26
IRUS Total
Downloads
  Altmetric

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

File Description SizeFormat 
Walker_et_al-2014-Journal_of_Geophysical_Research__Biogeosciences.pdfPublished version3.34 MBAdobe PDFView/Open
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
Authors: Walker, AP
Hanson, PJ
De Kauwe, MG
Medlyn, BE
Zaehle, S
Asao, S
Dietze, M
Hickler, T
Huntingford, C
Iversen, CM
Jain, A
Lomas, M
Luo, Y
McCarthy, H
Parton, WJ
Prentice, IC
Thornton, PE
Wang, S
Wang, Y-P
Warlind, D
Weng, E
Warren, JM
Woodward, FI
Oren, R
Norby, RJ
Item Type: Journal Article
Abstract: 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.
Issue Date: 1-May-2014
Date of Acceptance: 25-Apr-2014
URI: http://hdl.handle.net/10044/1/69648
DOI: https://dx.doi.org/10.1002/2013JG002553
ISSN: 2169-8961
Publisher: American Geophysical Union
Start Page: 937
End Page: 964
Journal / Book Title: Journal of Geophysical Research: Biogeosciences
Volume: 119
Issue: 5
Copyright Statement: © 2014 American Geophysical Union. All Rights Reserved.
Keywords: Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Environmental Sciences
Geosciences, Multidisciplinary
Environmental Sciences & Ecology
Geology
model structural analysis
model benchmarking
net primary production (NPP)
leaf area index (LAI)
sap flow
transpiration
FACE experiment
CARBON-DIOXIDE ENRICHMENT
NET PRIMARY PRODUCTIVITY
GLOBAL VEGETATION MODEL
LONG-TERM RESPONSE
CANOPY LEAF-AREA
LAND-USE CHANGE
ELEVATED CO2
ATMOSPHERIC CO2
DECIDUOUS FOREST
TERRESTRIAL ECOSYSTEMS
Publication Status: Published
Open Access location: https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1002/2013JG002553
Online Publication Date: 2014-05-27
Appears in Collections:Department of Life Sciences
Grantham Institute for Climate Change