Articles | Volume 19, issue 17
https://doi.org/10.5194/bg-19-4315-2022
https://doi.org/10.5194/bg-19-4315-2022
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12 Sep 2022
Research article | Highlight paper |  | 12 Sep 2022

Contrasting drought legacy effects on gross primary productivity in a mixed versus pure beech forest

Xin Yu, René Orth, Markus Reichstein, Michael Bahn, Anne Klosterhalfen, Alexander Knohl, Franziska Koebsch, Mirco Migliavacca, Martina Mund, Jacob A. Nelson, Benjamin D. Stocker, Sophia Walther, and Ana Bastos

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Latest update: 29 Dec 2024
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Co-editor-in-chief
This study significantly contributes to alleviating the data scarcity of drought legacy effects on ecosystem photosynthesis in temperate deciduous forests with a novel machine learning approach. This is probably the first time that drought legacies on ecosystem carbon fluxes are quantified using eddy-covariance data. The study reported that the reduction in photosynthesis due to drought legacy effects was of comparable magnitude to the concurrent drought effects at the studied sites. This study thus emphasizes the importance of drought legacy effects and provides a novel analytical method to quantify legacy effects elsewhere.
Short summary
Identifying drought legacy effects is challenging because they are superimposed on variability driven by climate conditions in the recovery period. We develop a residual-based approach to quantify legacies on gross primary productivity (GPP) from eddy covariance data. The GPP reduction due to legacy effects is comparable to the concurrent effects at two sites in Germany, which reveals the importance of legacy effects. Our novel methodology can be used to quantify drought legacies elsewhere.
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