Widespread and complex drought effects on vegetation physiology inferred from space.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
15 08 2023
Historique:
received: 26 02 2023
accepted: 12 07 2023
medline: 17 8 2023
pubmed: 16 8 2023
entrez: 15 8 2023
Statut: epublish

Résumé

The response of vegetation physiology to drought at large spatial scales is poorly understood due to a lack of direct observations. Here, we study vegetation drought responses related to photosynthesis, evaporation, and vegetation water content using remotely sensed data, and we isolate physiological responses using a machine learning technique. We find that vegetation functional decreases are largely driven by the downregulation of vegetation physiology such as stomatal conductance and light use efficiency, with the strongest downregulation in water-limited regions. Vegetation physiological decreases in wet regions also result in a discrepancy between functional and structural changes under severe drought. We find similar patterns of physiological drought response using simulations from a soil-plant-atmosphere continuum model coupled with a radiative transfer model. Observation-derived vegetation physiological responses to drought across space are mainly controlled by aridity and additionally modulated by abnormal hydro-meteorological conditions and vegetation types. Hence, isolating and quantifying vegetation physiological responses to drought enables a better understanding of ecosystem biogeochemical and biophysical feedback in modulating climate change.

Identifiants

pubmed: 37582763
doi: 10.1038/s41467-023-40226-9
pii: 10.1038/s41467-023-40226-9
pmc: PMC10427636
doi:

Substances chimiques

Water 059QF0KO0R

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4640

Informations de copyright

© 2023. The Author(s).

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Auteurs

Wantong Li (W)

Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany. wantong@bgc-jena.mpg.de.

Javier Pacheco-Labrador (J)

Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.

Mirco Migliavacca (M)

European Commission, Joint Research Centre (JRC), Ispra, Italy.

Diego Miralles (D)

Hydro-Climate Extremes Lab (H-CEL), Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.

Anne Hoek van Dijke (A)

Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.

Markus Reichstein (M)

Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.
Integrative Center for Biodiversity Research (iDIV), Leipzig, Germany.

Matthias Forkel (M)

Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Dresden, Germany.

Weijie Zhang (W)

Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.

Christian Frankenberg (C)

Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, 91125, USA.
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA.

Annu Panwar (A)

Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.

Qian Zhang (Q)

School of Geomatics Science and Technology, Nanjing Tech University, Nanjing, China.

Ulrich Weber (U)

Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.

Pierre Gentine (P)

Department of Earth and Environmental Engineering, Columbia University, New York, NY, 10027, USA.

Rene Orth (R)

Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.

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Classifications MeSH