@article{Walker:2014:10.1002/2013JG002553,
author = {Walker, AP and Hanson, PJ and De, Kauwe MG and Medlyn, BE and Zaehle, S and Asao, S and Dietze, M and Hickler, T and Huntingford, C and Iversen, CM and Jain, A and Lomas, M and Luo, Y and McCarthy, H and Parton, WJ and Prentice, IC and Thornton, PE and Wang, S and Wang, Y-P and Warlind, D and Weng, E and Warren, JM and Woodward, FI and Oren, R and Norby, RJ},
doi = {10.1002/2013JG002553},
journal = {Journal of Geophysical Research: Biogeosciences},
pages = {937--964},
title = {Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration},
url = {http://dx.doi.org/10.1002/2013JG002553},
volume = {119},
year = {2014}
}

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TY  - JOUR
AB  - Freeair 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 modeldata 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 modeldata 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 goodnessoffit statistics. Many models simulated annual NPP and transpiration within observed uncertainty. We demonstrate, however, that high goodnessoffit 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 modeldata synthesis therefore goes beyond goodnessoffit 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.
AU  - Walker,AP
AU  - Hanson,PJ
AU  - De,Kauwe MG
AU  - Medlyn,BE
AU  - Zaehle,S
AU  - Asao,S
AU  - Dietze,M
AU  - Hickler,T
AU  - Huntingford,C
AU  - Iversen,CM
AU  - Jain,A
AU  - Lomas,M
AU  - Luo,Y
AU  - McCarthy,H
AU  - Parton,WJ
AU  - Prentice,IC
AU  - Thornton,PE
AU  - Wang,S
AU  - Wang,Y-P
AU  - Warlind,D
AU  - Weng,E
AU  - Warren,JM
AU  - Woodward,FI
AU  - Oren,R
AU  - Norby,RJ
DO  - 10.1002/2013JG002553
EP  - 964
PY  - 2014///
SN  - 2169-8961
SP  - 937
TI  - Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration
T2  - Journal of Geophysical Research: Biogeosciences
UR  - http://dx.doi.org/10.1002/2013JG002553
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000337607900016&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/69648
VL  - 119
ER  - 

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