How do leaf and ecosystem measures of water-use efficiency compare?

The terrestrial carbon and water cycles are intimately linked: the carbon cycle is driven by photosynthesis, while the water balance is dominated by transpiration, and both fluxes are controlled by plant stomatal conductance. The ratio between these fluxes, the plant water-use efficiency (WUE), is a...

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Veröffentlicht in:The New phytologist Jg. 216; H. 3; S. 758 - 770
Hauptverfasser: Medlyn, Belinda E., De Kauwe, Martin G., Lin, Yan‐Shih, Knauer, Jürgen, Duursma, Remko A., Williams, Christopher A., Arneth, Almut, Clement, Rob, Isaac, Peter, Limousin, Jean‐Marc, Linderson, Maj‐Lena, Meir, Patrick, Martin‐StPaul, Nicolas, Wingate, Lisa
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England New Phytologist Trust 01.11.2017
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ISSN:0028-646X, 1469-8137, 1469-8137
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Zusammenfassung:The terrestrial carbon and water cycles are intimately linked: the carbon cycle is driven by photosynthesis, while the water balance is dominated by transpiration, and both fluxes are controlled by plant stomatal conductance. The ratio between these fluxes, the plant water-use efficiency (WUE), is a useful indicator of vegetation function. WUE can be estimated using several techniques, including leaf gas exchange, stable isotope discrimination, and eddy covariance. Here we compare global compilations of data for each of these three techniques. We show that patterns of variation in WUE across plant functional types (PFTs) are not consistent among the three datasets. Key discrepancies include the following: leaf-scale data indicate differences between needleleaf and broadleaf forests, but ecosystem-scale data do not; leaf-scale data indicate differences between C3 and C4 species, whereas at ecosystem scale there is a difference between C3 and C4 crops but not grasslands; and isotope-based estimates of WUE are higher than estimates based on gas exchange for most PFTs. Our study quantifies the uncertainty associated with different methods of measuring WUE, indicates potential for bias when using WUE measures to parameterize or validate models, and indicates key research directions needed to reconcile alternative measures of WUE.
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USDOE
ISSN:0028-646X
1469-8137
1469-8137
DOI:10.1111/nph.14626