Articles | Volume 23, issue 10
https://doi.org/10.5194/bg-23-3365-2026
© 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-23-3365-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 May 2026
Research article |
| 20 May 2026
| 20 May 2026
Detection of tree stress from sub-daily sap flow variability
Anna T. Schackow
CORRESPONDING AUTHOR
Institute for Earth System Science and Remote Sensing, Leipzig University, Germany
Max Planck Institute for Biogeochemistry, Dept. of Biogeochemical Integration, Jena, Germany
Susan C. Steele-Dunne
Department of Geoscience and Remote Sensing, Delft University of Technology, the Netherlands
David T. Milodowski
School of GeoSciences, University of Edinburgh, Edinburgh UK
Jean-Marc Limousin
4 CEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
Institute for Earth System Science and Remote Sensing, Leipzig University, Germany
Max Planck Institute for Biogeochemistry, Dept. of Biogeochemical Integration, Jena, Germany
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Thomas Luke Smallman, David Thomas Milodowski, and Mathew Williams
EGUsphere, https://doi.org/10.5194/egusphere-2026-3014, https://doi.org/10.5194/egusphere-2026-3014, 2026
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
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The terrestrial carbon (C) cycle is key in regulating ecosystem services; underpinning human livelihoods. Current global datasets are inadequate to provide > 95 % confidence on the sign of net exchange. We can identify ~ 1 % of vegetated land as a net source/sink. Uncertainty is driven by the dynamics of wood (r = 0.8) and soil (r = 0.7). Missions such as BIOMASS may enhance sink/source detection. Soil C requires research and investment required to provide global constraint on soil C changes.
Tim Stripp, Zhixuan Guo, Pierre Friedlingstein, Michael O’Sullivan, Stephen Sitch, Ana Bastos, Philippe Ciais, Jefferson Goncalves de Souza, Akihiko Ito, Wei Li, and Lei Ma
EGUsphere, https://doi.org/10.5194/egusphere-2026-3584, https://doi.org/10.5194/egusphere-2026-3584, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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Fire is a key process within the Earth system, yet it is often poorly represented in land carbon cycle models used to estimate how much carbon land ecosystems absorb from the atmosphere. We improved these models by applying long-term burned area data reconstructed from satellite observations. This reduced biases and uncertainty in fire carbon emission estimates and improved estimates of land carbon uptake, implying this method could enhance global and regional carbon budget estimates.
Franziska Müller, Laura Eifler, Felix Cremer, Pieter Beck, Gustau Camps-Valls, and Ana Bastos
Nat. Hazards Earth Syst. Sci., 26, 2785–2815, https://doi.org/10.5194/nhess-26-2785-2026, https://doi.org/10.5194/nhess-26-2785-2026, 2026
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Forest health is increasingly threatened, but disturbances like wind damage and insect outbreaks are hard to track. Our Sentinel-1 Disturbance Mapping (S1DM) approach combines satellite radar with survey data, improving detection for wind and bark beetle impacts and often spotting them earlier. Defoliators remain difficult to capture, but this method strengthens monitoring and supports better forest management.
Guohua Liu, Philippe Ciais, Shengli Tao, Hui Yang, Chenwei Xiao, and Ana Bastos
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-246, https://doi.org/10.5194/essd-2026-246, 2026
Preprint under review for ESSD
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We developed a long-term, moderate-resolution global dataset of forest above ground biomass, from satellite radar data and machine learning. The significance of this dataset lies in its ability to provide a continuous, moderate-resolution view of biomass carbon dynamics, offering a valuable resource for supporting studies of climate change, disturbance, and land use, and will help improve Earth System models and future carbon cycle.
Tim J. Green, David T. Milodowski, T. Luke Smallman, Annikki Mäkelä, and Mathew Williams
EGUsphere, https://doi.org/10.5194/egusphere-2026-2222, https://doi.org/10.5194/egusphere-2026-2222, 2026
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Widely used satellite-based products of leaf area index (LAI) used in carbon cycle studies consistently show unrealistically high seasonality over northern evergreen needleleaf forests. This study uses a model-data fusion approach to show how these biases adversely affect carbon cycle model results by comparing outputs against a calibration that includes leaf lifespan data and summer-only LAI. Results highlight the urgent need for modelling studies and LAI producers to address these biases.
Mara Y. McPartland, Tomas Lovato, Charles Koven, Jamie D. Wilson, Briony Turner, Colleen M. Petrik, José Licón-Saláiz, Fang Li, Fanny Lhardy, Jaclyn Clement Kinney, Michio Kawamiya, Birgit Hassler, Nathan P. Gillett, Cheikh Modou Noreyni Fall, Christopher Danek, Chris M. Brierley, Ana Bastos, and Oliver Andrews
Geosci. Model Dev., 19, 2849–2880, https://doi.org/10.5194/gmd-19-2849-2026, https://doi.org/10.5194/gmd-19-2849-2026, 2026
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The Coupled Model Intercomparison Project (CMIP) is an international consortium of climate modeling groups that produce coordinated experiments in order to evaluate human influence on the climate and test knowledge of Earth systems. This paper describes the data requested for Earth systems research in CMIP7. We detail the request for model output of the carbon cycle, the flows of energy among the atmosphere, land and the oceans, and interactions between these and the global climate.
Laura Eifler, Franziska Müller, and Ana Bastos
Biogeosciences, 23, 1291–1325, https://doi.org/10.5194/bg-23-1291-2026, https://doi.org/10.5194/bg-23-1291-2026, 2026
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Forests provide ecosystem services and biodiversity, but they are increasingly affected by disturbances. We evaluate five forest disturbance datasets across the Unites States to assess their consistency in space, timing, and disturbance agents. While datasets show good agreement in disturbance timing, spatial overlap and agent attribution differ substantially. This emphasizes the need for enhanced data quality assessment, integration, and accuracy to better understand forest disturbances.
Samuel Upton, Markus Reichstein, Wouter Peters, Santiago Botía, Jacob A. Nelson, Sophia Walther, Martin Jung, Fabian Gans, László Haszpra, and Ana Bastos
Atmos. Chem. Phys., 26, 2561–2595, https://doi.org/10.5194/acp-26-2561-2026, https://doi.org/10.5194/acp-26-2561-2026, 2026
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We create a hybrid ecosystem-level carbon flux model using both eddy-covariance observations and observations of the atmospheric mole fraction of CO2 at three tall-tower observatories. Our study uses an atmospheric transport model (STILT) to connect the atmospheric signal to the ecosystem-level model. We show that this inclusion of atmospheric information meaningfully improves the model's representation of the interannual variability of the global net flux of CO2.
Na Li, Sebastian Sippel, Nora Linscheid, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
Biogeosciences, 23, 767–792, https://doi.org/10.5194/bg-23-767-2026, https://doi.org/10.5194/bg-23-767-2026, 2026
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We study when anthropogenic signal becomes detectable in the global land carbon sink, which has risen since the 1950s due to CO₂ fertilization and mid- to high-latitude warming. The signal emerges earlier at the global than at regional scales. Future scenarios (2016–2100) take longer to detect than the historical period (1851–2014) because the signal is weaker relative to larger natural variability. Removing circulation-induced variability with dynamical adjustment shortens the detection time.
Tanguy Postic, François de Coligny, Isabelle Chuine, Louis Devresse, Daniel Berveiller, Hervé Cochard, Matthias Cuntz, Nicolas Delpierre, Émilie Joetzjer, Jean-Marc Limousin, Jean-Marc Ourcival, François Pimont, Julien Ruffault, Guillaume Simioni, Nicolas K. Martin-StPaul, and Xavier Morin
Geosci. Model Dev., 18, 7603–7679, https://doi.org/10.5194/gmd-18-7603-2025, https://doi.org/10.5194/gmd-18-7603-2025, 2025
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PHOREAU is a forest dynamic model that links plant traits with water use, growth, and climate responses to explore how species diversity affects productivity and resilience. Validated across European forests, PHOREAU simulates how tree communities function under drought and warming. Our findings support the use of trait-based modeling to guide forest adaptation strategies under future climate scenarios.
