Articles | Volume 17, issue 9
https://doi.org/10.5194/bg-17-2397-2020
© Author(s) 2020. 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-17-2397-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
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05 May 2020
Research article | Highlight paper |
| 05 May 2020
| 05 May 2020
Summarizing the state of the terrestrial biosphere in few dimensions
Max Planck Institute for Biogeochemistry, Department for Biogeochemical Integration, 07745 Jena, Germany
Image Processing Laboratory, Universitat de València, 46980 Paterna (València), Spain
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
Remote Sensing Centre for Earth System Research, Leipzig University, 04103 Leipzig, Germany
Gustau Camps-Valls
Image Processing Laboratory, Universitat de València, 46980 Paterna (València), Spain
Markus Reichstein
Max Planck Institute for Biogeochemistry, Department for Biogeochemical Integration, 07745 Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
Miguel D. Mahecha
Max Planck Institute for Biogeochemistry, Department for Biogeochemical Integration, 07745 Jena, Germany
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
Remote Sensing Centre for Earth System Research, Leipzig University, 04103 Leipzig, Germany
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Richard Nair, Yunpeng Luo, Tarek El-Madany, Victor Rolo, Javier Pacheco-Labrador, Silvia Caldararu, Kendalynn A. Morris, Marion Schrumpf, Arnaud Carrara, Gerardo Moreno, Markus Reichstein, and Mirco Migliavacca
EGUsphere, https://doi.org/10.5194/egusphere-2023-2434, https://doi.org/10.5194/egusphere-2023-2434, 2023
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We studied a Mediterranean ecosystem to understand carbon uptake efficiency and its controls. These ecosystems face potential nitrogen-phosphorus imbalances due to pollution. Analysing six years of carbon data, we assessed controls at different timeframes. This is crucial for predicting such vulnerable regions. Our findings revealed N limitation on C uptake, not N:P imbalance, and strong influence of water availability. whether drought or wetness promoted net C uptake depended on timescale.
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.
Hoontaek Lee, Martin Jung, Nuno Carvalhais, Tina Trautmann, Basil Kraft, Markus Reichstein, Matthias Forkel, and Sujan Koirala
Hydrol. Earth Syst. Sci., 27, 1531–1563, https://doi.org/10.5194/hess-27-1531-2023, https://doi.org/10.5194/hess-27-1531-2023, 2023
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A deep frost occurred in early April 2021, inducing severe damages in grapevine and fruit trees in France. We found that such extreme frosts occurring after the start of the growing season such as those of April 2021 are currently about 2°C colder [0.5 °C to 3.3 °C] in observations than in preindustrial climate. This observed intensification of growing-period frosts is attributable, at least in part, to human-caused climate change, making the 2021 event 50 % more likely [10 %–110 %].
Sinikka Jasmin Paulus, Tarek Sebastian El-Madany, René Orth, Anke Hildebrandt, Thomas Wutzler, Arnaud Carrara, Gerardo Moreno, Oscar Perez-Priego, Olaf Kolle, Markus Reichstein, and Mirco Migliavacca
Hydrol. Earth Syst. Sci., 26, 6263–6287, https://doi.org/10.5194/hess-26-6263-2022, https://doi.org/10.5194/hess-26-6263-2022, 2022
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In this study, we analyze small inputs of water to ecosystems such as fog, dew, and adsorption of vapor. To measure them, we use a scaling system and later test our attribution of different water fluxes to weight changes. We found that they occur frequently during 1 year in a dry summer ecosystem. In each season, a different flux seems dominant, but they all mainly occur during the night. Therefore, they could be important for the biosphere because rain is unevenly distributed over the year.
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.
D. Montero, C. Aybar, M. D. Mahecha, and S. Wieneke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 301–306, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022, 2022
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
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The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Basil Kraft, Martin Jung, Marco Körner, Sujan Koirala, and Markus Reichstein
Hydrol. Earth Syst. Sci., 26, 1579–1614, https://doi.org/10.5194/hess-26-1579-2022, https://doi.org/10.5194/hess-26-1579-2022, 2022
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We present a physics-aware machine learning model of the global hydrological cycle. As the model uses neural networks under the hood, the simulations of the water cycle are learned from data, and yet they are informed and constrained by physical knowledge. The simulated patterns lie within the range of existing hydrological models and are plausible. The hybrid modeling approach has the potential to tackle key environmental questions from a novel perspective.
J. Pacheco-Labrador, U. Weber, X. Ma, M. D. Mahecha, N. Carvalhais, C. Wirth, A. Huth, F. J. Bohn, G. Kraemer, U. Heiden, FunDivEUROPE members, and M. Migliavacca
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1-W1-2021, 49–55, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, 2022
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.
Christopher Krich, Mirco Migliavacca, Diego G. Miralles, Guido Kraemer, Tarek S. El-Madany, Markus Reichstein, Jakob Runge, and Miguel D. Mahecha
Biogeosciences, 18, 2379–2404, https://doi.org/10.5194/bg-18-2379-2021, https://doi.org/10.5194/bg-18-2379-2021, 2021
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Ecosystems and the atmosphere interact with each other. These interactions determine e.g. the water and carbon fluxes and thus are crucial to understand climate change effects. We analysed the interactions for many ecosystems across the globe, showing that very different ecosystems can have similar interactions with the atmosphere. Meteorological conditions seem to be the strongest interaction-shaping factor. This means that common principles can be identified to describe ecosystem behaviour.
Milan Flach, Alexander Brenning, Fabian Gans, Markus Reichstein, Sebastian Sippel, and Miguel D. Mahecha
Biogeosciences, 18, 39–53, https://doi.org/10.5194/bg-18-39-2021, https://doi.org/10.5194/bg-18-39-2021, 2021
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Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. We study the impact of droughts and heatwaves on the uptake of CO2 of different vegetation types at the global scale. We find that agricultural areas are generally strongly affected. Forests instead are not particularly sensitive to the events under scrutiny. This implies different water management strategies of forests but also a lack of sensitivity to remote-sensing-derived vegetation activity.
Naixin Fan, Sujan Koirala, Markus Reichstein, Martin Thurner, Valerio Avitabile, Maurizio Santoro, Bernhard Ahrens, Ulrich Weber, and Nuno Carvalhais
Earth Syst. Sci. Data, 12, 2517–2536, https://doi.org/10.5194/essd-12-2517-2020, https://doi.org/10.5194/essd-12-2517-2020, 2020
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The turnover time of terrestrial carbon (τ) controls the global carbon cycle–climate feedback. In this study, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback.
B. Kraft, M. Jung, M. Körner, and M. Reichstein
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1537–1544, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1537-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1537-2020, 2020
Daniel E. Pabon-Moreno, Talie Musavi, Mirco Migliavacca, Markus Reichstein, Christine Römermann, and Miguel D. Mahecha
Biogeosciences, 17, 3991–4006, https://doi.org/10.5194/bg-17-3991-2020, https://doi.org/10.5194/bg-17-3991-2020, 2020
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Ecosystem CO2 uptake changes in time depending on climate conditions. In this study, we analyze how different climate variables affect the timing when CO2 uptake is at a maximum (DOYGPPmax). We found that the joint effects of radiation, temperature, and vapor pressure deficit are the most relevant controlling factors of DOYGPPmax and that if they increase, DOYGPPmax will happen earlier. These results help us to better understand how CO2 uptake could be affected by climate change.
R. Sauzède, J. E. Johnson, H. Claustre, G. Camps-Valls, and A. B. Ruescas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 949–956, https://doi.org/10.5194/isprs-annals-V-2-2020-949-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-949-2020, 2020
René Orth, Georgia Destouni, Martin Jung, and Markus Reichstein
Biogeosciences, 17, 2647–2656, https://doi.org/10.5194/bg-17-2647-2020, https://doi.org/10.5194/bg-17-2647-2020, 2020
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Drought duration is a key control of the large-scale biospheric drought response.
Thereby, the vegetation responds linearly to drought duration at large spatial scales.
The slope of the linear relationship between the vegetation drought response and drought duration is steeper in drier climates.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Christopher Krich, Jakob Runge, Diego G. Miralles, Mirco Migliavacca, Oscar Perez-Priego, Tarek El-Madany, Arnaud Carrara, and Miguel D. Mahecha
Biogeosciences, 17, 1033–1061, https://doi.org/10.5194/bg-17-1033-2020, https://doi.org/10.5194/bg-17-1033-2020, 2020
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Causal inference promises new insight into biosphere–atmosphere interactions using time series only. To understand the behaviour of a specific method on such data, we used artificial and observation-based data. The observed structures are very interpretable and reveal certain ecosystem-specific behaviour, as only a few relevant links remain, in contrast to pure correlation techniques. Thus, causal inference allows to us gain well-constrained insights into processes and interactions.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
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The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020, https://doi.org/10.5194/bg-17-945-2020, 2020
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Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems. It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered. This scale dependency should be considered for modeling land–atmosphere interactions.
Javier Pacheco-Labrador, Tarek S. El-Madany, M. Pilar Martin, Rosario Gonzalez-Cascon, Arnaud Carrara, Gerardo Moreno, Oscar Perez-Priego, Tiana Hammer, Heiko Moossen, Kathrin Henkel, Olaf Kolle, David Martini, Vicente Burchard, Christiaan van der Tol, Karl Segl, Markus Reichstein, and Mirco Migliavacca
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-501, https://doi.org/10.5194/bg-2019-501, 2020
Revised manuscript not accepted
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The new generation of sensors on-board satellites have the potential to provide richer information about the function of vegetation than before. This information, nowadays missing, is fundamental to improve our understanding and prediction of carbon and water cycles, and therefore to anticipate effects and responses to Climate Change. In this manuscript we propose a method to exploit the data provided by these satellites to successfully obtain this information key to face Climate Change.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
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Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Sven Boese, Martin Jung, Nuno Carvalhais, Adriaan J. Teuling, and Markus Reichstein
Biogeosciences, 16, 2557–2572, https://doi.org/10.5194/bg-16-2557-2019, https://doi.org/10.5194/bg-16-2557-2019, 2019
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This study examines how limited water availability during droughts affects water-use efficiency. This metric describes how much carbon an ecosystem can assimilate for each unit of water lost by transpiration. We test how well different water-use efficiency models can capture the dynamics of transpiration decrease due to increased soil-water limitation. Accounting for the interacting effects of radiation and water limitation is necessary to accurately predict transpiration during these periods.
Richard K. F. Nair, Kendalynn A. Morris, Martin Hertel, Yunpeng Luo, Gerardo Moreno, Markus Reichstein, Marion Schrumpf, and Mirco Migliavacca
Biogeosciences, 16, 1883–1901, https://doi.org/10.5194/bg-16-1883-2019, https://doi.org/10.5194/bg-16-1883-2019, 2019
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We investigated how nutrient availability affects seasonal timing of root growth and death in a Spanish savanna, adapted to a long summer drought. We found that nitrogen (N) additions led to more root biomass but number of roots was higher with N and phosphorus together. These effects were strongly affected by the time of year. In autumn root growth occurred after leaf production. This has implications for how we understand biomass production and carbon uptake in these systems.
