giménez, Marta Gómez; Niamir, Aidin
- Taylor & Francis
Carbon and Water Use Efficiencies: A Comparative Analysis of Ten Terrestrial Ecosystem Models under Changing Climate
journal, October 2019
- El Masri, Bassil; Schwalm, Christopher; Huntzinger, Deborah N.
- Scientific Reports, Vol. 9, Issue 1
Advancing global change biology through experimental manipulations: Where have we been and where might we go?
journal, November 2019
- Hanson, Paul J.; Walker, Anthony P.
- Global Change Biology, Vol. 26, Issue 1
Developments and applications of terrestrial biosphere model
journal, January 2020
- Peng, Shu-Shi; Yue, Chao; Chang, Jin-Feng
- Chinese Journal of Plant Ecology, Vol. 44, Issue 4
Transient dynamics of terrestrial carbon storage: mathematical foundation and its applications
journal, January 2017
- Luo, Yiqi; Shi, Zheng; Lu, Xingjie
- Biogeosciences, Vol. 14, Issue 1
Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests
journal, January 2017
- Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie
- Biogeosciences, Vol. 14, Issue 20
Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling
journal, January 2020
- Pan, Shufen; Pan, Naiqing; Tian, Hanqin
- Hydrology and Earth System Sciences, Vol. 24, Issue 3