Friedrich J. Bohn, Giles B. Sioen, Ana Bastos, Yolandi Ernst, Marcin P. Jarzebski, Niak S. Koh, Romina Martin, Anja Rammig, Alex Godoy-Faúndez, Alexandros Gasparatos, Alvaro G. Gutiérrez, Amanda J. Aceituno, Andra-Ioana Horcea-Milcu, Andrea Marais-Potgieter, Ayyoob Sharifi, Caroline Howe, Cornelia B. Krug, Eduardo E. Acosta, Emmanuel F. Nzunda, Erik Andersson, Hans-Otto Pörtner, Helen Sooväli-Sepping, Ishihara Hiroe, Ivan Palmegiani, Kaera Coetzer, Kirsten Thonike, Krizler Tanalgo, Lisa Biber-Freudenberger, Nicholas O. Oguge, Mi S. Park, Milena Gross, Pablo De La Cruz, Paula R. Prist, Peng Bi, Rivera Diego, Roman Isaac, Rosemary McFarlane, Sinikka J. Paulus, Stefanie Burkhart, Sung-Ching Lee, Susanne Müller, Uchi D. Terhile, Wan-Yu Shih, William K. Smith, Viola Hakkarainen, Virginia Murray, Yuki Yoshida, Yohannes T. Damtew, and Zeenat Niazi
EGUsphere, https://doi.org/10.5194/egusphere-2025-3619, https://doi.org/10.5194/egusphere-2025-3619, 2025
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The aim of this series is to provide decision-makers with valuable insights into the current state of biosphere research. Firstly, it is intended to ensure the flow of information between the comprehensive assessment reports of the IPCC and IPBES. On the other hand, it is intended to support economic and political decisions closely related to the biosphere with scientifically sound findings – including uncertainties – and comprehensive polysolutions, helping to solve the earth system polycrisis.
Zhixuan Guo, Wei Li, Philippe Ciais, Stephen Sitch, Guido R. van der Werf, Simon P. K. Bowring, Ana Bastos, Florent Mouillot, Jiaying He, Minxuan Sun, Lei Zhu, Xiaomeng Du, Nan Wang, and Xiaomeng Huang
Earth Syst. Sci. Data, 17, 3599–3618, https://doi.org/10.5194/essd-17-3599-2025, https://doi.org/10.5194/essd-17-3599-2025, 2025
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To address the limitations of short time spans in satellite data and spatiotemporal discontinuity in site records, we reconstructed global monthly burned area maps at a 0.5° resolution for 1901–2020 using machine learning models. The global burned area is predicted at 3.46 × 106–4.58 × 106 km² per year, showing a decline from 1901 to 1978, an increase from 1978 to 2008 and a sharper decrease from 2008 to 2020. This dataset provides a benchmark for studies on fire ecology and the carbon cycle.
Guohua Liu, Philippe Ciais, Shengli Tao, Hui Yang, and Ana Bastos
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-330, https://doi.org/10.5194/essd-2025-330, 2025
Manuscript not accepted for further review
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We have developed a long-term and high-resolution global map of above-ground biomass changes from 1993 to 2020 using radar data and machine learning approach. This dataset can help understand the effects of disturbances, land-use changes, and extreme events on global carbon cycle, and enhance the representation of these processes in Earth System Models.
Theertha Kariyathan, Ana Bastos, Markus Reichstein, Wouter Peters, and Julia Marshall
Atmos. Chem. Phys., 25, 7863–7878, https://doi.org/10.5194/acp-25-7863-2025, https://doi.org/10.5194/acp-25-7863-2025, 2025
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The carbon uptake period (CUP) is the time period when land absorbs more CO2 than it emits. While atmospheric CO2 mole fraction measurements can be used to assess CUP changes, atmospheric transport and asynchronous timing across regions reduce the accuracy of the estimates. Forward model experiments show that only ~ 50 % of prescribed shifts in CUP timing applied to surface fluxes (ΔCUPNEE) are captured in simulated CO2 mole fraction data at monitoring sites like the Barrow Atmospheric Baseline Observatory.
Friedrich J. Bohn, Ana Bastos, Romina Martin, Anja Rammig, Niak Sian Koh, Giles B. Sioen, Bram Buscher, Louise Carver, Fabrice DeClerck, Moritz Drupp, Robert Fletcher, Matthew Forrest, Alexandros Gasparatos, Alex Godoy-Faúndez, Gregor Hagedorn, Martin C. Hänsel, Jessica Hetzer, Thomas Hickler, Cornelia B. Krug, Stasja Koot, Xiuzhen Li, Amy Luers, Shelby Matevich, H. Damon Matthews, Ina C. Meier, Mirco Migliavacca, Awaz Mohamed, Sungmin O, David Obura, Ben Orlove, Rene Orth, Laura Pereira, Markus Reichstein, Lerato Thakholi, Peter H. Verburg, and Yuki Yoshida
Biogeosciences, 22, 2425–2460, https://doi.org/10.5194/bg-22-2425-2025, https://doi.org/10.5194/bg-22-2425-2025, 2025
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An interdisciplinary collaboration of 36 international researchers from 35 institutions highlights recent findings in biosphere research. Within eight themes, they discuss issues arising from climate change and other anthropogenic stressors and highlight the co-benefits of nature-based solutions and ecosystem services. Based on an analysis of these eight topics, we have synthesized four overarching insights.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
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When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Mathew Williams, David T. Milodowski, T. Luke Smallman, Kyle G. Dexter, Gabi C. Hegerl, Iain M. McNicol, Michael O'Sullivan, Carla M. Roesch, Casey M. Ryan, Stephen Sitch, and Aude Valade
Biogeosciences, 22, 1597–1614, https://doi.org/10.5194/bg-22-1597-2025, https://doi.org/10.5194/bg-22-1597-2025, 2025
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Southern African woodlands are important in both regional and global carbon cycles. A new carbon analysis created by combining satellite data with ecosystem modelling shows that the region has a neutral C balance overall but with important spatial variations. Patterns of biomass and C balance across the region are the outcome of climate controls on production and vegetation–fire interactions, which determine the mortality of vegetation and spatial variations in vegetation function.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
István Dunkl, Ana Bastos, and Tatiana Ilyina
Earth Syst. Dynam., 16, 151–167, https://doi.org/10.5194/esd-16-151-2025, https://doi.org/10.5194/esd-16-151-2025, 2025
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While the El Niño–Southern Oscillation, a climate mode, has a similar impact on CO2 growth rates across Earth system models, there is significant uncertainty in the processes behind this relationship. We found a compensatory effect that masks differences in the sensitivity of carbon fluxes to climate anomalies and observed that the carbon fluxes contributing to global CO2 anomalies originate from different regions and are caused by different drivers.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
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Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
Samuel Upton, Markus Reichstein, Fabian Gans, Wouter Peters, Basil Kraft, and Ana Bastos
Atmos. Chem. Phys., 24, 2555–2582, https://doi.org/10.5194/acp-24-2555-2024, https://doi.org/10.5194/acp-24-2555-2024, 2024
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Data-driven eddy-covariance upscaled estimates of the global land–atmosphere net CO2 exchange (NEE) show important mismatches with regional and global estimates based on atmospheric information. To address this, we create a model with a dual constraint based on bottom-up eddy-covariance data and top-down atmospheric inversion data. Our model overcomes shortcomings of each approach, producing improved NEE estimates from local to global scale, helping to reduce uncertainty in the carbon budget.
Wolfgang Alexander Obermeier, Clemens Schwingshackl, Ana Bastos, Giulia Conchedda, Thomas Gasser, Giacomo Grassi, Richard A. Houghton, Francesco Nicola Tubiello, Stephen Sitch, and Julia Pongratz
Earth Syst. Sci. Data, 16, 605–645, https://doi.org/10.5194/essd-16-605-2024, https://doi.org/10.5194/essd-16-605-2024, 2024
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We provide and compare country-level estimates of land-use CO2 fluxes from a variety and large number of models, bottom-up estimates, and country reports for the period 1950–2021. Although net fluxes are small in many countries, they are often composed of large compensating emissions and removals. In many countries, the estimates agree well once their individual characteristics are accounted for, but in other countries, including some of the largest emitters, substantial uncertainties exist.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
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The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Chenwei Xiao, Sönke Zaehle, Hui Yang, Jean-Pierre Wigneron, Christiane Schmullius, and Ana Bastos
Earth Syst. Dynam., 14, 1211–1237, https://doi.org/10.5194/esd-14-1211-2023, https://doi.org/10.5194/esd-14-1211-2023, 2023
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Ecosystem resistance reflects their susceptibility during adverse conditions and can be changed by land management. We estimate ecosystem resistance to drought and temperature globally. We find a higher resistance to drought in forests compared to croplands and an evident loss of resistance to drought when primary forests are converted to secondary forests or they are harvested. Old-growth trees tend to be more resistant in some forests and crops benefit from irrigation during drought periods.