Xiaolu Tang, Nuno Carvalhais, Catarina Moura, Bernhard Ahrens, Sujan Koirala, Shaohui Fan, Fengying Guan, Wenjie Zhang, Sicong Gao, Vincenzo Magliulo, Pauline Buysse, Shibin Liu, Guo Chen, Wunian Yang, Zhen Yu, Jingjing Liang, Leilei Shi, Shenyan Pu, and Markus Reichstein
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-37, https://doi.org/10.5194/bg-2019-37, 2019
Preprint withdrawn
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Vegetation CUE is a key measure of carbon transfer from the atmosphere to terrestrial biomass. This study modelled global CUE with published observations using random forest. CUE varied with ecosystem types and spatially decreased with latitude, challenging the previous conclusion that CUE was independent of environmental controls. Our results emphasize a better understanding of environmental controls on CUE to reduce uncertainties in prognostic land-process model simulations.
Milan Flach, Sebastian Sippel, Fabian Gans, Ana Bastos, Alexander Brenning, Markus Reichstein, and Miguel D. Mahecha
Biogeosciences, 15, 6067–6085, https://doi.org/10.5194/bg-15-6067-2018, https://doi.org/10.5194/bg-15-6067-2018, 2018
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Northern forests enhanced their productivity during and before the 2010 Russian mega heatwave. We scrutinize this issue with a novel type of multivariate extreme event detection approach. Forests compensate for 54 % of the carbon losses in agricultural ecosystems due to vulnerable conditions in spring and better water management in summer. The findings highlight the importance of forests in mitigating climate change, while not alleviating the consequences of extreme events for food security.
Thomas Wutzler, Antje Lucas-Moffat, Mirco Migliavacca, Jürgen Knauer, Kerstin Sickel, Ladislav Šigut, Olaf Menzer, and Markus Reichstein
Biogeosciences, 15, 5015–5030, https://doi.org/10.5194/bg-15-5015-2018, https://doi.org/10.5194/bg-15-5015-2018, 2018
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Net fluxes of carbon dioxide at the ecosystem level measured by eddy covariance are a main source for understanding biosphere–atmosphere interactions. However, there is a need for more usable and extensible tools for post-processing steps of the half-hourly flux data. Therefore, we developed the REddyProc package, providing data filtering, gap filling, and flux partitioning. The extensible functions are compatible with state-of-the-art tools but allow easier integration in extended analysis.
Paul Bodesheim, Martin Jung, Fabian Gans, Miguel D. Mahecha, and Markus Reichstein
Earth Syst. Sci. Data, 10, 1327–1365, https://doi.org/10.5194/essd-10-1327-2018, https://doi.org/10.5194/essd-10-1327-2018, 2018
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We provide continuous half-hourly carbon and energy fluxes for 2001 to 2014 at 0.5° spatial resolution, which allows for analyzing diurnal cycles globally. The data set contains four fluxes: gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LE), and sensible heat (H). In addition, we provide a derived product that only contains monthly average diurnal cycles but which also enables us to study the important characteristics of subdaily patterns at a global scale.
Jacob A. Nelson, Nuno Carvalhais, Mirco Migliavacca, Markus Reichstein, and Martin Jung
Biogeosciences, 15, 2433–2447, https://doi.org/10.5194/bg-15-2433-2018, https://doi.org/10.5194/bg-15-2433-2018, 2018
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Plants have typical daily carbon uptake and water loss cycles. However, these cycles may change under periods of duress, such as water limitation. Here we identify two types of patterns in response to water limitations: a tendency to lose more water in the morning than afternoon and a decoupling of the carbon and water cycles. The findings show differences in responses by trees and grasses and suggest that morning shifts may be more efficient at gaining carbon per unit water used.
Jannis von Buttlar, Jakob Zscheischler, Anja Rammig, Sebastian Sippel, Markus Reichstein, Alexander Knohl, Martin Jung, Olaf Menzer, M. Altaf Arain, Nina Buchmann, Alessandro Cescatti, Damiano Gianelle, Gerard Kiely, Beverly E. Law, Vincenzo Magliulo, Hank Margolis, Harry McCaughey, Lutz Merbold, Mirco Migliavacca, Leonardo Montagnani, Walter Oechel, Marian Pavelka, Matthias Peichl, Serge Rambal, Antonio Raschi, Russell L. Scott, Francesco P. Vaccari, Eva van Gorsel, Andrej Varlagin, Georg Wohlfahrt, and Miguel D. Mahecha
Biogeosciences, 15, 1293–1318, https://doi.org/10.5194/bg-15-1293-2018, https://doi.org/10.5194/bg-15-1293-2018, 2018
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Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity (GPP) and ecosystem respiration globally across a wide range of ecosystems. We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Iulia Ilie, Peter Dittrich, Nuno Carvalhais, Martin Jung, Andreas Heinemeyer, Mirco Migliavacca, James I. L. Morison, Sebastian Sippel, Jens-Arne Subke, Matthew Wilkinson, and Miguel D. Mahecha
Geosci. Model Dev., 10, 3519–3545, https://doi.org/10.5194/gmd-10-3519-2017, https://doi.org/10.5194/gmd-10-3519-2017, 2017
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Accurate representation of land-atmosphere carbon fluxes is essential for future climate projections, although some of the responses of CO2 fluxes to climate often remain uncertain. The increase in available data allows for new approaches in their modelling. We automatically developed models for ecosystem and soil carbon respiration using a machine learning approach. When compared with established respiration models, we found that they are better in prediction as well as offering new insights.
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
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We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
Jakob Zscheischler, Miguel D. Mahecha, Valerio Avitabile, Leonardo Calle, Nuno Carvalhais, Philippe Ciais, Fabian Gans, Nicolas Gruber, Jens Hartmann, Martin Herold, Kazuhito Ichii, Martin Jung, Peter Landschützer, Goulven G. Laruelle, Ronny Lauerwald, Dario Papale, Philippe Peylin, Benjamin Poulter, Deepak Ray, Pierre Regnier, Christian Rödenbeck, Rosa M. Roman-Cuesta, Christopher Schwalm, Gianluca Tramontana, Alexandra Tyukavina, Riccardo Valentini, Guido van der Werf, Tristram O. West, Julie E. Wolf, and Markus Reichstein
Biogeosciences, 14, 3685–3703, https://doi.org/10.5194/bg-14-3685-2017, https://doi.org/10.5194/bg-14-3685-2017, 2017
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Here we synthesize a wide range of global spatiotemporal observational data on carbon exchanges between the Earth surface and the atmosphere. A key challenge was to consistently combining observational products of terrestrial and aquatic surfaces. Our primary goal is to identify today’s key uncertainties and observational shortcomings that would need to be addressed in future measurement campaigns or expansions of in situ observatories.
Milan Flach, Fabian Gans, Alexander Brenning, Joachim Denzler, Markus Reichstein, Erik Rodner, Sebastian Bathiany, Paul Bodesheim, Yanira Guanche, Sebastian Sippel, and Miguel D. Mahecha
Earth Syst. Dynam., 8, 677–696, https://doi.org/10.5194/esd-8-677-2017, https://doi.org/10.5194/esd-8-677-2017, 2017
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Anomalies and extremes are often detected using univariate peak-over-threshold approaches in the geoscience community. The Earth system is highly multivariate. We compare eight multivariate anomaly detection algorithms and combinations of data preprocessing. We identify three anomaly detection algorithms that outperform univariate extreme event detection approaches. The workflows have the potential to reveal novelties in data. Remarks on their application to real Earth observations are provided.
Sven Boese, Martin Jung, Nuno Carvalhais, and Markus Reichstein
Biogeosciences, 14, 3015–3026, https://doi.org/10.5194/bg-14-3015-2017, https://doi.org/10.5194/bg-14-3015-2017, 2017
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For plants, the ratio of carbon uptake to water loss by transpiration is usually thought to depend on characteristic properties (their adaption to water scarcity) and the dryness of the atmosphere at any given moment. We show that, on the ecosystem scale, radiation has an independent effect on this ratio that had not been previously considered. When including this variable in models, predictions of transpiration improve considerably.
Sebastian Sippel, Jakob Zscheischler, Miguel D. Mahecha, Rene Orth, Markus Reichstein, Martha Vogel, and Sonia I. Seneviratne
Earth Syst. Dynam., 8, 387–403, https://doi.org/10.5194/esd-8-387-2017, https://doi.org/10.5194/esd-8-387-2017, 2017
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The present study (1) evaluates land–atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and (2) refines the model ensemble using a land–atmosphere coupling diagnostic as constraint. Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season
moisture-limitedclimate regimes in midlatitude regions. This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble.
Sebastian Sippel, Jakob Zscheischler, Martin Heimann, Holger Lange, Miguel D. Mahecha, Geert Jan van Oldenborgh, Friederike E. L. Otto, and Markus Reichstein
Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, https://doi.org/10.5194/hess-21-441-2017, 2017
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The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Gianluca Tramontana, Martin Jung, Christopher R. Schwalm, Kazuhito Ichii, Gustau Camps-Valls, Botond Ráduly, Markus Reichstein, M. Altaf Arain, Alessandro Cescatti, Gerard Kiely, Lutz Merbold, Penelope Serrano-Ortiz, Sven Sickert, Sebastian Wolf, and Dario Papale
Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016, https://doi.org/10.5194/bg-13-4291-2016, 2016
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We have evaluated 11 machine learning (ML) methods and two complementary drivers' setup to estimate the carbon dioxide (CO2) and energy exchanges between land ecosystems and atmosphere. Obtained results have shown high consistency among ML and high capability to estimate the spatial and seasonal variability of the target fluxes. The results were good for all the ecosystems, with limitations to the ones in the extreme environments (cold, hot) or less represented in the training data (tropics).
S. Sippel, F. E. L. Otto, M. Forkel, M. R. Allen, B. P. Guillod, M. Heimann, M. Reichstein, S. I. Seneviratne, K. Thonicke, and M. D. Mahecha
Earth Syst. Dynam., 7, 71–88, https://doi.org/10.5194/esd-7-71-2016, https://doi.org/10.5194/esd-7-71-2016, 2016
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We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
O. Perez-Priego, J. Guan, M. Rossini, F. Fava, T. Wutzler, G. Moreno, N. Carvalhais, A. Carrara, O. Kolle, T. Julitta, M. Schrumpf, M. Reichstein, and M. Migliavacca
Biogeosciences, 12, 6351–6367, https://doi.org/10.5194/bg-12-6351-2015, https://doi.org/10.5194/bg-12-6351-2015, 2015
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Sun-induced chlorophyll fluorescence and photochemical reflectance index revealed controls of climate and nutrient availability on photosynthesis (gross primary production, GPP). Meteo-driven models (MMs) were unable to describe nutrient-induced effects on GPP. Important implications can be derived from these results, and uncertainties in the prediction of global GPP still remain when MMs do not account for plant nutrient availability.
