Publication Date:
2013-02-08
Description:
Predicted responses of transpiration to elevated atmospheric CO 2 concentration (eCO 2 ) are highly variable among process-based models. To better understand and constrain this variability among models, we conducted an intercomparison of 11 ecosystem models applied to data from two forest free-air CO 2 enrichment (FACE) experiments at Duke University and Oak Ridge National Laboratory. We analysed model structures in order to identify the key underlying assumptions causing differences in model predictions of transpiration and canopy water-use efficiency. We then compared the models against data to identify model assumptions that are incorrect or are large sources of uncertainty. We found that model-to-model and model-to-observations differences resulted from four key sets of assumptions, namely: (i) the nature of the stomatal response to elevated CO 2 (coupling between photosynthesis and stomata was supported by the data); (ii) the roles of the leaf and atmospheric boundary layer (models which assumed multiple conductance terms in series predicted more decoupled fluxes than observed at the broadleaf site); (iii) the treatment of canopy interception (large inter-model variability, 2-15 %); and (iv) the impact of soil moisture stress (process uncertainty in how models limit carbon and water fluxes during moisture stress). Overall, model predictions of the CO 2 effect on WUE were reasonable (inter-model μ = ~28 ± 10 %) compared to the observations (μ = ~30 ± 13 %) at the well-coupled coniferous site (Duke), but poor (inter-model μ = ~24 ± 6 %; observations μ = ~38 ± 7 %) at the broadleaf site (Oak Ridge). The study yields a framework for analysing and interpreting model predictions of transpiration responses to eCO 2 , and highlights key improvements to these types of models. © 2013 Blackwell Publishing Ltd
Print ISSN:
1354-1013
Electronic ISSN:
1365-2486
Topics:
Biology
,
Energy, Environment Protection, Nuclear Power Engineering
,
Geography
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