David T. Milodowski, T. Luke Smallman, and Mathew Williams
Biogeosciences, 20, 3301–3327, https://doi.org/10.5194/bg-20-3301-2023, https://doi.org/10.5194/bg-20-3301-2023, 2023
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Model–data fusion (MDF) allows us to combine ecosystem models with Earth observation data. Fragmented landscapes, with a mosaic of contrasting ecosystems, pose a challenge for MDF. We develop a novel MDF framework to estimate the carbon balance of fragmented landscapes and show the importance of accounting for ecosystem heterogeneity to prevent scale-dependent bias in estimated carbon fluxes, disturbance fluxes in particular, and to improve ecological fidelity of the calibrated models.
Theertha Kariyathan, Ana Bastos, Julia Marshall, Wouter Peters, Pieter Tans, and Markus Reichstein
Atmos. Meas. Tech., 16, 3299–3312, https://doi.org/10.5194/amt-16-3299-2023, https://doi.org/10.5194/amt-16-3299-2023, 2023
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The timing and duration of the carbon uptake period (CUP) are sensitive to the occurrence of major phenological events, which are influenced by recent climate change. This study presents an ensemble-based approach for quantifying the timing and duration of the CUP and their uncertainty when derived from atmospheric CO2 measurements with noise and gaps. The CUP metrics derived with the approach are more robust and have less uncertainty than when estimated with the conventional methods.
Na Li, Sebastian Sippel, Alexander J. Winkler, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
Earth Syst. Dynam., 13, 1505–1533, https://doi.org/10.5194/esd-13-1505-2022, https://doi.org/10.5194/esd-13-1505-2022, 2022
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Quantifying the imprint of large-scale atmospheric circulation dynamics and associated carbon cycle responses is key to improving our understanding of carbon cycle dynamics. Using a statistical model that relies on spatiotemporal sea level pressure as a proxy for large-scale atmospheric circulation, we quantify the fraction of interannual variability in atmospheric CO2 growth rate and the land CO2 sink that are driven by atmospheric circulation variability.
Melissa Ruiz-Vásquez, Sungmin O, Alexander Brenning, Randal D. Koster, Gianpaolo Balsamo, Ulrich Weber, Gabriele Arduini, Ana Bastos, Markus Reichstein, and René Orth
Earth Syst. Dynam., 13, 1451–1471, https://doi.org/10.5194/esd-13-1451-2022, https://doi.org/10.5194/esd-13-1451-2022, 2022
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Subseasonal forecasts facilitate early warning of extreme events; however their predictability sources are not fully explored. We find that global temperature forecast errors in many regions are related to climate variables such as solar radiation and precipitation, as well as land surface variables such as soil moisture and evaporative fraction. A better representation of these variables in the forecasting and data assimilation systems can support the accuracy of temperature forecasts.
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
Biogeosciences, 19, 4315–4329, https://doi.org/10.5194/bg-19-4315-2022, https://doi.org/10.5194/bg-19-4315-2022, 2022
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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.
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022, https://doi.org/10.5194/hess-26-2997-2022, 2022
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This study investigates spatial and temporal patterns in the incidence angle dependence of backscatter from the ASCAT C-band scatterometer and relates those to precipitation, humidity, and radiation data and GRACE equivalent water thickness in ecoregions in the Amazon. The results show that the ASCAT data record offers a unique perspective on vegetation water dynamics exhibiting sensitivity to moisture availability and demand and phenological change at interannual, seasonal, and diurnal scales.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Paul C. Vermunt, Susan C. Steele-Dunne, Saeed Khabbazan, Jasmeet Judge, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022, https://doi.org/10.5194/hess-26-1223-2022, 2022
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This study investigates the use of hydrometeorological sensors to reconstruct variations in internal vegetation water content of corn and relates these variations to the sub-daily behaviour of polarimetric L-band backscatter. The results show significant sensitivity of backscatter to the daily cycles of vegetation water content and dew, particularly on dry days and for vertical and cross-polarizations, which demonstrates the potential for using radar for studies on vegetation water dynamics.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Thomas Luke Smallman, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams
Earth Syst. Dynam., 12, 1191–1237, https://doi.org/10.5194/esd-12-1191-2021, https://doi.org/10.5194/esd-12-1191-2021, 2021
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Our study provides a novel assessment of model parameter, structure and climate change scenario uncertainty contribution to future predictions of the Brazilian terrestrial carbon stocks to 2100. We calibrated (2001–2017) five models of the terrestrial C cycle of varied structure. The calibrated models were then projected to 2100 under multiple climate change scenarios. Parameter uncertainty dominates overall uncertainty, being ~ 40 times that of either model structure or climate change scenario.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
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Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Cited articles
Acosta-Motos, J. R., Ortuño, M. F., Bernal-Vicente, A., Diaz-Vivancos, P., Sanchez-Blanco, M. J., and Hernandez, J. A.: Plant Responses to Salt Stress: Adaptive Mechanisms, Agronomy, 7, 18, https://doi.org/10.3390/agronomy7010018, 2017. a
Aguilos, M., Hérault, B., Burban, B., Wagner, F., and Bonal, D.: What drives long-term variations in carbon flux and balance in a tropical rainforest in French Guiana?, Agr. Forest Meteorol., 253-254, 114–123, https://doi.org/10.1016/j.agrformet.2018.02.009, 2018. a
Allard, V., Ourcival, J.-M., Rambal, S., Joffre, R., and Rocheteau, A.: Seasonal and annual variation of carbon exchange in an evergreen Mediterranean forest in southern France, Glob. Change Biol., 14, 714–725, https://doi.org/10.1111/j.1365-2486.2008.01539.x, 2008. a
Allen, C. D., Breshears, D. D., and McDowell, N. G.: On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene, Ecosphere, 6, art129, https://doi.org/10.1890/ES15-00203.1, 2015. a, b
