Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration

Walker, Anthony P.; Hanson, Paul J.; De Kauwe, Martin G.; Medlyn, Belinda E.; Zaehle, Sönke; Asao, Shinichi; Dietze, Michael; Hickler, Thomas; Huntingford, Chris ORCID: https://orcid.org/0000-0002-5941-7770; Iversen, Colleen M.; Jain, Atul; Lomas, Mark; Luo, Yiqi; McCarthy, Heather; Parton, William J.; Prentice, I. Colin; Thornton, Peter E.; Wang, Shusen; Wang, Ying-Ping; Warlind, David; Weng, Ensheng; Warren, Jeffrey M.; Woodward, F. Ian; Oren, Ram; Norby, Richard J.. 2014 Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration. Journal of Geophysical Research: Biogeosciences, 119 (5). 937-964. https://doi.org/10.1002/2013JG002553

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Abstract/Summary

Free-air CO2 enrichment (FACE) experiments provide a remarkable wealth of data which can be used to evaluate and improve terrestrial ecosystem models (TEMs). In the FACE model-data synthesis project, 11 TEMs were applied to two decadelong FACE experiments in temperate forests of the southeastern U.S.—the evergreen Duke Forest and the deciduous Oak Ridge Forest. In this baseline paper, we demonstrate our approach to model-data synthesis by evaluating the models' ability to reproduce observed net primary productivity (NPP), transpiration, and leaf area index (LAI) in ambient CO2 treatments. Model outputs were compared against observations using a range of goodness-of-fit statistics. Many models simulated annual NPP and transpiration within observed uncertainty. We demonstrate, however, that high goodness-of-fit values do not necessarily indicate a successful model, because simulation accuracy may be achieved through compensating biases in component variables. For example, transpiration accuracy was sometimes achieved with compensating biases in leaf area index and transpiration per unit leaf area. Our approach to model-data synthesis therefore goes beyond goodness-of-fit to investigate the success of alternative representations of component processes. Here we demonstrate this approach by comparing competing model hypotheses determining peak LAI. Of three alternative hypotheses—(1) optimization to maximize carbon export, (2) increasing specific leaf area with canopy depth, and (3) the pipe model—the pipe model produced peak LAI closest to the observations. This example illustrates how data sets from intensive field experiments such as FACE can be used to reduce model uncertainty despite compensating biases by evaluating individual model assumptions.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1002/2013JG002553
Programmes:	CEH Topics & Objectives 2009 - 2012 > Biogeochemistry > BGC Topic 1 - Monitoring and Interpretation of Biogeochemical and Climate Changes > BGC - 1.3 - Quantify & attribute changes in biogeochemiical cycles ... CEH Topics & Objectives 2009 - 2012 > Biogeochemistry > BGC Topic 1 - Monitoring and Interpretation of Biogeochemical and Climate Changes
UKCEH and CEH Sections/Science Areas:	Reynard
ISSN:	0148-0227
Additional Keywords:	model structural analysis, model benchmarking, net primary production (NPP), leaf area index (LAI), sap flow/transpiration, FACE experiment
NORA Subject Terms:	Meteorology and Climatology Atmospheric Sciences Biology and Microbiology
Date made live:	08 Mar 2016 12:09 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/513150

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