2014
DOI: 10.1002/eco.1478
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Quantifying the effects of elevated CO2 on water budgets by combining FACE data with an ecohydrological model

Abstract: Response of leaf area index (LAI) is the key determinant for predicting impacts of the elevated CO2 (eCO2) on water budgets. Importance of the changes in functional attributes of vegetation associated with eCO2 for predicting responses of LAI has rarely been addressed. In this study, the WAter Vegetation Energy and Solute (WAVES) model was applied to simulate ecohydrological effects of the eCO2 at two free‐air CO2 enrichment (FACE) experimental sites with contrasting vegetation. One was carried out by the Oak … Show more

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Cited by 12 publications
(6 citation statements)
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References 102 publications
(158 reference statements)
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“…Assuming that increased CO 2 does have a positive impact on water-use efficiency, this effect could be cancelled out by changes in average temperatures. Additionally, leaf area index is known to increase under elevated CO 2 , offsetting additional water availability that results from reduced stomatal conductance (Cheng et al 2014 ). Angert et al ( 2005 ) demonstrate that in the northern hemisphere, any benefit plants experience from increased CO 2 is counteracted by increasing summer temperatures.…”
Section: Global Driversmentioning
confidence: 99%
See 1 more Smart Citation
“…Assuming that increased CO 2 does have a positive impact on water-use efficiency, this effect could be cancelled out by changes in average temperatures. Additionally, leaf area index is known to increase under elevated CO 2 , offsetting additional water availability that results from reduced stomatal conductance (Cheng et al 2014 ). Angert et al ( 2005 ) demonstrate that in the northern hemisphere, any benefit plants experience from increased CO 2 is counteracted by increasing summer temperatures.…”
Section: Global Driversmentioning
confidence: 99%
“…It is possible, therefore, that any additionally water saved through decreases in stomatal conductance would be used to mitigate against this added stress, with the net consequence that there is little effect on tree and grass growth rates. In consequence, predicting the overall effects of increased soil moisture from a decrease in stomatal conductance is made challenging by different stomatal responses and confounding interacting factors, such as plant traits, composition and local climate (Cheng et al 2014 ).…”
Section: Global Driversmentioning
confidence: 99%
“…The BW model can realistically represent a comprehensive range of soil moisture characteristics, from a highly nonlinear associated with a well-developed capillary fringe to a weakly nonlinear associated with highly structured soil and macropores. The WAVES model has been successfully used to simulate vegetation water-use and carbon processes under different conditions (Wang et al 2013;Chen et al 2016) and quantify water budget with elevated CO 2 (Cheng et al 2014a(Cheng et al , 2014b. The advantages of the WAVES model are the following: (1) accurately simulating the soil water dynamics under saturated and unsaturated soil and (2) accurately simulating the canopy transpiration due to the linkage between the hydrological process and vegetation growth at plot scales (Cheng et al 2014b).…”
Section: Waves Modelmentioning
confidence: 99%
“…Zhang et al (1999) used the WAVES model to test lucerne growth and groundwater uptake with the salinity and groundwater level changes, and the results also showed that the WAVES model can simulate well and can be used in the irrigated agricultural systems. In recent years, the WAVES model was used to study the impacts of climate change and CO 2 concentration increase on hydrological processes (Crosbie et al 2010;Cheng et al 2014aCheng et al , 2014b. Crosbie et al (2010) enlarged the WAVES model application scale from point to the basin after the study of future climate impacts on the groundwater recharge in the Murray-Darling Basin in Australia.…”
Section: Introductionmentioning
confidence: 99%
“…The various approaches include models that concentrate, for example, on the factors directly relevant to greenhouse gas emissions [13][14][15] or track the dependencies for the entire ecosystem (see, for example, the LPJ model family [16,17]). Such ecosystem models are predestined for mapping the manifold effects of elevated CO 2 concentrations but require correspondingly long observation series from FACE experiments for validation [18,19]. In a comprehensive study, several complex ecosystem models were calibrated and tested against measurements from two Forest-FACE experiments [20,21] showing that all models lacked the capability to simulate long-term effects of enhanced CO 2 adequately.…”
mentioning
confidence: 99%