Apgaua, D. M. G., Ishida, F. Y., Tng, D. Y. P., Laidlaw, M. J., Santos, R. M., Rumman, R., Eamus, D., Holtum, J. A. M., and Laurance, S. G. W.: Functional Traits and Water Transport Strategies in Lowland Tropical Rainforest Trees, PLOS ONE, 10, e0130799, https://doi.org/10.1371/journal.pone.0130799, 2015. a
Asgarimehr, M., Entekhabi, D., and Camps, A.: Diurnal Vegetation Moisture Cycle in the Amazon and Response to Water Stress, Geophys. Res. Lett., 51, e2024GL111462, https://doi.org/10.1029/2024GL111462, 2024. a
Aurelle, D., Thomas, S., Albert, C., Bally, M., Bondeau, A., Boudouresque, C.-F., Cahill, A. E., Carlotti, F., Chenuil, A., Cramer, W., Davi, H., De Jode, A., Ereskovsky, A., Farnet, A.-M., Fernandez, C., Gauquelin, T., Mirleau, P., Monnet, A.-C., Prévosto, B., Rossi, V., Sartoretto, S., Van Wambeke, F., and Fady, B.: Biodiversity, climate change, and adaptation in the Mediterranean, Ecosphere, 13, e3915, https://doi.org/10.1002/ecs2.3915, 2022. a
Barchenkov, A. P., Petrov, I. A., Shushpanov, A. S., and Golyukov, A. S.: Climatic Response of Larch (Larix sp.) Radial Increment in Provenances on the Krasnoyarsk Forest Steppe, Contemp. Probl. Ecol., 16, 620–630, https://doi.org/10.1134/S1995425523050025, 2023. a, b, c, d
Bastos, A., Orth, R., Reichstein, M., Ciais, P., Viovy, N., Zaehle, S., Anthoni, P., Arneth, A., Gentine, P., Joetzjer, E., Lienert, S., Loughran, T., McGuire, P. C., O, S., Pongratz, J., and Sitch, S.: Vulnerability of European ecosystems to two compound dry and hot summers in 2018 and 2019, Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, 2021. a
Berner, L. T., Beck, P. S. A., Bunn, A. G., and Goetz, S. J.: Plant Response to Climate Change along the Forest-Tundra Ecotone in Northeastern Siberia, Glob. Change Biol., 19, 3449–3462, https://doi.org/10.1111/gcb.12304, 2013. a
Bodner, G., Nakhforoosh, A., and Kaul, H.-P.: Management of Crop Water under Drought: A Review, Agron. Sustain. Dev., 35, 401–442, https://doi.org/10.1007/s13593-015-0283-4, 2015. a
Bonal, D., Bosc, A., Ponton, S., Goret, J.-Y., Burban, B., Gross, P., Bonnefond, J.-M., Elbers, J., Longdoz, B., Epron, D., Guehl, J.-M., and Granier, A.: Impact of severe dry season on net ecosystem exchange in the Neotropical rainforest of French Guiana, Glob. Change Biol., 14, 1917–1933, https://doi.org/10.1111/j.1365-2486.2008.01610.x, 2008. a
Brunner, I., Herzog, C., Dawes, M. A., Arend, M., and Sperisen, C.: How Tree Roots Respond to Drought, Front. Plant Sci., 6, 547, https://doi.org/10.3389/fpls.2015.00547, 2015. a
Bustamante, M., Roy, J., Ospina, D., Achakulwisut, P., Aggarwal, A., Bastos, A., Broadgate, W., Canadell, J. G., Carr, E. R., Chen, D., Cleugh, H. A., Ebi, K. L., Edwards, C., Farbotko, C., Fernández-Martínez, M., Frölicher, T. L., Fuss, S., Geden, O., Gruber, N., Harrington, L. J., Hauck, J., Hausfather, Z., Hebden, S., Hebinck, A., Huq, S., Huss, M., Jamero, M. L. P., Juhola, S., Kumarasinghe, N., Lwasa, S., Mallick, B., Martin, M., McGreevy, S., Mirazo, P., Mukherji, A., Muttitt, G., Nemet, G. F., Obura, D., Okereke, C., Oliver, T., Orlove, B., Ouedraogo, N. S., Patra, P. K., Pelling, M., Pereira, L. M., Persson, A., Pongratz, J., Prakash, A., Rammig, A., Raymond, C., Redman, A., Reveco, C., Rockström, J., Rodrigues, R., Rounce, D. R., Schipper, E. L. F., Schlosser, P., Selomane, O., Semieniuk, G., Shin, Y.-J., Siddiqui, T. A., Singh, V., Sioen, G. B., Sokona, Y., Stammer, D., Steinert, N. J., Suk, S., Sutton, R., Thalheimer, L., Thompson, V., Trencher, G., Geest, K. V. D., Werners, S. E., Wübbelmann, T., Wunderling, N., Yin, J., Zickfeld, K., and Zscheischler, J.: Ten new insights in climate science 2023, Glob. Sustain., 7, e19, https://doi.org/10.1017/sus.2023.25, 2023. a
Chakir, A., Frison, P. L., Khabba, S., Ezzahar, J., Villard, L., Fanise, P., Ouaadi, N., Ledantec, V., and Jarlan, L.: Diurnal Cycles of C-Band Temporal Coherence and Backscattering Coefficient Over an Olive Orchard in a Semi-Arid Area: Comparison of In Situ and Sentinel-1 Radar Observations, in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, IEEE, 3801–3804, https://doi.org/10.1109/IGARSS47720.2021.9553129, 2021. a
Chen, L., Zhang, Z., and Ewers, B. E.: Urban Tree Species Show the Same Hydraulic Response to Vapor Pressure Deficit across Varying Tree Size and Environmental Conditions, PLOS ONE, 7, e47882, https://doi.org/10.1371/journal.pone.0047882, 2012. a
Choat, B., Brodribb, T. J., Brodersen, C. R., Duursma, R. A., López, R., and Medlyn, B. E.: Triggers of tree mortality under drought, Nature, 558, 531–539, https://doi.org/10.1038/s41586-018-0240-x, 2018. a
Cicuéndez, V., Litago, J., Huesca, M., Rodríguez-Rastrero, M., Recuero, L., Merino-de Miguel, S., and Palacios-Orueta, A.: Assessment of the gross primary production dynamics of a Mediterranean holm oak forest by remote sensing time series analysis, Agroforest. Syst., 89, 491–510, https://doi.org/10.1007/s10457-015-9786-x, 2015. a
Cranko Page, J., De Kauwe, M. G., Abramowitz, G., Cleverly, J., Hinko-Najera, N., Hovenden, M. J., Liu, Y., Pitman, A. J., and Ogle, K.: Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems, Biogeosciences, 19, 1913–1932, https://doi.org/10.5194/bg-19-1913-2022, 2022. a
Davis, S. D. and Mooney, H. A.: Water use patterns of four co-occurring chaparral shrubs, Oecologia, 70, 172–177, https://doi.org/10.1007/BF00379236, 1986. a
Forster, M. A.: How significant is nocturnal sap flow?, Tree Physiol., 34, 757–765, https://doi.org/10.1093/treephys/tpu051, 2014. a
Franks, P. J., Berry, J. A., Lombardozzi, D. L., and Bonan, G. B.: Stomatal Function across Temporal and Spatial Scales: Deep-Time Trends, Land-Atmosphere Coupling and Global Models, Plant Physiol., 174, 583–602, https://doi.org/10.1104/pp.17.00287, 2017. a
Frappart, F., Wigneron, J.-P., Li, X., Liu, X., Al-Yaari, A., Fan, L., Wang, M., Moisy, C., Le Masson, E., Aoulad Lafkih, Z., Vallé, C., Ygorra, B., and Baghdadi, N.: Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review, Remote Sens., 12, 2915, https://doi.org/10.3390/rs12182915, 2020. a
Friesen, J. C.: Regional vegetation water effects on satellite soil moisture estimations for West Africa, Ecol. Dev. Ser., 63, 153 pp., ISBN 978-3-940124-13-5, 2008. a
Frolking, S., Milliman, T., Palace, M., Wisser, D., Lammers, R., and Fahnestock, M.: Tropical forest backscatter anomaly evident in SeaWinds scatterometer morning overpass data during 2005 drought in Amazonia, Remote Sens. Environ., 115, 897–907, https://doi.org/10.1016/j.rse.2010.11.017, 2011. a
Gambetta, G. A., Herrera, J. C., Dayer, S., Feng, Q., Hochberg, U., and Castellarin, S. D.: The Physiology of Drought Stress in Grapevine: Towards an Integrative Definition of Drought Tolerance, J. Exp. Bot., 71, 4658–4676, https://doi.org/10.1093/jxb/eraa245, 2020. a