S. Hashimoto, N. Carvalhais, A. Ito, M. Migliavacca, K. Nishina, and M. Reichstein
Biogeosciences, 12, 4121–4132, https://doi.org/10.5194/bg-12-4121-2015, https://doi.org/10.5194/bg-12-4121-2015, 2015
A. Rammig, M. Wiedermann, J. F. Donges, F. Babst, W. von Bloh, D. Frank, K. Thonicke, and M. D. Mahecha
Biogeosciences, 12, 373–385, https://doi.org/10.5194/bg-12-373-2015, https://doi.org/10.5194/bg-12-373-2015, 2015
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
X. Wu, F. Babst, P. Ciais, D. Frank, M. Reichstein, M. Wattenbach, C. Zang, and M. D. Mahecha
Biogeosciences, 11, 3057–3068, https://doi.org/10.5194/bg-11-3057-2014, https://doi.org/10.5194/bg-11-3057-2014, 2014
J. Zscheischler, M. Reichstein, S. Harmeling, A. Rammig, E. Tomelleri, and M. D. Mahecha
Biogeosciences, 11, 2909–2924, https://doi.org/10.5194/bg-11-2909-2014, https://doi.org/10.5194/bg-11-2909-2014, 2014
B. Ahrens, M. Reichstein, W. Borken, J. Muhr, S. E. Trumbore, and T. Wutzler
Biogeosciences, 11, 2147–2168, https://doi.org/10.5194/bg-11-2147-2014, https://doi.org/10.5194/bg-11-2147-2014, 2014
J. v. Buttlar, J. Zscheischler, and M. D. Mahecha
Nonlin. Processes Geophys., 21, 203–215, https://doi.org/10.5194/npg-21-203-2014, https://doi.org/10.5194/npg-21-203-2014, 2014
B. Badawy, C. Rödenbeck, M. Reichstein, N. Carvalhais, and M. Heimann
Biogeosciences, 10, 6485–6508, https://doi.org/10.5194/bg-10-6485-2013, https://doi.org/10.5194/bg-10-6485-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
M. C. Braakhekke, T. Wutzler, C. Beer, J. Kattge, M. Schrumpf, B. Ahrens, I. Schöning, M. R. Hoosbeek, B. Kruijt, P. Kabat, and M. Reichstein
Biogeosciences, 10, 399–420, https://doi.org/10.5194/bg-10-399-2013, https://doi.org/10.5194/bg-10-399-2013, 2013
G. Lasslop, M. Migliavacca, G. Bohrer, M. Reichstein, M. Bahn, A. Ibrom, C. Jacobs, P. Kolari, D. Papale, T. Vesala, G. Wohlfahrt, and A. Cescatti
Biogeosciences, 9, 5243–5259, https://doi.org/10.5194/bg-9-5243-2012, https://doi.org/10.5194/bg-9-5243-2012, 2012
Related subject area
Biogeochemistry: Land
Seasonality and synchrony of photosynthesis in African forests inferred from spaceborne chlorophyll fluorescence and vegetation indices
Altitudinal distribution of soil organic and inorganic carbon in a dry alpine rangeland of northern Qinghai-Tibetan Plateau
Precipitation–fire functional interactions control biomass stocks and carbon exchanges across the world's largest savanna
Nitrogen concentrations in boreal and temperate tree tissues vary with tree age/size, growth rate, and climate
Burn severity and vegetation type control phosphorus concentration, molecular composition, and mobilization
Fertilization turns a rubber plantation from sink to methane source
Comparison of shortwave radiation dynamics between boreal forest and open peatland pairs in southern and northern Finland
Cropland expansion drives vegetation greenness decline in Southeast Asia
How to measure the efficiency of bioenergy crops compared to forestation
On the added value of sequential deep learning for upscaling evapotranspiration
Annual net CO2 fluxes from drained organic soils used for agriculture in the hemiboreal region of Europe
Implications of climate and litter quality for simulations of litterbag decomposition at high latitudes
Soil carbon-concentration and carbon-climate feedbacks in CMIP6 Earth system models
Monitoring the impact of forest changes on carbon uptake with solar-induced fluorescence measurements from GOME-2A and TROPOMI for an Australian and Chinese case study
Technical note: Flagging inconsistencies in flux tower data
Uncertainty in Amazon vegetation productivity in CMIP6 projections driven by surface energy fluxes
Relevance of near-surface soil moisture vs. terrestrial water storage for global vegetation functioning
High-resolution spatial patterns and drivers of terrestrial ecosystem carbon dioxide, methane, and nitrous oxide fluxes in the tundra
Long-term additions of ammonium nitrate to montane forest ecosystems may cause limited soil acidification, even in the presence of soil carbonate
Leaf carbon and nitrogen stoichiometric variation along environmental gradients
Gross primary productivity and the predictability of CO2: more uncertainty in what we predict than how well we predict it
Scale variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using model–data fusion
Seasonal controls override forest harvesting effects on the composition of dissolved organic matter mobilized from boreal forest soil organic horizons
Carbon cycle extremes accelerate weakening of the land carbon sink in the late 21st century
Estimating oil-palm Si storage, Si return to soils, and Si losses through harvest in smallholder oil-palm plantations of Sumatra, Indonesia
Assessing the sensitivity of multi-frequency passive microwave vegetation optical depth to vegetation properties
Seasonal variation of mercury concentration of ancient olive groves of Lebanon
Soil organic matter diagenetic state informs boreal forest ecosystem feedbacks to climate change
Upscaling dryland carbon and water fluxes with artificial neural networks of optical, thermal, and microwave satellite remote sensing
Sun-induced fluorescence as a proxy for primary productivity across vegetation types and climates
Technical note: A view from space on global flux towers by MODIS and Landsat: the FluxnetEO data set
Changing sub-Arctic tundra vegetation upon permafrost degradation: impact on foliar mineral element cycling
Land Management Contributes significantly to observed Vegetation Browning in Syria during 2001–2018
MODIS Vegetation Continuous Fields tree cover needs calibrating in tropical savannas
Assessing the representation of the Australian carbon cycle in global vegetation models
Assessing the response of soil carbon in Australia to changing inputs and climate using a consistent modelling framework
Reviews and syntheses: Ongoing and emerging opportunities to improve environmental science using observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellites
First pan-Arctic assessment of dissolved organic carbon in lakes of the permafrost region
The impact of wildfire on biogeochemical fluxes and water quality in boreal catchments
Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño
Subalpine grassland productivity increased with warmer and drier conditions, but not with higher N deposition, in an altitudinal transplantation experiment
Reviews and syntheses: Impacts of plant-silica–herbivore interactions on terrestrial biogeochemical cycling
Implementation of nitrogen cycle in the CLASSIC land model
Combined effects of ozone and drought stress on the emission of biogenic volatile organic compounds from Quercus robur L.
A bottom-up quantification of foliar mercury uptake fluxes across Europe
Lagged effects regulate the inter-annual variability of the tropical carbon balance
Spatial variations in terrestrial net ecosystem productivity and its local indicators
Nitrogen cycling in CMIP6 land surface models: progress and limitations
Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest
Sensitivity of 21st century simulated ecosystem indicators to model parameters, prescribed climate drivers, RCP scenarios and forest management actions for two Finnish boreal forest sites
Russell Doughty, Michael C. Wimberly, Dan Wanyama, Helene Peiro, Nicholas Parazoo, Sean Crowell, and Moses Azong Cho
Biogeosciences, 22, 1985–2004, https://doi.org/10.5194/bg-22-1985-2025, https://doi.org/10.5194/bg-22-1985-2025, 2025
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We find West African solar-induced fluorescence (SIF) increases during the dry season and peaks before precipitation, similar to the Amazon. In central Africa, a continental-scale bimodal SIF seasonality appears; its minimum aligns with precipitation, but its maximum seems less environmentally driven. Notably, differences between SIF and vegetation index (VI) seasonality indicate VI-based photosynthesis estimates may be inaccurate.
Qinglin Liu, Ailin Zhang, Xiangyi Li, Jinfei Yin, Yuxue Zhang, Osbert Jianxin Sun, and Yong Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1269, https://doi.org/10.5194/egusphere-2025-1269, 2025
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The arid region of the plateau is a fragile ecosystem sensitive to environmental change. Changes in the soil carbon pool in this ecosystem will affect the terrestrial carbon cycle. The soil carbon pool in this region is mainly composed of soil inorganic carbon, and the response to environmental changes is more obvious. At the same time, the impact of environment on vegetation is also an important part of the carbon cycle of terrestrial organisms.
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.
Martin Thurner, Kailiang Yu, Stefano Manzoni, Anatoly Prokushkin, Melanie A. Thurner, Zhiqiang Wang, and Thomas Hickler
Biogeosciences, 22, 1475–1493, https://doi.org/10.5194/bg-22-1475-2025, https://doi.org/10.5194/bg-22-1475-2025, 2025
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Nitrogen concentrations in tree tissues (leaves, branches, stems, and roots) are related to photosynthesis, growth, and respiration and thus to vegetation carbon uptake. Our novel database allows us to identify the controls of tree tissue nitrogen concentrations in boreal and temperate forests, such as tree age/size, species, and climate. Changes therein will affect tissue nitrogen concentrations and thus also vegetation carbon uptake.
Morgan E. Barnes, Jesse Alan Roebuck Jr., Samantha Grieger, Paul J. Aronstein, Vanessa A. Garayburu-Caruso, Kathleen Munson, Robert P. Young, Kevin D. Bladon, John D. Bailey, Emily B. Graham, Lupita Renteria, Peggy A. O'Day, Timothy D. Scheibe, and Allison N. Myers-Pigg
EGUsphere, https://doi.org/10.5194/egusphere-2025-21, https://doi.org/10.5194/egusphere-2025-21, 2025
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Wildfires impact nutrient cycles on land and in water. We used burning experiments to understand the types of phosphorous (P), an essential nutrient, that might be released to the environment after different types of fires. We found that the amount of P moving through the environment post-fire is dependent on the type of vegetation and degree of burning which may influence when and where this material is processed or stored.
Daniel Epron, Rawiwan Chotiphan, Zixiao Wang, Ornuma Duangngam, Makoto Shibata, Sumonta Kumar Paul, Takumi Mochidome, Jate Sathornkich, Wakana A. Azuma, Jun Murase, Yann Nouvellon, Poonpipope Kasemsap, and Kannika Sajjaphan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2, https://doi.org/10.5194/egusphere-2025-2, 2025
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The rapid expansion of rubber cultivation constitutes a significant land-use change in Southeast Asia. Despite fertilization been a common practice in rubber plantations, its impact on soil methane (CH4) dynamics remained poorly understood. Our study demonstrates that fertilization not only reduces soil CH4 consumption but also increases CH4 production, transforming rubber plantations from a net CH4 sink into a source. Implementing rational fertilization could enhance atmospheric CH4 removal.
Otso Peräkylä, Erkka Rinne, Ekaterina Ezhova, Anna Lintunen, Annalea Lohila, Juho Aalto, Mika Aurela, Pasi Kolari, and Markku Kulmala
Biogeosciences, 22, 153–179, https://doi.org/10.5194/bg-22-153-2025, https://doi.org/10.5194/bg-22-153-2025, 2025
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Forests are seen as good for climate. Yet, in areas with snow, trees break up the white snow surface and absorb more sunlight than open areas. This has a warming effect, negating some of the climate benefit of trees. We studied two site pairs in Finland, both with an open peatland and a forest. We found that the later the snow melts, the more extra energy the forest absorbs as compared to the peatland. This has implications for the future, as snow cover duration is affected by global warming.
Ruiying Zhao, Xiangzhong Luo, Yuheng Yang, Luri Nurlaila Syahid, Chi Chen, and Janice Ser Huay Lee
Biogeosciences, 21, 5393–5406, https://doi.org/10.5194/bg-21-5393-2024, https://doi.org/10.5194/bg-21-5393-2024, 2024
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Southeast Asia has been a global hot spot of land-use change over the past 50 years. Meanwhile, it also hosts some of the most carbon-dense and diverse ecosystems in the world. Here, we explore the impact of land-use change, along with other environmental factors, on the ecosystem in Southeast Asia. We find that elevated CO2 imposed a positive impact on vegetation greenness, but the positive impact was largely offset by intensive land-use changes in the region, particularly cropland expansion.
