The DOI matches its Crossref record; 93 of the 93 references it cites were found in a registry or an index.
Forest water use and water use efficiency at elevated CO2: a model‐data intercomparison at two contrasting temperate forest FACE sites
Abstract
Predicted responses of transpiration to elevated atmospheric CO 2 concentration (eCO 2) are highly variable amongst process‐based models. To better understand and constrain this variability amongst 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 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 intermodel 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 (intermodel μ = approximately 28% ± 10%) compared to the observations (μ = approximately 30% ± 13%) at the well‐coupled coniferous site (Duke), but poor (intermodel μ = approximately 24% ± 6%; observations μ = approximately 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.
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Self-citationStomatal Control of Transpiration: Scaling Up from Leaf to Region
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Metadata
- Authors
- De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Walker, A. P., Dietze, M. C., Hickler, T., Jain, A. K., Luo, Y., Parton, W. J., Prentice, I. C., Smith, B., Thornton, P. E., Wang, S., Wang, Y., Wårlind, D., Weng, E., Crous, K. Y., Ellsworth, D. S., Hanson, P. J., Seok Kim, H., Warren, J. M., Oren, R., & Norby, R. J.
- Venue
- Global Change Biology
- Publisher
- Wiley
- Published
- 2013-03-25
- Volume
- 19
- Issue
- 6
- Pages
- 1759-1779
- ISSN
- 1354-1013 (ISSN-L)
- 1365-2486
- OpenAlex
- W2166572146
- Cited by
- 384
- References
- 93
- FWCI
- 29.21
- Type
- journal article
- Language
- en
- Open access
- closed
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- De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Walker, A. P., Dietze, M. C., Hickler, T., Jain, A. K., Luo, Y., Parton, W. J., Prentice, I. C., Smith, B., Thornton, P. E., Wang, S., Wang, Y., Wårlind, D., Weng, E., Crous, K. Y., Ellsworth, D. S., Hanson, P. J., . . . Norby, R. J. (2013). Forest water use and water use efficiency at elevated CO2: a model‐data intercomparison at two contrasting temperate forest FACE sites. Global Change Biology. https://doi.org/10.1111/gcb.12164
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