Hamadi, A., Albinet, C., Borderies, P., Koleck, T., Villard, L., Ho Tong Minh, D., and Le Toan, T.: Temporal Survey of Polarimetric P-Band Scattering of Tropical Forests, IEEE Trans. Geosci. Remote Sens., 52, 4539–4547, https://doi.org/10.1109/TGRS.2013.2282357, 2014. a
Hartmann, H., Bastos, A., Das, A. J., Esquivel-Muelbert, A., Hammond, W. M., Martínez-Vilalta, J., McDowell, N. G., Powers, J. S., Pugh, T. A. M., and Ruthrof, K. X.: Climate change risks to global forest health: emergence of unexpected events of elevated tree mortality worldwide, Ann. Rev. Plant Biol., 73, 673–702, https://doi.org/10.1146/annurev-arplant-102820-012804, 2022. a
Ho Tong Minh, D., Tebaldini, S., Rocca, F., Le Toan, T., Borderies, P., Koleck, T., Albinet, C., Villard, L., and Hamadi, A.: Temporal decorrelation in tropical forest: results from TropiScat and implications for BIOMASS tomography, in: 2013 IEEE International Geoscience and Remote Sensing Symposium – IGARSS, 1206–1209, https://doi.org/10.1109/IGARSS.2013.6722996, 2013. a
Holtzman, N., Wang, Y., Wood, J. D., Frankenberg, C., and Konings, A. G.: Constraining Plant Hydraulics With Microwave Radiometry in a Land Surface Model: Impacts of Temporal Resolution, Water Resour. Res., 59, e2023WR035481, https://doi.org/10.1029/2023WR035481, 2023. a
Holtzman, N. M., Anderegg, L. D. L., Kraatz, S., Mavrovic, A., Sonnentag, O., Pappas, C., Cosh, M. H., Langlois, A., Lakhankar, T., Tesser, D., Steiner, N., Colliander, A., Roy, A., and Konings, A. G.: L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand, Biogeosciences, 18, 739–753, https://doi.org/10.5194/bg-18-739-2021, 2021. a
Horna, V., Schuldt, B., Brix, S., and Leuschner, C.: Environment and Tree Size Controlling Stem Sap Flux in a Perhumid Tropical Forest of Central Sulawesi, Indonesia, Ann. Forest Sci., 68, 1027–1038, https://doi.org/10.1007/s13595-011-0110-2, 2011. a, b
Humphrey, V. and Frankenberg, C.: Continuous ground monitoring of vegetation optical depth and water content with GPS signals, Biogeosciences, 20, 1789–1811, https://doi.org/10.5194/bg-20-1789-2023, 2023. a
ICOS RI: Ecosystem final quality (L2) product in ETC-Archive format – release 2022-1, ICOS ERIC – Carbon Portal, https://doi.org/10.18160/PAD9-HQHU, 2022. a
Jagdhuber, T., Schmidt, A.-S., Fluhrer, A., Chaparro, D., Jonard, F., Piles, M., Holtzman, N. M., Konings, A. G., Feldman, A., Baur, M. J., Steele-Dunne, S. C., Schellenberg, K., and Kunstmann, H.: Estimation of Forest Water Potential from Ground-Based L-band Radiometry, IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens., 18, 5509–5522, https://doi.org/10.1109/JSTARS.2025.3533567, 2025. a
Jarvis, P. G. and McNaughton, K. G.: Stomatal Control of Transpiration: Scaling Up from Leaf to Region, in: Advances in Ecological Research, edited by: MacFadyen, A. and Ford, E. D., 1–49, Academic Press, https://doi.org/10.1016/S0065-2504(08)60119-1, 1986. a, b
Jones, S., Eller, C. B., and Cox, P. M.: Application of Feedback Control to Stomatal Optimisation in a Global Land Surface Model, Front. Environ. Sci., 10, 970266, https://doi.org/10.3389/fenvs.2022.970266, 2022. a
Khabbazan, S., Steele-Dunne, S. C., Vermunt, P. C., Judge, J., Vreugdenhil, M., and Gao, G.: The influence of surface canopy water on the relationship between L-band backscatter and biophysical variables in agricultural monitoring, Remote Sens. Environ., 268, 112789, https://doi.org/10.1016/j.rse.2021.112789, 2022. a
Konings, A. G., Piles, M., Das, N., and Entekhabi, D.: L-band vegetation optical depth and effective scattering albedo estimation from SMAP, Remote Sens. Environ., 198, 460–470, https://doi.org/10.1016/j.rse.2017.06.037, 2017. a, b
Konings, A. G., Rao, K., and Steele-Dunne, S. C.: Macro to micro: microwave remote sensing of plant water content for physiology and ecology, New Phytol., 223, 1166–1172, https://doi.org/10.1111/nph.15808, 2019. a, b
Konings, A. G., Saatchi, S. S., Frankenberg, C., Keller, M., Leshyk, V., Anderegg, W. R. L., Humphrey, V., Matheny, A. M., Trugman, A., Sack, L., Agee, E., Barnes, M. L., Binks, O., Cawse-Nicholson, K., Christoffersen, B. O., Entekhabi, D., Gentine, P., Holtzman, N. M., Katul, G. G., Liu, Y., Longo, M., Martinez-Vilalta, J., McDowell, N., Meir, P., Mencuccini, M., Mrad, A., Novick, K. A., Oliveira, R. S., Siqueira, P., Steele-Dunne, S. C., Thompson, D. R., Wang, Y., Wehr, R., Wood, J. D., Xu, X., and Zuidema, P. A.: Detecting forest response to droughts with global observations of vegetation water content, Glob. Change Biol., 27, 6005–6024, https://doi.org/10.1111/gcb.15872, 2021. a, b
Kotowska, M. M., Link, R. M., Röll, A., Hertel, D., Hölscher, D., Waite, P.-A., Moser, G., Tjoa, A., Leuschner, C., and Schuldt, B.: Effects of Wood Hydraulic Properties on Water Use and Productivity of Tropical Rainforest Trees, Front. Forest. Glob. Change, 3, 598759, https://doi.org/10.3389/ffgc.2020.598759, 2021. a
Landsberg, J., Waring, R., and Ryan, M.: Water relations in tree physiology: where to from here?, Tree Physiol., 37, 18–32, https://doi.org/10.1093/treephys/tpw102, 2017. a
Lawson, T., von Caemmerer, S., and Baroli, I.: Photosynthesis and Stomatal Behaviour, Springer Berlin Heidelberg, Berlin, Heidelberg, 265–304, https://doi.org/10.1007/978-3-642-13145-5_11, 2011. a
Limousin, J.-M., Rambal, S., Ourcival, J.-M., Rocheteau, A., Joffre, R., and Rodriguez-Cortina, R.: Long-term transpiration change with rainfall decline in a Mediterranean Quercus ilex forest, Glob. Change Biol., 15, 2163–2175, https://doi.org/10.1111/j.1365-2486.2009.01852.x, 2009. a, b, c
Limousin, J.-M., Longepierre, D., Huc, R., and Rambal, S.: Change in hydraulic traits of Mediterranean Quercus ilex subjected to long-term throughfall exclusion, Tree Physiol., 30, 1026–1036, https://doi.org/10.1093/treephys/tpq062, 2010a. a
Limousin, J.-M., Misson, L., Lavoir, A.-V., Martin, N. K., and Rambal, S.: Do photosynthetic limitations of evergreen Quercus ilex leaves change with long-term increased drought severity?, Plant Cell Environ., 33, 863–875, https://doi.org/10.1111/j.1365-3040.2009.02112.x, 2010b. a
Limousin, J.-M., Roussel, A., Rodríguez-Calcerrada, J., Torres-Ruiz, J. M., Moreno, M., Garcia de Jalon, L., Ourcival, J.-M., Simioni, G., Cochard, H., and Martin-StPaul, N.: Drought acclimation of Quercus ilex leaves improves tolerance to moderate drought but not resistance to severe water stress, Plant Cell Environ., 45, 1967–1984, https://doi.org/10.1111/pce.14326, 2022. a
Liu, H., Xu, C., Allen, C. D., Hartmann, H., Wei, X., Yakir, D., Wu, X., and Yu, P.: Nature-based Framework for Sustainable Afforestation in Global Drylands under Changing Climate, Glob. Change Biol., 28, 2202–2220, https://doi.org/10.1111/gcb.16059, 2022. a