Sabine Egerer, Stefanie Falk, Dorothea Mayer, Tobias Nützel, Wolfgang A. Obermeier, and Julia Pongratz
Biogeosciences, 21, 5005–5025, https://doi.org/10.5194/bg-21-5005-2024, https://doi.org/10.5194/bg-21-5005-2024, 2024
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Using a state-of-the-art land model, we find that bioenergy plants can store carbon more efficiently than forests over long periods in the soil, in geological reservoirs, or by substituting fossil-fuel-based energy. Planting forests is more suitable for reaching climate targets by 2050. The carbon removal potential depends also on local environmental conditions. These considerations have important implications for climate policy, spatial planning, nature conservation, and agriculture.
Basil Kraft, Jacob A. Nelson, Sophia Walther, Fabian Gans, Ulrich Weber, Gregory Duveiller, Markus Reichstein, Weijie Zhang, Marc Rußwurm, Devis Tuia, Marco Körner, Zayd Mahmoud Hamdi, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2024-2896, https://doi.org/10.5194/egusphere-2024-2896, 2024
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Global evapotranspiration (ET) can be estimated using machine learning (ML) models optimized on local data and applied to global data. This study explores whether sequential neural networks, which consider past data, perform better than models that do not. The findings show that sequential models struggle with global upscaling, likely due to their sensitivity to data shifts from local to global scales. To improve ML-based upscaling, additional data or integration of physical knowledge is needed.
Arta Bārdule, Raija Laiho, Jyrki Jauhiainen, Kaido Soosaar, Andis Lazdiņš, Kęstutis Armolaitis, Aldis Butlers, Dovilė Čiuldienė, Andreas Haberl, Ain Kull, Milda Muraškienė, Ivika Ostonen, Gristin Rohula-Okunev, Muhammad Kamil-Sardar, Thomas Schindler, Hanna Vahter, Egidijus Vigricas, and Ieva Līcīte
EGUsphere, https://doi.org/10.5194/egusphere-2024-2523, https://doi.org/10.5194/egusphere-2024-2523, 2024
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Estimates of CO2 fluxes from drained nutrient-rich organic soils in cropland and grassland in the hemiboreal region of Europe revealed that annual net CO2 fluxes were lower than the latest (2014) IPCC emission factors provided for the whole temperate zone including hemiboreal region. Contribution of CO2 fluxes from shallow highly decomposed organic soils, former peatlands that no longer meet the IPCC criterion for organic soils, to total emissions can be high and should not be underestimated.
Elin Ristorp Aas, Inge Althuizen, Hui Tang, Sonya Geange, Eva Lieungh, Vigdis Vandvik, and Terje Koren Berntsen
Biogeosciences, 21, 3789–3817, https://doi.org/10.5194/bg-21-3789-2024, https://doi.org/10.5194/bg-21-3789-2024, 2024
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We used a soil model to replicate two litterbag decomposition experiments to examine the implications of climate, litter quality, and soil microclimate representation. We found that macroclimate was more important than litter quality for modeled mass loss. By comparing different representations of soil temperature and moisture we found that using observed data did not improve model results. We discuss causes for this and suggest possible improvements to both the model and experimental design.
Rebecca M. Varney, Pierre Friedlingstein, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
Biogeosciences, 21, 2759–2776, https://doi.org/10.5194/bg-21-2759-2024, https://doi.org/10.5194/bg-21-2759-2024, 2024
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Soil carbon is the largest store of carbon on the land surface of Earth and is known to be particularly sensitive to climate change. Understanding this future response is vital to successfully meeting Paris Agreement targets, which rely heavily on carbon uptake by the land surface. In this study, the individual responses of soil carbon are quantified and compared amongst CMIP6 Earth system models used within the most recent IPCC report, and the role of soils in the land response is highlighted.
Juliëtte C. S. Anema, Klaas Folkert Boersma, Piet Stammes, Gerbrand Koren, William Woodgate, Philipp Köhler, Christian Frankenberg, and Jacqui Stol
Biogeosciences, 21, 2297–2311, https://doi.org/10.5194/bg-21-2297-2024, https://doi.org/10.5194/bg-21-2297-2024, 2024
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To keep the Paris agreement goals within reach, negative emissions are necessary. They can be achieved with mitigation techniques, such as reforestation, which remove CO2 from the atmosphere. While governments have pinned their hopes on them, there is not yet a good set of tools to objectively determine whether negative emissions do what they promise. Here we show how satellite measurements of plant fluorescence are useful in detecting carbon uptake due to reforestation and vegetation regrowth.
Martin Jung, Jacob Nelson, Mirco Migliavacca, Tarek El-Madany, Dario Papale, Markus Reichstein, Sophia Walther, and Thomas Wutzler
Biogeosciences, 21, 1827–1846, https://doi.org/10.5194/bg-21-1827-2024, https://doi.org/10.5194/bg-21-1827-2024, 2024
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We present a methodology to detect inconsistencies in perhaps the most important data source for measurements of ecosystem–atmosphere carbon, water, and energy fluxes. We expect that the derived consistency flags will be relevant for data users and will help in improving our understanding of and our ability to model ecosystem–climate interactions.
Matteo Mastropierro, Daniele Peano, and Davide Zanchettin
EGUsphere, https://doi.org/10.5194/egusphere-2024-823, https://doi.org/10.5194/egusphere-2024-823, 2024
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We address how different ESMs represent vegetation productivity, in terms of carbon fluxes, within the Amazon basin. By statistically assessing the role of climatological and model specific factors that influence vegetation, we showed that surface energy fluxes and the implementation of Phosphorous limitation resulted to be the main drivers of model uncertainties in a future scenario. Reducing these uncertainties allows to increase the reliability of tropical land carbon and climate projections
Prajwal Khanal, Anne J. Hoek Van Dijke, Timo Schaffhauser, Wantong Li, Sinikka J. Paulus, Chunhui Zhan, and René Orth
Biogeosciences, 21, 1533–1547, https://doi.org/10.5194/bg-21-1533-2024, https://doi.org/10.5194/bg-21-1533-2024, 2024
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Water availability is essential for vegetation functioning, but the depth of vegetation water uptake is largely unknown due to sparse ground measurements. This study correlates vegetation growth with soil moisture availability globally to infer vegetation water uptake depth using only satellite-based data. We find that the vegetation water uptake depth varies across climate regimes and vegetation types and also changes during dry months at a global scale.
Anna-Maria Virkkala, Pekka Niittynen, Julia Kemppinen, Maija E. Marushchak, Carolina Voigt, Geert Hensgens, Johanna Kerttula, Konsta Happonen, Vilna Tyystjärvi, Christina Biasi, Jenni Hultman, Janne Rinne, and Miska Luoto
Biogeosciences, 21, 335–355, https://doi.org/10.5194/bg-21-335-2024, https://doi.org/10.5194/bg-21-335-2024, 2024
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Arctic greenhouse gas (GHG) fluxes of CO2, CH4, and N2O are important for climate feedbacks. We combined extensive in situ measurements and remote sensing data to develop machine-learning models to predict GHG fluxes at a 2 m resolution across a tundra landscape. The analysis revealed that the system was a net GHG sink and showed widespread CH4 uptake in upland vegetation types, almost surpassing the high wetland CH4 emissions at the landscape scale.
Thomas Baer, Gerhard Furrer, Stephan Zimmermann, and Patrick Schleppi
Biogeosciences, 20, 4577–4589, https://doi.org/10.5194/bg-20-4577-2023, https://doi.org/10.5194/bg-20-4577-2023, 2023
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Nitrogen (N) deposition to forest ecosystems is a matter of concern because it affects their nutrient status and makes their soil acidic. We observed an ongoing acidification in a montane forest in central Switzerland even if the subsoil of this site contains carbonates and is thus well buffered. We experimentally added N to simulate a higher pollution, and this increased the acidification. After 25 years of study, however, we can see the first signs of recovery, also under higher N deposition.
Huiying Xu, Han Wang, Iain Colin Prentice, and Sandy P. Harrison
Biogeosciences, 20, 4511–4525, https://doi.org/10.5194/bg-20-4511-2023, https://doi.org/10.5194/bg-20-4511-2023, 2023
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Leaf carbon (C) and nitrogen (N) are crucial elements in leaf construction and physiological processes. This study reconciled the roles of phylogeny, species identity, and climate in stoichiometric traits at individual and community levels. The variations in community-level leaf N and C : N ratio were captured by optimality-based models using climate data. Our results provide an approach to improve the representation of leaf stoichiometry in vegetation models to better couple N with C cycling.
István Dunkl, Nicole Lovenduski, Alessio Collalti, Vivek K. Arora, Tatiana Ilyina, and Victor Brovkin
Biogeosciences, 20, 3523–3538, https://doi.org/10.5194/bg-20-3523-2023, https://doi.org/10.5194/bg-20-3523-2023, 2023
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Despite differences in the reproduction of gross primary productivity (GPP) by Earth system models (ESMs), ESMs have similar predictability of the global carbon cycle. We found that, although GPP variability originates from different regions and is driven by different climatic variables across the ESMs, the ESMs rely on the same mechanisms to predict their own GPP. This shows that the predictability of the carbon cycle is limited by our understanding of variability rather than predictability.
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.
Keri L. Bowering, Kate A. Edwards, and Susan E. Ziegler
Biogeosciences, 20, 2189–2206, https://doi.org/10.5194/bg-20-2189-2023, https://doi.org/10.5194/bg-20-2189-2023, 2023
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Dissolved organic matter (DOM) mobilized from surface soils is a source of carbon (C) for deeper mineral horizons but also a mechanism of C loss. Composition of DOM mobilized in boreal forests varied more by season than as a result of forest harvesting. Results suggest reduced snowmelt and increased fall precipitation enhance DOM properties promoting mineral soil C stores. These findings, coupled with hydrology, can inform on soil C fate and boreal forest C balance in response to climate change.
Bharat Sharma, Jitendra Kumar, Auroop R. Ganguly, and Forrest M. Hoffman
Biogeosciences, 20, 1829–1841, https://doi.org/10.5194/bg-20-1829-2023, https://doi.org/10.5194/bg-20-1829-2023, 2023
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Rising atmospheric carbon dioxide increases vegetation growth and causes more heatwaves and droughts. The impact of such climate extremes is detrimental to terrestrial carbon uptake capacity. We found that due to overall climate warming, about 88 % of the world's regions towards the end of 2100 will show anomalous losses in net biospheric productivity (NBP) rather than gains. More than 50 % of all negative NBP extremes were driven by the compound effect of dry, hot, and fire conditions.
Britta Greenshields, Barbara von der Lühe, Felix Schwarz, Harold J. Hughes, Aiyen Tjoa, Martyna Kotowska, Fabian Brambach, and Daniela Sauer
Biogeosciences, 20, 1259–1276, https://doi.org/10.5194/bg-20-1259-2023, https://doi.org/10.5194/bg-20-1259-2023, 2023
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Silicon (Si) can have multiple beneficial effects on crops such as oil palms. In this study, we quantified Si concentrations in various parts of an oil palm (leaflets, rachises, fruit-bunch parts) to derive Si storage estimates for the total above-ground biomass of an oil palm and 1 ha of an oil-palm plantation. We proposed a Si balance by identifying Si return (via palm fronds) and losses (via harvest) in the system and recommend management measures that enhance Si cycling.
Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
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Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Nagham Tabaja, David Amouroux, Lamis Chalak, François Fourel, Emmanuel Tessier, Ihab Jomaa, Milad El Riachy, and Ilham Bentaleb
Biogeosciences, 20, 619–633, https://doi.org/10.5194/bg-20-619-2023, https://doi.org/10.5194/bg-20-619-2023, 2023
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This study investigates the seasonality of the mercury (Hg) concentration of olive trees. Hg concentrations of foliage, stems, soil surface, and litter were analyzed on a monthly basis in ancient olive trees growing in two groves in Lebanon. Our study draws an adequate baseline for the eastern Mediterranean and for the region with similar climatic inventories on Hg vegetation uptake in addition to being a baseline for new studies on olive trees in the Mediterranean.
Allison N. Myers-Pigg, Karl Kaiser, Ronald Benner, and Susan E. Ziegler
Biogeosciences, 20, 489–503, https://doi.org/10.5194/bg-20-489-2023, https://doi.org/10.5194/bg-20-489-2023, 2023
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Boreal forests, historically a global sink for atmospheric CO2, store carbon in vast soil reservoirs. To predict how such stores will respond to climate warming we need to understand climate–ecosystem feedbacks. We find boreal forest soil carbon stores are maintained through enhanced nitrogen cycling with climate warming, providing direct evidence for a key feedback. Further application of the approach demonstrated here will improve our understanding of the limits of climate–ecosystem feedbacks.
Matthew P. Dannenberg, Mallory L. Barnes, William K. Smith, Miriam R. Johnston, Susan K. Meerdink, Xian Wang, Russell L. Scott, and Joel A. Biederman
Biogeosciences, 20, 383–404, https://doi.org/10.5194/bg-20-383-2023, https://doi.org/10.5194/bg-20-383-2023, 2023
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Earth's drylands provide ecosystem services to many people and will likely be strongly affected by climate change, but it is quite challenging to monitor the productivity and water use of dryland plants with satellites. We developed and tested an approach for estimating dryland vegetation activity using machine learning to combine information from multiple satellite sensors. Our approach excelled at estimating photosynthesis and water use largely due to the inclusion of satellite soil moisture.
Mark Pickering, Alessandro Cescatti, and Gregory Duveiller
Biogeosciences, 19, 4833–4864, https://doi.org/10.5194/bg-19-4833-2022, https://doi.org/10.5194/bg-19-4833-2022, 2022
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This study explores two of the most recent products in carbon productivity estimation, FLUXCOM gross primary productivity (GPP), calculated by upscaling local measurements of CO2 exchange, and remotely sensed sun-induced chlorophyll a fluorescence (SIF). High-resolution SIF data are valuable in demonstrating similarity in the SIF–GPP relationship between vegetation covers, provide an independent probe of the FLUXCOM GPP model and demonstrate the response of SIF to meteorological fluctuations.
Sophia Walther, Simon Besnard, Jacob Allen Nelson, Tarek Sebastian El-Madany, Mirco Migliavacca, Ulrich Weber, Nuno Carvalhais, Sofia Lorena Ermida, Christian Brümmer, Frederik Schrader, Anatoly Stanislavovich Prokushkin, Alexey Vasilevich Panov, and Martin Jung
Biogeosciences, 19, 2805–2840, https://doi.org/10.5194/bg-19-2805-2022, https://doi.org/10.5194/bg-19-2805-2022, 2022
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Satellite observations help interpret station measurements of local carbon, water, and energy exchange between the land surface and the atmosphere and are indispensable for simulations of the same in land surface models and their evaluation. We propose generalisable and efficient approaches to systematically ensure high quality and to estimate values in data gaps. We apply them to satellite data of surface reflectance and temperature with different resolutions at the stations.
Elisabeth Mauclet, Yannick Agnan, Catherine Hirst, Arthur Monhonval, Benoît Pereira, Aubry Vandeuren, Maëlle Villani, Justin Ledman, Meghan Taylor, Briana L. Jasinski, Edward A. G. Schuur, and Sophie Opfergelt
Biogeosciences, 19, 2333–2351, https://doi.org/10.5194/bg-19-2333-2022, https://doi.org/10.5194/bg-19-2333-2022, 2022
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Arctic warming and permafrost degradation largely affect tundra vegetation. Wetter lowlands show an increase in sedges, whereas drier uplands favor shrub expansion. Here, we demonstrate that the difference in the foliar elemental composition of typical tundra vegetation species controls the change in local foliar elemental stock and potential mineral element cycling through litter production upon a shift in tundra vegetation.
Tiexi Chen, Renjie Guo, Qingyun Yan, Xin Chen, Shengjie Zhou, Chuanzhuang Liang, Xueqiong Wei, and Han Dolman
Biogeosciences, 19, 1515–1525, https://doi.org/10.5194/bg-19-1515-2022, https://doi.org/10.5194/bg-19-1515-2022, 2022
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Currently people are very concerned about vegetation changes and their driving factors, including natural and anthropogenic drivers. In this study, a general browning trend is found in Syria during 2001–2018, indicated by the vegetation index. We found that land management caused by social unrest is the main cause of this browning phenomenon. The mechanism initially reported here highlights the importance of land management impacts at the regional scale.
Rahayu Adzhar, Douglas I. Kelley, Ning Dong, Charles George, Mireia Torello Raventos, Elmar Veenendaal, Ted R. Feldpausch, Oliver L. Phillips, Simon L. Lewis, Bonaventure Sonké, Herman Taedoumg, Beatriz Schwantes Marimon, Tomas Domingues, Luzmila Arroyo, Gloria Djagbletey, Gustavo Saiz, and France Gerard
Biogeosciences, 19, 1377–1394, https://doi.org/10.5194/bg-19-1377-2022, https://doi.org/10.5194/bg-19-1377-2022, 2022
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The MODIS Vegetation Continuous Fields (VCF) product underestimates tree cover compared to field data and could be underestimating tree cover significantly across the tropics. VCF is used to represent land cover or validate model performance in many land surface and global vegetation models and to train finer-scaled Earth observation products. Because underestimation in VCF may render it unsuitable for training data and bias model predictions, it should be calibrated before use in the tropics.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
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The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Juhwan Lee, Raphael A. Viscarra Rossel, Mingxi Zhang, Zhongkui Luo, and Ying-Ping Wang
Biogeosciences, 18, 5185–5202, https://doi.org/10.5194/bg-18-5185-2021, https://doi.org/10.5194/bg-18-5185-2021, 2021
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We performed Roth C simulations across Australia and assessed the response of soil carbon to changing inputs and future climate change using a consistent modelling framework. Site-specific initialisation of the C pools with measurements of the C fractions is essential for accurate simulations of soil organic C stocks and composition at a large scale. With further warming, Australian soils will become more vulnerable to C loss: natural environments > native grazing > cropping > modified grazing.
Anam M. Khan, Paul C. Stoy, James T. Douglas, Martha Anderson, George Diak, Jason A. Otkin, Christopher Hain, Elizabeth M. Rehbein, and Joel McCorkel
Biogeosciences, 18, 4117–4141, https://doi.org/10.5194/bg-18-4117-2021, https://doi.org/10.5194/bg-18-4117-2021, 2021
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Remote sensing has played an important role in the study of land surface processes. Geostationary satellites, such as the GOES-R series, can observe the Earth every 5–15 min, providing us with more observations than widely used polar-orbiting satellites. Here, we outline current efforts utilizing geostationary observations in environmental science and look towards the future of GOES observations in the carbon cycle, ecosystem disturbance, and other areas of application in environmental science.
Lydia Stolpmann, Caroline Coch, Anne Morgenstern, Julia Boike, Michael Fritz, Ulrike Herzschuh, Kathleen Stoof-Leichsenring, Yury Dvornikov, Birgit Heim, Josefine Lenz, Amy Larsen, Katey Walter Anthony, Benjamin Jones, Karen Frey, and Guido Grosse
Biogeosciences, 18, 3917–3936, https://doi.org/10.5194/bg-18-3917-2021, https://doi.org/10.5194/bg-18-3917-2021, 2021
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Our new database summarizes DOC concentrations of 2167 water samples from 1833 lakes in permafrost regions across the Arctic to provide insights into linkages between DOC and environment. We found increasing lake DOC concentration with decreasing permafrost extent and higher DOC concentrations in boreal permafrost sites compared to tundra sites. Our study shows that DOC concentration depends on the environmental properties of a lake, especially permafrost extent, ecoregion, and vegetation.
Gustaf Granath, Christopher D. Evans, Joachim Strengbom, Jens Fölster, Achim Grelle, Johan Strömqvist, and Stephan J. Köhler
Biogeosciences, 18, 3243–3261, https://doi.org/10.5194/bg-18-3243-2021, https://doi.org/10.5194/bg-18-3243-2021, 2021
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We measured element losses and impacts on water quality following a wildfire in Sweden. We observed the largest carbon and nitrogen losses during the fire and a strong pulse of elements 1–3 months after the fire that showed a fast (weeks) and a slow (months) release from the catchments. Total carbon export through water did not increase post-fire. Overall, we observed a rapid recovery of the biogeochemical cycling of elements within 3 years but still an annual net release of carbon dioxide.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, and Benjamin Smith
Biogeosciences, 18, 2181–2203, https://doi.org/10.5194/bg-18-2181-2021, https://doi.org/10.5194/bg-18-2181-2021, 2021
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The El Niño–Southern Oscillation (ENSO) describes changes in the sea surface temperature patterns of the Pacific Ocean. This influences the global weather, impacting vegetation on land. There are two types of El Niño: central Pacific (CP) and eastern Pacific (EP). In this study, we explored the long-term impacts on the carbon balance on land linked to the two El Niño types. Using a dynamic vegetation model, we simulated what would happen if only either CP or EP El Niño events had occurred.
Matthias Volk, Matthias Suter, Anne-Lena Wahl, and Seraina Bassin
Biogeosciences, 18, 2075–2090, https://doi.org/10.5194/bg-18-2075-2021, https://doi.org/10.5194/bg-18-2075-2021, 2021
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Grassland ecosystem services like forage production and greenhouse gas storage in the soil depend on plant growth.
In an experiment in the mountains with warming treatments, we found that despite dwindling soil water content, the grassland growth increased with up to +1.3 °C warming (annual mean) compared to present temperatures. Even at +2.4 °C the growth was still larger than at the reference site.
This suggests that plant growth will increase due to global warming in the near future.
Bernice C. Hwang and Daniel B. Metcalfe
Biogeosciences, 18, 1259–1268, https://doi.org/10.5194/bg-18-1259-2021, https://doi.org/10.5194/bg-18-1259-2021, 2021
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Despite growing recognition of herbivores as important ecosystem engineers, many major gaps remain in our understanding of how silicon and herbivory interact to shape biogeochemical processes. We highlight the need for more research particularly in natural settings as well as on the potential effects of herbivory on terrestrial silicon cycling to understand potentially critical animal–plant–soil feedbacks.
