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Title: The importance of radiation for semiempirical water-use efficiency models

Water-use efficiency (WUE) is a fundamental property for the coupling of carbon and water cycles in plants and ecosystems. Existing model formulations predicting this variable differ in the type of response of WUE to the atmospheric vapor pressure deficit of water (VPD). We tested a representative WUE model on the ecosystem scale at 110 eddy covariance sites of the FLUXNET initiative by predicting evapotranspiration (ET) based on gross primary productivity (GPP) and VPD. We found that introducing an intercept term in the formulation increases model performance considerably, indicating that an additional factor needs to be considered. We demonstrate that this intercept term varies seasonally and we subsequently associate it with radiation. Replacing the constant intercept term with a linear function of global radiation was found to further improve model predictions of ET. Our new semiempirical ecosystem WUE formulation indicates that, averaged over all sites, this radiation term accounts for up to half (39–47 %) of transpiration. These empirical findings challenge the current understanding of water-use efficiency on the ecosystem scale.
Authors:
 [1] ;  [1] ;  [1] ;  [1]
  1. Max Planck Institute for Biogeochemistry, Jena (Germany). Dept. for Biogeochemical Integration
Publication Date:
Grant/Contract Number:
FG02-04ER63917; FG02-04ER63911
Type:
Accepted Manuscript
Journal Name:
Biogeosciences (Online)
Additional Journal Information:
Journal Name: Biogeosciences (Online); Journal Volume: 14; Journal Issue: 12; Journal ID: ISSN 1726-4189
Publisher:
European Geosciences Union
Research Org:
Oregon State Univ., Corvallis, OR (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; 59 BASIC BIOLOGICAL SCIENCES
OSTI Identifier:
1429886

Boese, Sven, Jung, Martin, Carvalhais, Nuno, and Reichstein, Markus. The importance of radiation for semiempirical water-use efficiency models. United States: N. p., Web. doi:10.5194/bg-14-3015-2017.
Boese, Sven, Jung, Martin, Carvalhais, Nuno, & Reichstein, Markus. The importance of radiation for semiempirical water-use efficiency models. United States. doi:10.5194/bg-14-3015-2017.
Boese, Sven, Jung, Martin, Carvalhais, Nuno, and Reichstein, Markus. 2017. "The importance of radiation for semiempirical water-use efficiency models". United States. doi:10.5194/bg-14-3015-2017. https://www.osti.gov/servlets/purl/1429886.
@article{osti_1429886,
title = {The importance of radiation for semiempirical water-use efficiency models},
author = {Boese, Sven and Jung, Martin and Carvalhais, Nuno and Reichstein, Markus},
abstractNote = {Water-use efficiency (WUE) is a fundamental property for the coupling of carbon and water cycles in plants and ecosystems. Existing model formulations predicting this variable differ in the type of response of WUE to the atmospheric vapor pressure deficit of water (VPD). We tested a representative WUE model on the ecosystem scale at 110 eddy covariance sites of the FLUXNET initiative by predicting evapotranspiration (ET) based on gross primary productivity (GPP) and VPD. We found that introducing an intercept term in the formulation increases model performance considerably, indicating that an additional factor needs to be considered. We demonstrate that this intercept term varies seasonally and we subsequently associate it with radiation. Replacing the constant intercept term with a linear function of global radiation was found to further improve model predictions of ET. Our new semiempirical ecosystem WUE formulation indicates that, averaged over all sites, this radiation term accounts for up to half (39–47 %) of transpiration. These empirical findings challenge the current understanding of water-use efficiency on the ecosystem scale.},
doi = {10.5194/bg-14-3015-2017},
journal = {Biogeosciences (Online)},
number = 12,
volume = 14,
place = {United States},
year = {2017},
month = {6}
}