Maréchaux, I., Bonal, D., Bartlett, M. K., Burban, B., Coste, S., Courtois, E. A., Dulormne, M., Goret, J.-Y., Mira, E., Mirabel, A., Sack, L., and Stahl, C.: Dry-season Decline in Tree Sapflux Is Correlated with Leaf Turgor Loss Point in a Tropical Rainforest, Funct. Ecol., 32, 2285–2297, https://doi.org/10.1111/1365-2435.13188, 2018. a
Matar, J., Sanjuan-Ferrer, M. J., Rodriguez-Cassola, M., Steele-Dunne, S. C., and De Zan, F.: A Concept for an Interferometric SAR Mission with Sub-daily Revisit, in: 15th European Conference on Synthetic Aperture Radar, EUSAR 2024, 18–22, VDE Verlag GmbH, https://elib.dlr.de/203471/ (last access: 14 May 2026), 2024. a
McDonald, K. C., Dobson, M. C., and Ulaby, F. T.: Using Mimics To Model L-band Multiangle and Multitemporal Backscatter From A Walnut Orchard, IEEE Trans. Geosci. Remote Sens., 28, 477–491, https://doi.org/10.1109/TGRS.1990.572925, 1990. a
McDowell, N. G., Sapes, G., Pivovaroff, A., Adams, H. D., Allen, C. D., Anderegg, W. R. L., Arend, M., Breshears, D. D., Brodribb, T., Choat, B., Cochard, H., De Cáceres, M., De Kauwe, M. G., Grossiord, C., Hammond, W. M., Hartmann, H., Hoch, G., Kahmen, A., Klein, T., Mackay, D. S., Mantova, M., Martínez-Vilalta, J., Medlyn, B. E., Mencuccini, M., Nardini, A., Oliveira, R. S., Sala, A., Tissue, D. T., Torres-Ruiz, J. M., Trowbridge, A. M., Trugman, A. T., Wiley, E., and Xu, C.: Mechanisms of woody-plant mortality under rising drought, CO2 and vapour pressure deficit, Nat. Rev. Earth Environ., 3, 294–308, https://doi.org/10.1038/s43017-022-00272-1, 2022. a
Misson, L., Degueldre, D., Collin, C., Rodriguez, R., Rocheteau, A., Ourcival, J.-M., and Rambal, S.: Phenological responses to extreme droughts in a Mediterranean forest, Glob. Change Biol., 17, 1036–1048, https://doi.org/10.1111/j.1365-2486.2010.02348.x, 2011. a
Momen, M., Wood, J. D., Novick, K. A., Pangle, R., Pockman, W. T., McDowell, N. G., and Konings, A. G.: Interacting Effects of Leaf Water Potential and Biomass on Vegetation Optical Depth, J. Geophys. Res.-Biogeo., 122, 3031–3046, https://doi.org/10.1002/2017JG004145, 2017. a
Monteith, A. R. and Ulander, L. M. H.: A Tower-Based Radar Study of Temporal Coherence of a Boreal Forest at P-, L-, and C-Bands and Linear Cross Polarization, IEEE Trans. Geosci. Remote Sens., 60, 1–15, https://doi.org/10.1109/TGRS.2021.3074098, 2022. a
Ouaadi, N., Villard, L., Ezzahar, J., Frison, P. L., Khabba, S., Kasbani, M., Fanise, P., Chakir, A., Le Dantec, V., Er-Raki, S., and Jarlan, L.: Diurnal Cycles of C-Band Temporal Coherence and Backscattering Coefficient Over a Wheat Field in a Semi-Arid Area, in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, IEEE, 3817–3820, https://doi.org/10.1109/IGARSS47720.2021.9553586, 2021. a
Paget, A. C., Long, D. G., and Madsen, N. M.: RapidScat Diurnal Cycles Over Land, IEEE Trans. Geosc. Remote Sens., 54, 3336–3344, https://doi.org/10.1109/TGRS.2016.2515022, 2016. a
Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Cheah, Y.-W., Poindexter, C., Chen, J., Elbashandy, A., Humphrey, M., Isaac, P., Polidori, D., Ribeca, A., van Ingen, C., Zhang, L., Amiro, B., Ammann, C., Arain, M. A., Ardö, J., Arkebauer, T., Arndt, S. K., Arriga, N., Aubinet, M., Aurela, M., Baldocchi, D., Barr, A., Beamesderfer, E., Marchesini, L. B., Bergeron, O., Beringer, J., Bernhofer, C., Berveiller, D., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Boike, J., Bolstad, P. V., Bonal, D., Bonnefond, J.-M., Bowling, D. R., Bracho, R., Brodeur, J., Brümmer, C., Buchmann, N., Burban, B., Burns, S. P., Buysse, P., Cale, P., Cavagna, M., Cellier, P., Chen, S., Chini, I., Christensen, T. R., Cleverly, J., Collalti, A., Consalvo, C., Cook, B. D., Cook, D., Coursolle, C., Cremonese, E., Curtis, P. S., D’Andrea, E., da Rocha, H., Dai, X., Davis, K. J., De Cinti, B., de Grandcourt, A., De Ligne, A., De Oliveira, R. C., Delpierre, N., Desai, A. R., Di Bella, C. M., di Tommasi, P., Dolman, H., Domingo, F., Dong, G., Dore, S., Duce, P., Dufrêne, E., Dunn, A., Dušek, J., Eamus, D., Eichelmann, U., ElKhidir, H. A. M., Eugster, W., Ewenz, C. M., Ewers, B., Famulari, D., Fares, S., Feigenwinter, I., Feitz, A., Fensholt, R., Filippa, G., Fischer, M., Frank, J., Galvagno, M., Gharun, M., Gianelle, D., Gielen, B., Gioli, B., Gitelson, A., Goded, I., Goeckede, M., Goldstein, A. H., Gough, C. M., Goulden, M. L., Graf, A., Griebel, A., Gruening, C., Grünwald, T., Hammerle, A., Han, S., Han, X., Hansen, B. U., Hanson, C., Hatakka, J., He, Y., Hehn, M., Heinesch, B., Hinko-Najera, N., Hörtnagl, L., Hutley, L., Ibrom, A., Ikawa, H., Jackowicz-Korczynski, M., Janouš, D., Jans, W., Jassal, R., Jiang, S., Kato, T., Khomik, M., Klatt, J., Knohl, A., Knox, S., Kobayashi, H., Koerber, G., Kolle, O., Kosugi, Y., Kotani, A., Kowalski, A., Kruijt, B., Kurbatova, J., Kutsch, W. L., Kwon, H., Launiainen, S., Laurila, T., Law, B., Leuning, R., Li, Y., Liddell, M., Limousin, J.-M., Lion, M., Liska, A. J., Lohila, A., López-Ballesteros, A., López-Blanco, E., Loubet, B., Loustau, D., Lucas-Moffat, A., Lüers, J., Ma, S., Macfarlane, C., Magliulo, V., Maier, R., Mammarella, I., Manca, G., Marcolla, B., Margolis, H. A., Marras, S., Massman, W., Mastepanov, M., Matamala, R., Matthes, J. H., Mazzenga, F., McCaughey, H., McHugh, I., McMillan, A. M. S., Merbold, L., Meyer, W., Meyers, T., Miller, S. D., Minerbi, S., Moderow, U., Monson, R. K., Montagnani, L., Moore, C. E., Moors, E., Moreaux, V., Moureaux, C., Munger, J. W., Nakai, T., Neirynck, J., Nesic, Z., Nicolini, G., Noormets, A., Northwood, M., Nosetto, M., Nouvellon, Y., Novick, K., Oechel, W., Olesen, J. E., Ourcival, J.-M., Papuga, S. A., Parmentier, F.-J., Paul-Limoges, E., Pavelka, M., Peichl, M., Pendall, E., Phillips, R. P., Pilegaard, K., Pirk, N., Posse, G., Powell, T., Prasse, H., Prober, S. M., Rambal, S., Rannik, U., Raz-Yaseef, N., Reed, D., de Dios, V. R., Restrepo-Coupe, N., Reverter, B. R., Roland, M., Sabbatini, S., Sachs, T., Saleska, S. R., Sánchez-Cañete, E. P., Sanchez-Mejia, Z. M., Schmid, H. P., Schmidt, M., Schneider, K., Schrader, F., Schroder, I., Scott, R. L., Sedlák, P., Serrano-Ortíz, P., Shao, C., Shi, P., Shironya, I., Siebicke, L., Šigut, L., Silberstein, R., Sirca, C., Spano, D., Steinbrecher, R., Stevens, R. M., Sturtevant, C., Suyker, A., Tagesson, T., Takanashi, S., Tang, Y., Tapper, N., Thom, J., Tiedemann, F., Tomassucci, M., Tuovinen, J.-P., Urbanski, S., Valentini, R., van der Molen, M., van Gorsel, E., van Huissteden, K., Varlagin, A., Verfaillie, J., Vesala, T., Vincke, C., Vitale, D., Vygodskaya, N., Walker, J. P., Walter-Shea, E., Wang, H., Weber, R., Westermann, S., Wille, C., Wofsy, S., Wohlfahrt, G., Wolf, S., Woodgate, W., Li, Y., Zampedri, R., Zhang, J., Zhou, G., Zona, D., Agarwal, D., Biraud, S., Torn, M., and Papale, D.: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data, Sci. Data, 7, 225, https://doi.org/10.1038/s41597-020-0534-3, 2020. a, b