Ali Asaadi and Vivek K. Arora
Biogeosciences, 18, 669–706, https://doi.org/10.5194/bg-18-669-2021, https://doi.org/10.5194/bg-18-669-2021, 2021
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More than a quarter of the current anthropogenic CO2 emissions are taken up by land, reducing the atmospheric CO2 growth rate. This is because of the CO2 fertilization effect which benefits 80 % of global vegetation. However, if nitrogen and phosphorus nutrients cannot keep up with increasing atmospheric CO2, the magnitude of this terrestrial ecosystem service may reduce in future. This paper implements nitrogen constraints on photosynthesis in a model to understand the mechanisms involved.
Arianna Peron, Lisa Kaser, Anne Charlott Fitzky, Martin Graus, Heidi Halbwirth, Jürgen Greiner, Georg Wohlfahrt, Boris Rewald, Hans Sandén, and Thomas Karl
Biogeosciences, 18, 535–556, https://doi.org/10.5194/bg-18-535-2021, https://doi.org/10.5194/bg-18-535-2021, 2021
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Drought events are expected to become more frequent with climate change. Along with these events atmospheric ozone is also expected to increase. Both can stress plants. Here we investigate to what extent these factors modulate the emission of volatile organic compounds (VOCs) from oak plants. We find an antagonistic effect between drought stress and ozone, impacting the emission of different BVOCs, which is indirectly controlled by stomatal opening, allowing plants to control their water budget.
Lena Wohlgemuth, Stefan Osterwalder, Carl Joseph, Ansgar Kahmen, Günter Hoch, Christine Alewell, and Martin Jiskra
Biogeosciences, 17, 6441–6456, https://doi.org/10.5194/bg-17-6441-2020, https://doi.org/10.5194/bg-17-6441-2020, 2020
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Mercury uptake by trees from the air represents an important but poorly quantified pathway in the global mercury cycle. We determined mercury uptake fluxes by leaves and needles at 10 European forests which were 4 times larger than mercury deposition via rainfall. The amount of mercury taken up by leaves and needles depends on their age and growing height on the tree. Scaling up our measurements to the forest area of Europe, we estimate that each year 20 t of mercury is taken up by trees.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
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We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Erqian Cui, Chenyu Bian, Yiqi Luo, Shuli Niu, Yingping Wang, and Jianyang Xia
Biogeosciences, 17, 6237–6246, https://doi.org/10.5194/bg-17-6237-2020, https://doi.org/10.5194/bg-17-6237-2020, 2020
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Mean annual net ecosystem productivity (NEP) is related to the magnitude of the carbon sink of a specific ecosystem, while its inter-annual variation (IAVNEP) characterizes the stability of such a carbon sink. Thus, a better understanding of the co-varying NEP and IAVNEP is critical for locating the major and stable carbon sinks on land. Based on daily NEP observations from eddy-covariance sites, we found local indicators for the spatially varying NEP and IAVNEP, respectively.
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
Rui Cheng, Troy S. Magney, Debsunder Dutta, David R. Bowling, Barry A. Logan, Sean P. Burns, Peter D. Blanken, Katja Grossmann, Sophia Lopez, Andrew D. Richardson, Jochen Stutz, and Christian Frankenberg
Biogeosciences, 17, 4523–4544, https://doi.org/10.5194/bg-17-4523-2020, https://doi.org/10.5194/bg-17-4523-2020, 2020
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We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments that play an important role in regulating the seasonality of photosynthesis. Results show a strong mechanistic link between spectral reflectance features and pigment content, which is validated using a biophysical model. Our results show spectrally where, why, and when spectral features change over the course of the season and show promise for estimating photosynthesis remotely.
Jarmo Mäkelä, Francesco Minunno, Tuula Aalto, Annikki Mäkelä, Tiina Markkanen, and Mikko Peltoniemi
Biogeosciences, 17, 2681–2700, https://doi.org/10.5194/bg-17-2681-2020, https://doi.org/10.5194/bg-17-2681-2020, 2020
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We assess the relative magnitude of uncertainty sources on ecosystem indicators of the 21st century climate change on two boreal forest sites. In addition to RCP and climate model uncertainties, we included the overlooked model parameter uncertainty and management actions in our analysis. Management was the dominant uncertainty factor for the more verdant southern site, followed by RCP, climate and parameter uncertainties. The uncertainties were estimated with canonical correlation analysis.
Cited articles
Abatzoglou, J. T., Rupp, D. E., and Mote, P. W.: Seasonal Climate
Variability and Change in the Pacific Northwest of the United
States, J. Clim., 27, 2125–2142,
https://doi.org/10.1175/JCLI-D-13-00218.1, 2014. a
Anav, A., Friedlingstein, P., Beer, C., Ciais, P., Harper, A., Jones, C.,
Murray-Tortarolo, G., Papale, D., Parazoo, N. C., Peylin, P., Piao, S.,
Sitch, S., Viovy, N., Wiltshire, A., and Zhao, M.: Spatiotemporal patterns of
terrestrial gross primary production: A review: GPP Spatiotemporal
Patterns, Rev. Geophys., 53, 785–818, https://doi.org/10.1002/2015RG000483, 2015. a, b
Aragão, L. E. O. C., Anderson, L. O., Fonseca, M. G., Rosan, T. M.,
Vedovato, L. B., Wagner, F. H., Silva, C. V. J., Silva Junior, C. H. L.,
Arai, E., Aguiar, A. P., Barlow, J., Berenguer, E., Deeter, M. N., Domingues,
L. G., Gatti, L., Gloor, M., Malhi, Y., Marengo, J. A., Miller, J. B.,
Phillips, O. L., and Saatchi, S.: 21st Century Drought-Related Fires
Counteract the Decline of Amazon Deforestation Carbon Emissions, Nat.
Commun., 9, 146–149, https://doi.org/10.1038/s41467-017-02771-y, 2018. a
Ardisson, P.-L., Bourget, E., and Legendre, P.: Multivariate Approach to
Study Species Assemblages at Large Spatiotemporal Scales: The
Community Structure of the Epibenthic Fauna of the Estuary and
Gulf of St. Lawrence, Can. J. Fish. Aquat.
Sci., 47, 1364–1377, https://doi.org/10.1139/f90-156, 1990. a
Arenas-Garcia, J., Petersen, K. B., Camps-Valls, G., and Hansen, L. K.:
Kernel Multivariate Analysis Framework for Supervised Subspace
Learning: A Tutorial on Linear and Kernel Multivariate Methods,
IEEE Signal Processing Magazine, 30, 16–29, https://doi.org/10.1109/MSP.2013.2250591,
2013. a
Babst, F., Poulter, B., Bodesheim, P., Mahecha, M. D., and Frank, D. C.:
Improved tree-ring archives will support earth-system science, Nat. Ecol.
Evol., 1, 1–2, 2017. a
Baldocchi, D. D.: How Eddy Covariance Flux Measurements Have Contributed to Our
Understanding of Global Change Biology, Glob. Change Biol., 26,
242–260, https://doi.org/10.1111/gcb.14807, 2020. a, b
Barriopedro, D., Fischer, E. M., Luterbacher, J., Trigo, R. M., and
García-Herrera, R.: The Hot Summer of 2010: Redrawing the
Temperature Record Map of Europe, Science, 332, 220–224,
https://doi.org/10.1126/science.1201224, 2011. a
Beisner, B., Haydon, D., and Cuddington, K.: Alternative Stable States in
Ecology, Front. Ecol. Environ., 1, 376–382,
https://doi.org/10.1890/1540-9295(2003)001[0376:ASSIE]2.0.CO;2, 2003. a
Benjamini, Y. and Hochberg, Y.: Controlling the False Discovery Rate: A
Practical and Powerful Approach to Multiple Testing, J.
Roy. Stat. Soc. B, 57, 289–300, 1995. a
Berger, M., Moreno, J., Johannessen, J. A., Levelt, P. F., and Hanssen, R. F.:
ESA's Sentinel Missions in Support of Earth System Science, Remote
Sens. Environ., 120, 84–90, https://doi.org/10.1016/j.rse.2011.07.023, 2012. a
Blonder, B., Moulton, D. E., Blois, J., Enquist, B. J., Graae, B. J.,
Macias-Fauria, M., McGill, B., Nogué, S., Ordonez, A., Sandel, B., and
Svenning, J.-C.: Predictability in Community Dynamics, Ecol. Lett., 20,
293–306, https://doi.org/10.1111/ele.12736, 2017. a
Bowen, I. S.: The Ratio of Heat Losses by Conduction and by
Evaporation from Any Water Surface, Phys. Rev., 27, 779–787,
https://doi.org/10.1103/PhysRev.27.779, 1926. a, b
Brown, R. L., Durbin, J., and Evans, J. M.: Techniques for Testing the.ournal of the
Roy. Stat. Soc. B, 37, 149–192, 1975. a
Cattell, R. B.: The Scree Test For The Number Of Factors, Multivar.
Behav. Res., 1, 245–276, https://doi.org/10.1207/s15327906mbr0102_10, 1966. a
Chapin, F. S., Woodwell, G. M., Randerson, J. T., Rastetter, E. B., Lovett,
G. M., Baldocchi, D. D., Clark, D. A., Harmon, M. E., Schimel, D. S.,
Valentini, R., Wirth, C., Aber, J. D., Cole, J. J., Goulden, M. L., Harden,
J. W., Heimann, M., Howarth, R. W., Matson, P. A., McGuire, A. D., Melillo,
J. M., Mooney, H. A., Neff, J. C., Houghton, R. A., Pace, M. L., Ryan, M. G.,
Running, S. W., Sala, O. E., Schlesinger, W. H., and Schulze, E.-D.:
Reconciling Carbon-Cycle Concepts, Terminol. Method.
