Articles | Volume 23, issue 6
https://doi.org/10.5194/bg-23-2079-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-23-2079-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Mar 2026
Research article |
| 26 Mar 2026
| 26 Mar 2026
Interpreting carbon-water trade-offs in Daisy crop model using Pareto-based calibration
Laura Delhez
CORRESPONDING AUTHOR
Biosystems Dynamics and Exchanges, TERRA Teaching and Research Centre, University of Liège, Gembloux, 5030, Belgium
Eric Laloy
Sustainable Waste & Decommissioning, Belgian Nuclear Research Centre (SCK-CEN), Mol, 2400, Belgium
Quentin Beauclaire
Biosystems Dynamics and Exchanges, TERRA Teaching and Research Centre, University of Liège, Gembloux, 5030, Belgium
Bernard Longdoz
CORRESPONDING AUTHOR
Biosystems Dynamics and Exchanges, TERRA Teaching and Research Centre, University of Liège, Gembloux, 5030, Belgium
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Jennifer Michel, Yves Brostaux, Bernard Longdoz, Hervé Vanderschuren, and Pierre Delaplace
SOIL, 11, 755–762, https://doi.org/10.5194/soil-11-755-2025, https://doi.org/10.5194/soil-11-755-2025, 2025
Short summary
Short summary
We discuss three aspects to ensure (rhizosphere) priming effects are correctly perceived in their ecological context and measured at appropriate scales. (i) The first aspect is that there is little empirical evidence for net C losses from priming. (ii) The second aspect is critical publication bias. (iii) The third aspect is a need to distinguish between priming effects (PE) and rhizosphere priming effects (RPE).
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Short summary
Using an advanced optimisation method, we calibrated a crop model against dry matter, carbon and water exchanges. Although model predictions matched observations well, the process revealed weaknesses in the model, such as difficulty in representing evapotranspiration, especially during heatwaves. This multi-objective approach highlighted the need to better capture stomatal and non-stomatal responses in order to improve predictions of crop models.
Using an advanced optimisation method, we calibrated a crop model against dry matter, carbon and...
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