Peguero-Pina, J. J., Vilagrosa, A., Alonso-Forn, D., Ferrio, J. P., Sancho-Knapik, D., and Gil-Pelegrín, E.: Living in Drylands: Functional Adaptations of Trees and Shrubs to Cope with High Temperatures and Water Scarcity, Forests, 11, 1028, https://doi.org/10.3390/f11101028, 2020. a
Peltier, D. M. P. and Ogle, K.: Still recovering or just remembering? To understand drought legacies, modelling choices matter, J. Ecol., 111, 1170–1173, https://doi.org/10.1111/1365-2745.14116, 2023. a
Poyatos, R., Granda, V., Molowny-Horas, R., Mencuccini, M., Steppe, K., and Martínez-Vilalta, J.: SAPFLUXNET: towards a global database of sap flow measurements, Tree Physiol., 36, 1449–1455, https://doi.org/10.1093/treephys/tpw110, 2016. a, b
Poyatos, R., Granda, V., Flo, V., Molowny-Horas, R., Steppe, K., Mencuccini, M., and Martínez-Vilalta, J.: SAPFLUXNET: A global database of sap flow measurements, Zenodo [data set], https://doi.org/10.5281/zenodo.2530798, 2019. a
Poyatos, R., Granda, V., Flo, V., Adams, M. A., Adorján, B., Aguadé, D., Aidar, M. P. M., Allen, S., Alvarado-Barrientos, M. S., Anderson-Teixeira, K. J., Aparecido, L. M., Arain, M. A., Aranda, I., Asbjornsen, H., Baxter, R., Beamesderfer, E., Berry, Z. C., Berveiller, D., Blakely, B., Boggs, J., Bohrer, G., Bolstad, P. V., Bonal, D., Bracho, R., Brito, P., Brodeur, J., Casanoves, F., Chave, J., Chen, H., Cisneros, C., Clark, K., Cremonese, E., Dang, H., David, J. S., David, T. S., Delpierre, N., Desai, A. R., Do, F. C., Dohnal, M., Domec, J.-C., Dzikiti, S., Edgar, C., Eichstaedt, R., El-Madany, T. S., Elbers, J., Eller, C. B., Euskirchen, E. S., Ewers, B., Fonti, P., Forner, A., Forrester, D. I., Freitas, H. C., Galvagno, M., Garcia-Tejera, O., Ghimire, C. P., Gimeno, T. E., Grace, J., Granier, A., Griebel, A., Guangyu, Y., Gush, M. B., Hanson, P. J., Hasselquist, N. J., Heinrich, I., Hernandez-Santana, V., Herrmann, V., Hölttä, T., Holwerda, F., Irvine, J., Isarangkool Na Ayutthaya, S., Jarvis, P. G., Jochheim, H., Joly, C. A., Kaplick, J., Kim, H. S., Klemedtsson, L., Kropp, H., Lagergren, F., Lane, P., Lang, P., Lapenas, A., Lechuga, V., Lee, M., Leuschner, C., Limousin, J.-M., Linares, J. C., Linderson, M.-L., Lindroth, A., Llorens, P., López-Bernal, A., Loranty, M. M., Lüttschwager, D., Macinnis-Ng, C., Maréchaux, I., Martin, T. A., Matheny, A., McDowell, N., McMahon, S., Meir, P., Mészáros, I., Migliavacca, M., Mitchell, P., Mölder, M., Montagnani, L., Moore, G. W., Nakada, R., Niu, F., Nolan, R. H., Norby, R., Novick, K., Oberhuber, W., Obojes, N., Oishi, A. C., Oliveira, R. S., Oren, R., Ourcival, J.-M., Paljakka, T., Perez-Priego, O., Peri, P. L., Peters, R. L., Pfautsch, S., Pockman, W. T., Preisler, Y., Rascher, K., Robinson, G., Rocha, H., Rocheteau, A., Röll, A., Rosado, B. H. P., Rowland, L., Rubtsov, A. V., Sabaté, S., Salmon, Y., Salomón, R. L., Sánchez-Costa, E., Schäfer, K. V. R., Schuldt, B., Shashkin, A., Stahl, C., Stojanović, M., Suárez, J. C., Sun, G., Szatniewska, J., Tatarinov, F., Tesař, M., Thomas, F. M., Tor-ngern, P., Urban, J., Valladares, F., van der Tol, C., van Meerveld, I., Varlagin, A., Voigt, H., Warren, J., Werner, C., Werner, W., Wieser, G., Wingate, L., Wullschleger, S., Yi, K., Zweifel, R., Steppe, K., Mencuccini, M., and Martínez-Vilalta, J.: Global transpiration data from sap flow measurements: the SAPFLUXNET database, Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, 2021. a, b, c, d, e, f
Preisler, Y., Tatarinov, F., Grünzweig, J. M., and Yakir, D.: Seeking the “point of no return” in the sequence of events leading to mortality of mature trees, Plant Cell Environ., 44, 1315–1328, https://doi.org/10.1111/pce.13942, 2021. a, b, c, d
Prigent, C., Jimenez, C., Dinh, L. A., Frappart, F., Gentine, P., Wigneron, J.-P., and Munchak, J.: Diurnal and Seasonal Variations of Passive and Active Microwave Satellite Observations Over Tropical Forests, J. Geophys. Res.-Biogeo., 127, e2021JG006677, https://doi.org/10.1029/2021JG006677, 2022. a
Renninger, H. J., Stewart, L. F., and Rousseau, R. J.: Water Use, Efficiency, and Stomatal Sensitivity in Eastern Cottonwood and Hybrid Poplar Varietals on Contrasting Sites in the Southeastern United States, Front. Forest. Glob. Change, 4, https://doi.org/10.3389/ffgc.2021.704799, 2021. a
Rowland, L., da Costa, A. C. L., Galbraith, D. R., Oliveira, R. S., Binks, O. J., Oliveira, A. A. R., Pullen, A. M., Doughty, C. E., Metcalfe, D. B., Vasconcelos, S. S., Ferreira, L. V., Malhi, Y., Grace, J., Mencuccini, M., and Meir, P.: Death from drought in tropical forests is triggered by hydraulics not carbon starvation, Nature, 528, 119–122, https://doi.org/10.1038/nature15539, 2015. a
Ruehr, N. K., Gast, A., Weber, C., Daub, B., and Arneth, A.: Water Availability as Dominant Control of Heat Stress Responses in Two Contrasting Tree Species, Tree Physiol., 36, 164–178, https://doi.org/10.1093/treephys/tpv102, 2015. a
Ruehr, N. K., Grote, R., Mayr, S., and Arneth, A.: Beyond the Extreme: Recovery of Carbon and Water Relations in Woody Plants Following Heat and Drought Stress, Tree Physiol., 39, 1285–1299, https://doi.org/10.1093/treephys/tpz032, 2019. a
Ruffault, J., Limousin, J.-M., Pimont, F., Dupuy, J.-L., De Càceres, M., Cochard, H., Mouillot, F., Blackman, C. J., Torres-Ruiz, J. M., Parsons, R. A., Moreno, M., Delzon, S., Jansen, S., Olioso, A., Choat, B., and Martin-StPaul, N.: Plant hydraulic modelling of leaf and canopy fuel moisture content reveals increasing vulnerability of a Mediterranean forest to wildfires under extreme drought, New Phytol., 237, 1256–1269, https://doi.org/10.1111/nph.18614, 2023. a
Schackow, A. T.: A-sch-A/hysteresis_SF-VPD: v1.0.0 – Code for Schackow et al. (2026), Biogeosciences (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.19224230, 2026. a
Schneebeli, M., Wolf, S., Kunert, N., Eugster, W., and Mätzler, C.: Relating the X-band opacity of a tropical tree canopy to sapflow, rain interception and dew formation, Remote Sens. Environ., 115, 2116–2125, https://doi.org/10.1016/j.rse.2011.04.016, 2011. a
Schymanski, S. J., Or, D., and Zwieniecki, M.: Stomatal Control and Leaf Thermal and Hydraulic Capacitances under Rapid Environmental Fluctuations, PLOS ONE, 8, e54231, https://doi.org/10.1371/journal.pone.0054231, 2013. a