Ecosys., 9, 1041–1050, https://doi.org/10.1007/s10021-005-0105-7, 2006. a
Chen, C., Park, T., Wang, X., Piao, S., Xu, B., Chaturvedi, R. K., Fuchs, R.,
Brovkin, V., Ciais, P., Fensholt, R., Tømmervik, H., Bala, G., Zhu, Z.,
Nemani, R. R., and Myneni, R. B.: China and India Lead in Greening of the
World through Land-Use Management, Nature Sustainability, 2, 122–129,
https://doi.org/10.1038/s41893-019-0220-7, 2019. a
Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogée, J., Allard, V.,
Aubinet, M., Buchmann, N., Bernhofer, C., Carrara, A., Chevallier, F.,
Noblet, N. D., Friend, A. D., Friedlingstein, P., Grünwald, T., Heinesch,
B., Keronen, P., Knohl, A., Krinner, G., Loustau, D., Manca, G., Matteucci,
G., Miglietta, F., Ourcival, J. M., Papale, D., Pilegaard, K., Rambal, S.,
Seufert, G., Soussana, J. F., Sanz, M. J., Schulze, E. D., Vesala, T., and
Valentini, R.: Europe-Wide Reduction in Primary Productivity Caused by the
Heat and Drought in 2003, Nature, 437, 529–533, https://doi.org/10.1038/nature03972, 2005. a
de Jong, R., de Bruin, S., de Wit, A., Schaepman, M. E., and Dent, D. L.:
Analysis of Monotonic Greening and Browning Trends from Global NDVI
Time-Series, Remote Sens. Environ., 115, 692–702,
https://doi.org/10.1016/j.rse.2010.10.011, 2011. a, b
Díaz, S., Settele, J., Brondízio, E. S., Ngo, H. T., Agard, J., Arneth,
A., Balvanera, P., Brauman, K. A., Butchart, S. H. M., Chan, K. M. A.,
Garibaldi, L. A., Ichii, K., Liu, J., Subramanian, S. M., Midgley, G. F.,
Miloslavich, P., Molnár, Z., Obura, D., Pfaff, A., Polasky, S., Purvis,
A., Razzaque, J., Reyers, B., Chowdhury, R. R., Shin, Y.-J.,
Visseren-Hamakers, I., Willis, K. J., and Zayas, C. N.: Pervasive
Human-Driven Decline of Life on Earth Points to the Need for
Transformative Change, Science, 366, 6471, https://doi.org/10.1126/science.aax3100, 2019. a
Disney, M., Muller, J.-P., Kharbouche, S., Kaminski, T., Voßbeck, M.,
Lewis, P., and Pinty, B.: A New Global fAPAR and LAI Dataset Derived
from Optimal Albedo Estimates: Comparison with MODIS Products,
Remote Sens., 8, 1–29, https://doi.org/10.3390/rs8040275, 2016. a, b
Doughty, C. E., Metcalfe, D. B., Girardin, C. a. J., Amézquita, F. F.,
Cabrera, D. G., Huasco, W. H., Silva-Espejo, J. E., Araujo-Murakami, A.,
da Costa, M. C., Rocha, W., Feldpausch, T. R., Mendoza, A. L. M., da Costa,
A. C. L., Meir, P., Phillips, O. L., and Malhi, Y.: Drought impact on forest
carbon dynamics and fluxes in Amazonia, Nature, 519, 78–82,
https://doi.org/10.1038/nature14213, 2015. a
Feldpausch, T. R., Phillips, O. L., Brienen, R. J. W., Gloor, E., Lloyd, J.,
Lopez-Gonzalez, G., Monteagudo-Mendoza, A., Malhi, Y., Alarcón, A.,
Dávila, E. A., Alvarez-Loayza, P., Andrade, A., Aragao, L. E. O. C.,
Arroyo, L., C, G. A. A., Baker, T. R., Baraloto, C., Barroso, J., Bonal, D.,
Castro, W., Chama, V., Chave, J., Domingues, T. F., Fauset, S., Groot, N.,
Coronado, E. H., Laurance, S., Laurance, W. F., Lewis, S. L., Licona, J. C.,
Marimon, B. S., Marimon-Junior, B. H., Bautista, C. M., Neill, D. A.,
Oliveira, E. A., dos Santos, C. O., Camacho, N. C. P., Pardo-Molina, G.,
Prieto, A., Quesada, C. A., Ramírez, F., Ramírez-Angulo, H.,
Réjou-Méchain, M., Rudas, A., Saiz, G., Salomão, R. P., Silva-Espejo,
J. E., Silveira, M., ter Steege, H., Stropp, J., Terborgh, J., Thomas-Caesar,
R., van der Heijden, G. M. F., Martinez, R. V., Vilanova, E., and Vos, V. A.:
Amazon Forest Response to Repeated Droughts, Global Biogeochem. Cy.,
30, 964–982, https://doi.org/10.1002/2015GB005133, 2016. a
Flach, M., Gans, F., Brenning, A., Denzler, J., Reichstein, M., Rodner, E., Bathiany, S., Bodesheim, P., Guanche, Y., Sippel, S., and Mahecha, M. D.: Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques, Earth Syst. Dynam., 8, 677–696, https://doi.org/10.5194/esd-8-677-2017, 2017. a
Flach, M., Sippel, S., Gans, F., Bastos, A., Brenning, A., Reichstein, M., and
Mahecha, M. D.: Contrasting biosphere responses to hydrometeorological
extremes: revisiting the 2010 western Russian heatwave, Biogeosciences, 15,
6067–6085, https://doi.org/10.5194/bg-15-6067-2018, 2018. a, b, c, d
Folke, C., Carpenter, S., Walker, B., Scheffer, M., Elmqvist, T., Gunderson,
L., and Holling, C.: Regime Shifts, Resilience, and Biodiversity
in Ecosystem Management, Annu. Rev. Ecol. Evol.
S., 35, 557–581, https://doi.org/10.1146/annurev.ecolsys.35.021103.105711,
2004. a
Forkel, M., Carvalhais, N., Verbesselt, J., Mahecha, M., Neigh, C., Reichstein,
M., Forkel, M., Carvalhais, N., Verbesselt, J., Mahecha, M. D., Neigh, C.
S. R., and Reichstein, M.: Trend Change Detection in NDVI Time
Series: Effects of Inter-Annual Variability and
Methodology, Remote Sens., 5, 2113–2144, https://doi.org/10.3390/rs5052113,
2013. a
Forkel, M., Migliavacca, M., Thonicke, K., Reichstein, M., Schaphoff, S.,
Weber, U., and Carvalhais, N.: Codominant Water Control on Global Interannual
Variability and Trends in Land Surface Phenology and Greenness, Glob. Change
Biol., 21, 3414–3435, https://doi.org/10.1111/gcb.12950, 2015. a
Forkel, M., Carvalhais, N., Rodenbeck, C., Keeling, R., Heimann, M., Thonicke,
K., Zaehle, S., and Reichstein, M.: Enhanced Seasonal CO2 Exchange Caused
by Amplified Plant Productivity in Northern Ecosystems, Science, 351,
696–699, https://doi.org/10.1126/science.aac4971, 2016. a, b
Foster, A. C., Armstrong, A. H., Shuman, J. K., Shugart, H. H., Rogers, B. M.,
Mack, M. C., Goetz, S. J., and Ranson, K. J.: Importance of Tree- and
Species-Level Interactions with Wildfire, Climate, and Soils in Interior
Alaska: Implications for Forest Change under a Warming Climate,
Ecol. Modell., 409, 108765, https://doi.org/10.1016/j.ecolmodel.2019.108765,
2019. a
García-Herrera, R., Díaz, J., Trigo, R. M., Luterbacher, J., and Fischer,
E. M.: A Review of the European Summer Heat Wave of 2003, Crit.
Rev. Env. Sci. Tec., 40, 267–306,
https://doi.org/10.1080/10643380802238137,
2010. a
Gaumont-Guay, D., Black, T. A., Griffis, T. J., Barr, A. G., Jassal, R. S.,
and Nesic, Z.: Interpreting the Dependence of Soil Respiration on Soil
Temperature and Water Content in a Boreal Aspen Stand, Agr.
Forest Meteorol., 140, 220–235, https://doi.org/10.1016/j.agrformet.2006.08.003,
2006. a
Graven, H. D., Keeling, R. F., Piper, S. C., Patra, P. K., Stephens, B. B.,
Wofsy, S. C., Welp, L. R., Sweeney, C., Tans, P. P., Kelley, J. J., Daube,
B. C., Kort, E. A., Santoni, G. W., and Bent, J. D.: Enhanced Seasonal
Exchange of CO2 by Northern Ecosystems Since 1960, Science, 341,
1085–1089, https://doi.org/10.1126/science.1239207, 2013. a
Hao, Z., Zheng, J., Ge, Q., and Wang, W.: Historical Analogues of the 2008
Extreme Snow Event over Central and Southern China, Clim. Res.,
50, 161–170, https://doi.org/10.3354/cr01052, 2011. a
Hendon, H. H., Lim, E.-P., Arblaster, J. M., and Anderson, D. L. T.: Causes and
Predictability of the Record Wet East Australian Spring 2010, Clim.
Dynam., 42, 1155–1174, https://doi.org/10.1007/s00382-013-1700-5, 2014. a
Higham, N. J.: The Accuracy of Floating Point Summation, SIAM J.
Sci. Comput., 14, 783–799, https://doi.org/10.1137/0914050, 1993. a
Horridge, M., Madden, J., and Wittwer, G.: The Impact of the
2002–2003 Drought on Australia, J. Policy Model.,
27, 285–308, https://doi.org/10.1016/j.jpolmod.2005.01.008, 2005. a
Huang, K., Xia, J., Wang, Y., Ahlström, A., Chen, J., Cook, R. B., Cui, E.,
Fang, Y., Fisher, J. B., Huntzinger, D. N., Li, Z., Michalak, A. M., Qiao,
Y., Schaefer, K., Schwalm, C., Wang, J., Wei, Y., Xu, X., Yan, L., Bian, C.,
and Luo, Y.: Enhanced Peak Growth of Global Vegetation and Its Key
Mechanisms, Nat. Ecol. Evol., 2, 1897–1905,
https://doi.org/10.1038/s41559-018-0714-0, 2018. a
IPBES: Summary for Policymakers of the Global Assessment Report on
Biodiversity and Ecosystem Services of the Intergovernmental
Science-Policy Platform on Biodiversity and Ecosystem Services,
Summary for policymakers, IPBES, 39 pp., 2019. a
IPCC: Climate Change 2014: Synthesis Report. Contribution of
Working Groups I, II and III to the Fifth Assessment Report
of the Intergovernmental Panel on Climate Change, Tech. rep., IPCC,
Geneva, Swizerland, 2014. a
Ivits, E., Horion, S., Fensholt, R., and Cherlet, M.: Drought Footprint on
European Ecosystems between 1999 and 2010 Assessed by Remotely Sensed
Vegetation Phenology and Productivity, Glob. Change Biol., 20, 581–593,
https://doi.org/10.1111/gcb.12393, 2014. a
Jolly, W. M., Cochrane, M. A., Freeborn, P. H., Holden, Z. A., Brown, T. J.,
Williamson, G. J., and Bowman, D. M. J. S.: Climate-Induced Variations in
Global Wildfire Danger from 1979 to 2013, Nat. Commun., 6, 7537,
https://doi.org/10.1038/ncomms8537, 2015. a
Keeling, C. D., Chin, J. F. S., and Whorf, T. P.: Increased Activity of
Northern Vegetation Inferred from AtmosphericCO2 Measurements, Nature,
382, 146–149, https://doi.org/10.1038/382146a0, 1996. a
Kendall, M. G.: Rank Correlation Methods, Griffin, London, 202 pp., 1970. a
Khanna, J., Medvigy, D., Fueglistaler, S., and Walko, R.: Regional dry-season
climate changes due to three decades of Amazonian deforestation, Nat.
Clim. Change, 7, 200–204, https://doi.org/10.1038/nclimate3226, 2017. a
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World Map of
the Köppen-Geiger climate classification updated, Meteorol.
