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| 001 | 889718 | ||
| 005 | 20211025141312.0 | ||
| 024 | 7 | _ | |a 10.1016/j.agrformet.2020.108242 |2 doi |
| 024 | 7 | _ | |a 0168-1923 |2 ISSN |
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| 100 | 1 | _ | |a Herbst, Michael |0 P:(DE-Juel1)129469 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Quantification of water stress induced within-field variability of carbon dioxide fluxes in a sugar beet stand |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2021 |b Elsevier |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a Net ecosystem exchange of carbon dioxide (NEE) and soil respiration at field scale can exhibit considerable spatial variability linked to the heterogeneity of soil properties and state variables. In this study, we measured NEE with the eddy covariance (EC) method in a sugar beet field characterized by high spatial variability in soil physical properties. We further measured NEE and soil respiration by chambers as well as soil water content and temperature at 18 locations within the field.Spatially averaged chamber-measured NEE showed good agreement to the EC-based data. During a dry period high spatial variation of within-field NEE was detected with the chamber method. The coefficient of variation was on average 0.57 during the dry period, with a maximum of 0.72. Based on the depth-specific soil water content measurements the AgroC ecosystem model was inverted for soil hydraulic properties at each of the 18 locations, where soil water content was measured. Analyzing the model results revealed that root water uptake stress was the main driver of spatial and temporal variability in crop development and NEE, whereby the soil coarse material fraction (gravel content) and thickness of the layer above a gravel dominated soil layer were identified as the main influencing soil properties.The chamber-measured NEE and the flux footprint analysis showed that particularly during periods of severe root water uptake stress EC-based measurements would be prone to biases. A combination of the footprint model with the AgroC ecosystem model estimated a bias of 14 % for the dry period and a vegetation period bias of 6 % in relation to the average CO2 flux. |
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| 700 | 1 | _ | |a Pohlig, Philipp |0 P:(DE-Juel1)162321 |b 1 |
| 700 | 1 | _ | |a Graf, Alexander |0 P:(DE-Juel1)129461 |b 2 |
| 700 | 1 | _ | |a Weihermüller, Lutz |0 P:(DE-Juel1)129553 |b 3 |
| 700 | 1 | _ | |a Schmidt, M. |0 P:(DE-Juel1)144420 |b 4 |
| 700 | 1 | _ | |a Vanderborght, Jan |0 P:(DE-Juel1)129548 |b 5 |
| 700 | 1 | _ | |a Vereecken, H. |0 P:(DE-Juel1)129549 |b 6 |
| 773 | _ | _ | |a 10.1016/j.agrformet.2020.108242 |g Vol. 297, p. 108242 - |0 PERI:(DE-600)2012165-9 |p 108242 - |t Agricultural and forest meteorology |v 297 |y 2021 |x 0168-1923 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/889718/files/supplement.pdf |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/889718/files/text.pdf |y Published on 2020-11-12. Available in OpenAccess from 2022-11-12. |
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