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Comprehensive ecosystem model‐data synthesis using multiple data sets at two temperate forest free‐air CO 2 enrichment experiments: Model performance at ambient CO 2 concentration
Author(s) -
Walker Anthony P.,
Hanson Paul J.,
De Kauwe Martin G.,
Medlyn Belinda E.,
Zaehle Sönke,
Asao Shinichi,
Dietze Michael,
Hickler Thomas,
Huntingford Chris,
Iversen Colleen M.,
Jain Atul,
Lomas Mark,
Luo Yiqi,
McCarthy Heather,
Parton William J.,
Prentice I. Colin,
Thornton Peter E.,
Wang Shusen,
Wang YingPing,
Warlind David,
Weng Ensheng,
Warren Jeffrey M.,
Woodward F. Ian,
Oren Ram,
Norby Richard J.
Publication year - 2014
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1002/2013jg002553
Subject(s) - evergreen , transpiration , leaf area index , temperate rainforest , environmental science , temperate forest , deciduous , canopy , range (aeronautics) , forest ecology , temperate deciduous forest , temperate climate , goodness of fit , atmospheric sciences , ecosystem , statistics , ecology , mathematics , botany , photosynthesis , biology , geology , materials science , composite material
Free‐air CO 2 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 CO 2 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.