Seidl, R., Thom, D., Kautz, M., Martin-Benito, D., Peltoniemi, M., Vacchiano, G., Wild, J., Ascoli, D., Petr, M., Honkaniemi, J., Lexer, M. J., Trotsiuk, V., Mairota, P., Svoboda, M., Fabrika, M., Nagel, T. A., and Reyer, C. P. O.: Forest disturbances under climate change, Nat. Clim. Change, 7, 395–402, https://doi.org/10.1038/NCLIMATE3303, 2017. a
Seleiman, M. F., Al-Suhaibani, N., Ali, N., Akmal, M., Alotaibi, M., Refay, Y., Dindaroglu, T., Abdul-Wajid, H. H., and Battaglia, M. L.: Drought Stress Impacts on Plants and Different Approaches to Alleviate Its Adverse Effects, Plants, 10, 259, https://doi.org/10.3390/plants10020259, 2021. a
Spanner, G. C., Gimenez, B. O., Wright, C. L., Menezes, V. S., Newman, B. D., Collins, A. D., Jardine, K. J., Negrón-Juárez, R. I., Lima, A. J. N., Rodrigues, J. R., Chambers, J. Q., Higuchi, N., and Warren, J. M.: Dry Season Transpiration and Soil Water Dynamics in the Central Amazon, Front. Plant Sci., 13, 825097, https://doi.org/10.3389/fpls.2022.825097, 2022. a
Sperry, J. S. and Love, D. M.: What Plant Hydraulics Can Tell Us about Responses to Climate-Change Droughts, New Phytol., 207, 14–27, https://doi.org/10.1111/nph.13354, 2015. a
Steele-Dunne, S. C., Friesen, J. C., and van de Giesen, N.: Using Diurnal Variation in Backscatter to Detect Vegetation Water Stress, IEEE Trans. Geosci. Remote Sens., 50, 2618–2629, https://doi.org/10.1109/TGRS.2012.2194156, 2012. a
Steele-Dunne, S. C., Basto, A., de Zan, F., Dorigo, W., Lhermitte, S., Massari, C., Matar, J., Milodowski, D. T., Miralle, D., Monteith, A. R., Rodriguez Cassola, M., Taylor, C., Tebaldini, S., and Ulander, L. M. H.: SLAINTE: A SAR mission concept for sub-daily microwave remote sensing of vegetation, in: EUSAR 2024; 15th European Conference on Synthetic Aperture Radar, VDE Verlag GmbH, 870–872, ISBN 978-3-8007-6286-6 / ISSN 2197-4403, 2024. a
Suárez, J. C., Casanoves, F., Bieng, M. A. N., Melgarejo, L. M., Di Rienzo, J. A., and Armas, C.: Prediction Model for Sap Flow in Cacao Trees under Different Radiation Intensities in the Western Colombian Amazon, Sci. Rep., 11, 10512, https://doi.org/10.1038/s41598-021-89876-z, 2021. a
Tchebakova, N. M., Zyryanov, V. I., Zyryanova, O. A., Parfenova, E. I., Kajimoto, T., and Matsuura, Y.: A Comparative Study of Climatology, Energy and Mass Exchange in Two Forests on Contrasting Habitats in Central Siberia: Permafrost Larix gmelinii vs. Permafrost-Free Pinus sylvestris, Forests, 14, 346, https://doi.org/10.3390/f14020346, 2023. a, b
Tyree, M. T. and Ewers, F. W.: The hydraulic architecture of trees and other woody plants, New Phytol., 119, 345–360, https://doi.org/10.1111/j.1469-8137.1991.tb00035.x, 1991. a
Ulander, L. M. H. and Monteith, A. R.: BorealScat Final Report (Contract Change Notice 1), Tech. rep., ESA, https://doi.org/10.1109/EUSAR.2024.10659518, 2022. a
Ulander, L. M. H., Monteith, A. R., and Rönnfalk, M.: BorealScat Final Report, Tech. rep., ESA, https://doi.org/10.57780/esa-e071d3d, 2019. a
Urban, J., Ingwers, M., McGuire, M. A., and Teskey, R. O.: Stomatal Conductance Increases with Rising Temperature, Plant Signal. Behav., 12, e1356534, https://doi.org/10.1080/15592324.2017.1356534, 2017. a
Urban, J., Rubtsov, A. V., Urban, A. V., Shashkin, A. V., and Benkova, V. E.: Canopy transpiration of a Larix sibirica and Pinus sylvestris forest in Central Siberia, Agr. Forest Meteorol., 271, 64–72, https://doi.org/10.1016/j.agrformet.2019.02.038, 2019. a, b, c
Van Emmerik, T., Steele-Dunne, S. C., Hut, R., Gentine, P., Guerin, M., Oliveira, R. S., Wagner, J., Selker, J., and van de Giesen, N.: Measuring Tree Properties and Responses Using Low-Cost Accelerometers, Sensors, 17, 1098, https://doi.org/10.3390/s17051098, 2017. a
Vermunt, P. C., Khabbazan, S., Steele-Dunne, S. C., Judge, J., Monsivais-Huertero, A., Guerriero, L., and Liu, P.-W.: Response of Subdaily L-Band Backscatter to Internal and Surface Canopy Water Dynamics, IEEE Trans. Geosci. Remote Sens., 59, 7322–7337, https://doi.org/10.1109/TGRS.2020.3035881, 2021. a
Vermunt, P. C., Steele-Dunne, S. C., Khabbazan, S., Judge, J., and van de Giesen, N. C.: Extrapolating continuous vegetation water content to understand sub-daily backscatter variations, Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022, 2022. a
Vicente-Serrano, S. M., Miralles, D. G., McDowell, N., Brodribb, T., Domínguez-Castro, F., Leung, R., and Koppa, A.: The uncertain role of rising atmospheric CO2 on global plant transpiration, Earth-Sci. Rev., 230, 104055, https://doi.org/10.1016/j.earscirev.2022.104055, 2022a. a
Vicente-Serrano, S. M., Peña-Angulo, D., Beguería, S., Domínguez-Castro, F., Tomás-Burguera, M., Noguera, I., Gimeno-Sotelo, L., and El Kenawy, A.: Global drought trends and future projections, Philos. T. R. Soc. A, 380, 20210 285, https://doi.org/10.1098/rsta.2021.0285, 2022b. a
Wan, L., Zhang, Q., Cheng, L., Liu, Y., Qin, S., Xu, J., and Wang, Y.: What determines the time lags of sap flux with solar radiation and vapor pressure deficit?, Agr. Forest Meteorol., 333, 109414, https://doi.org/10.1016/j.agrformet.2023.109414, 2023. a, b
Wheeler, W. D., Black, B., and Bugbee, B.: Assessing water stress in a high-density apple orchard using trunk circumference variation, sap flow index and stem water potential, Front. Plant Sci., 14, 1214429, https://doi.org/10.3389/fpls.2023.1214429, 2023. a
Xu, S., McVicar, T. R., Li, L., Yu, Z., Jiang, P., Zhang, Y., Ban, Z., Xing, W., Dong, N., Zhang, H., and Zhang, M.: Globally assessing the hysteresis between sub-diurnal actual evaporation and vapor pressure deficit at the ecosystem scale: Patterns and mechanisms, Agr. Forest Meteorol., 323, 109085, https://doi.org/10.1016/j.agrformet.2022.109085, 2022. a
Zotta, R.-M., Moesinger, L., van der Schalie, R., Vreugdenhil, M., Preimesberger, W., Frederikse, T., de Jeu, R., and Dorigo, W.: VODCA v2: multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring, Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, 2024. a
Zuecco, G., Penna, D., Borga, M., and van Meerveld, H. J.: A versatile index to characterize hysteresis between hydrological variables at the runoff event timescale, Hydrol. Process., 30, 1449–1466, https://doi.org/10.1002/hyp.10681, 2016. a
Short summary
Plants regulate how much water they lose and how much carbon they take in, but rising heat and dryness make this balance harder. We studied how water movement inside plant stems changes during the day and relates to dryness in the air and soil. By analyzing these daily patterns, we identified signals of stress that could be tracked not only with sensors in plants but also from satellites, offering new ways to monitor global vegetation health.
Plants regulate how much water they lose and how much carbon they take in, but rising heat and...
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