Z., 15, 259–263, https://doi.org/10.1127/0941-2948/2006/0130, a
Kraemer, G.: gdkrmr/summarizing_the_state_of_the_biosphere v1.1.1, Zenodo, https://doi.org/10.5281/zenodo.3733783, 2020. a
Kraemer, G., Reichstein, M., and Mahecha, M. D.: dimRed and coRanking –
Unifying Dimensionality Reduction in R, R J., 10, 342–358,
https://doi.org/10.32614/RJ-2018-039, 2018. a, b
Kraemer, G., Camps-Valls, G., Reichstein, M., and Mahecha, M. D.:
Summarizing the state of the terrestrial biosphere in few dimensions, Zenodo, https://doi.org/10.5281/zenodo.3733766, 2020. a
Kuan, C.-M. and Hornik, K.: The Generalized Fluctuation Test: A Unifying
View, Economet. Rev., 14, 135–161, https://doi.org/10.1080/07474939508800311,
1995. a
Legendre, P., Planas, D., and Auclair, M.-J.: Succession des communautés de
gastéropodes dans deux milieux différant par leur degré d'eutrophisation,
Can. J. Zool., 62, 2317–2327, https://doi.org/10.1139/z84-339, 1984. a
Lenton, T. M., Held, H., Kriegler, E., Hall, J. W., Lucht, W., Rahmstorf, S.,
and Schellnhuber, H. J.: Tipping Elements in the Earth's Climate System,
P. Natl. Acad. Sci. USA, 105, 1786–1793,
https://doi.org/10.1073/pnas.0705414105, 2008. a
Mahecha, M. D., Martínez, A., Lischeid, G., and Beck, E.: Nonlinear
Dimensionality Reduction: Alternative Ordination Approaches for
Extracting and Visualizing Biodiversity Patterns in Tropical Montane Forest
Vegetation Data, Ecol. Inform., 2, 138–149,
https://doi.org/10.1016/j.ecoinf.2007.05.002, 2007a. a, b
Mahecha, M. D., Reichstein, M., Lange, H., Carvalhais, N., Bernhofer, C.,
Grünwald, T., Papale, D., and Seufert, G.: Characterizing
Ecosystem-Atmosphere Interactions from Short to Interannual Time Scales,
Biogeosciences, 4, 743–758, https://doi.org/10.5194/bg-4-743-2007,
2007b. a
Mahecha, M. D., Gans, F., Sippel, S., Donges, J. F., Kaminski, T., Metzger, S.,
Migliavacca, M., Papale, D., Rammig, A., and Zscheischler, J.: Detecting
Impacts of Extreme Events with Ecological in Situ Monitoring Networks,
Biogeosciences, 14, 4255–4277,
https://doi.org/10.5194/bg-14-4255-2017, 2017. a
Mahecha, M. D., Gans, F., Brandt, G., Christiansen, R., Cornell, S. E., Fomferra, N., Kraemer, G., Peters, J., Bodesheim, P., Camps-Valls, G., Donges, J. F., Dorigo, W., Estupinan-Suarez, L. M., Gutierrez-Velez, V. H., Gutwin, M., Jung, M., Londoño, M. C., Miralles, D. G., Papastefanou, P., and Reichstein, M.: Earth system data cubes unravel global multivariate dynamics, Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, 2020. a
Mann, H. B.: Nonparametric Tests Against Trend, Econometrica, 13, 245–259,
https://doi.org/10.2307/1907187, 1945. a
Martens, B., Miralles, D. G., Lievens, H., Schalie, R. v. d., Jeu, R. A. M. d.,
Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.:
GLEAM v3: satellite-based land evaporation and root-zone soil moisture,
Geosci. Model Dev., 10, 1903–1925,
https://doi.org/10.5194/gmd-10-1903-2017, 2017. a, b, c, d, e, f, g, h, i
Metzger, M. J., Bunce, R. G. H., Jongman, R. H. G., Sayre, R., Trabucco, A.,
and Zomer, R.: A High-resolution Bioclimate Map of the World: A Unifying
Framework for Global Biodiversity Research and Monitoring, Glob. Ecol.
Biogeogr., 22, 630–638, https://doi.org/10.1111/geb.12022, 2013. a
Mika, S., Scholkopf, B., Smola, A., Muller, K., Scholz, M., and Ratsch, G.:
Kernel PCA and De-Noising in Feature Spaces, in: Advances In Neural
Information Processing Systems, edited by: Kearns, M. S., Solla, S. A., and
Cohn, D. A., Vol. 11 of Advances in Neural Information Processing Systems, 12th Annual Conference on Neural Information
Processing Systems (NIPS), Denver, CO, 30 November–5 December 1998, 536–542, 1999. a
Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C., and Vilà-Guerau de
Arellano, J.: Mega-heatwave temperatures due to combined soil desiccation and
atmospheric heat accumulation, Nat. Geosci., 7, 345–349,
https://doi.org/10.1038/ngeo2141, 2014. a
Najafi, E., Pal, I., and Khanbilvardi, R.: Climate Drives Variability and Joint
Variability of Global Crop Yields, Sci. Total Environ.t, 662,
361–372, https://doi.org/10.1016/j.scitotenv.2019.01.172, 2019. a
Nasahara, K. N. and Nagai, S.: Review: Development of an in Situ
Observation Network for Terrestrial Ecological Remote Sensing: The
Phenological Eyes Network (PEN), Ecol. Res., 30, 211–223,
https://doi.org/10.1007/s11284-014-1239-x, 2015. a
Nicholls, N.: The Changing Nature of Australian Droughts, Climatic
Change, 63, 323–336, https://doi.org/10.1023/B:CLIM.0000018515.46344.6d, 2004. a
Nicholson, S. E.: A detailed look at the recent drought situation in the
Greater Horn of Africa, J. Arid Environ., 103, 71–79,
https://doi.org/10.1016/j.jaridenv.2013.12.003,
2014. a
Papale, D., Black, T. A., Carvalhais, N., Cescatti, A., Chen, J., Jung, M.,
Kiely, G., Lasslop, G., Mahecha, M. D., Margolis, H., Merbold, L.,
Montagnani, L., Moors, E., Olesen, J. E., Reichstein, M., Tramontana, G., van
Gorsel, E., Wohlfahrt, G., and Ráduly, B.: Effect of Spatial Sampling
from European Flux Towers for Estimating Carbon and Water Fluxes with
Artificial Neural Networks, J. Geophys. Res.-Biogeo.,
120, 1941–1957, https://doi.org/10.1002/2015JG002997, 2015. a
Parmesan, C.: Ecological and Evolutionary Responses to Recent Climate
Change, Ann. Rev. Ecol. Evol. S., 37, 637–669,
https://doi.org/10.1146/annurev.ecolsys.37.091305.110100, 2006. a
Pearson, K.: On Lines and Planes of Closest Fit to Systems of Points in Space,
Philos. Mag., 2, 559–572, 1901. a
Piao, S., Wang, X., Park, T., Chen, C., Lian, X., He, Y., Bjerke, J. W., Chen,
A., Ciais, P., Tømmervik, H., Nemani, R. R., and Myneni, R. B.: Characteristics, drivers and
feedbacks of global greening, Nat. Rev. Earth Environ., 1, 14–27, https://doi.org/10.1038/s43017-019-0001-x,
2019. a
Piao, S., Wang, X., Wang, K., Li, X., Bastos, A., Canadell, J. G., Ciais, P.,
Friedlingstein, P., and Sitch, S.: Interannual Variation of Terrestrial
Carbon Cycle: Issues and Perspectives, Glob. Change Biol., 26,
300–318, https://doi.org/10.1111/gcb.14884, 2020. a
Rao, M., Saw Htun, Platt, S. G., Tizard, R., Poole, C., Than Myint, and
Watson, J. E. M.: Biodiversity Conservation in a Changing Climate:
A Review of Threats and Implications for Conservation
Planning in Myanmar, AMBIO, 42, 789–804,
https://doi.org/10.1007/s13280-013-0423-5, 2013. a
Reichstein, M., Bahn, M., Ciais, P., Frank, D., Mahecha, M. D., Seneviratne,
S. I., Zscheischler, J., Beer, C., Buchmann, N., Frank, D. C., Papale, D.,
Rammig, A., Smith, P., Thonicke, K., van der Velde, M., Vicca, S., Walz, A.,
and Wattenbach, M.: Climate extremes and the carbon cycle, Nature, 500,
287–295, https://doi.org/10.1038/nature12350, 2013. a
Renner, M., Brenner, C., Mallick, K., Wizemann, H.-D., Conte, L., Trebs, I.,
Wei, J., Wulfmeyer, V., Schulz, K., and Kleidon, A.: Using Phase Lags to
Evaluate Model Biases in Simulating the Diurnal Cycle of Evapotranspiration:
A Case Study in Luxembourg, Hydrol. Earth Syst. Sci., 23,
515–535, https://doi.org/10.5194/hess-23-515-2019, 2019. a
Richardson, A. D., Braswell, B. H., Hollinger, D. Y., Burman, P., Davidson,
E. A., Evans, R. S., Flanagan, L. B., Munger, J. W., Savage, K., Urbanski,
S. P., and Wofsy, S. C.: Comparing Simple Respiration Models for Eddy Flux
and Dynamic Chamber Data, Agr. Forest Meteorol., 141, 219–234,
https://doi.org/10.1016/j.agrformet.2006.10.010, 2006. a
Rosenfeld, D., Zhu, Y., Wang, M., Zheng, Y., Goren, T., and Yu, S.:
Aerosol-Driven Droplet Concentrations Dominate Coverage and Water of Oceanic
Low-Level Clouds, Science, 363, eaav0566, https://doi.org/10.1126/science.aav0566, 2019. a
Sarmah, S., Jia, G., and Zhang, A.: Satellite View of Seasonal Greenness Trends
and Controls in South Asia, Environ. Res. Lett., 13, 034026,
https://doi.org/10.1088/1748-9326/aaa866, 2018. a
Schimel, D. and Schneider, F. D.: Flux Towers in the Sky: Global Ecology from
Space, New Phytol., 224, 570–584, https://doi.org/10.1111/nph.15934, 2019. a
Schwartz, M. D.: Monitoring Global Change with Phenology: The Case of the
Spring Green Wave, Int. J. Biometeorol., 38, 18–22,
https://doi.org/10.1007/BF01241799, 1994. a
Schwartz, M. D.: Green-Wave Phenology, Nature, 394, 839–840, https://doi.org/10.1038/29670,
1998. a, b
Sen, P. K.: Estimates of the Regression Coefficient Based on Kendall's
Tau, J. Am. Stat. Assoc., 63, 1379–1389,
https://doi.org/10.2307/2285891, 1968. a
Sippel, S., Reichstein, M., Ma, X., Mahecha, M. D., Lange, H., Flach, M., and
Frank, D.: Drought, Heat, and the Carbon Cycle: A Review, Current
Climate Change Reports, 4, 266–286, https://doi.org/10.1007/s40641-018-0103-4, 2018. a
Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo,
G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C.,
Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng,
N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais,
P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C.,
Smith, B., Zhu, Z., and Myneni, R.: Recent Trends and Drivers of Regional
Sources and Sinks of Carbon Dioxide, Biogeosciences, 12, 653–679,
https://doi.org/10.5194/bg-12-653-2015, 2015. a
Song, X.-P., Hansen, M. C., Stehman, S. V., Potapov, P. V., Tyukavina, A.,
Vermote, E. F., and Townshend, J. R.: Global Land Change from 1982 to 2016,
Nature, 560, 639–643, https://doi.org/10.1038/s41586-018-0411-9, 2018. a, b
Steffen, W., Richardson, K., Rockström, J., Cornell, S. E., Fetzer, I.,
Bennett, E. M., Biggs, R., Carpenter, S. R., de Vries, W., de Wit, C. A.,
Folke, C., Gerten, D., Heinke, J., Mace, G. M., Persson, L. M., Ramanathan,
V., Reyers, B., and Sörlin, S.: Planetary Boundaries: Guiding Human
Development on a Changing Planet, Science, 347, 1259855-1–1259855-10,
https://doi.org/10.1126/science.1259855, 2015. a
Stine, A. R., Huybers, P., and Fung, I. Y.: Changes in the Phase of the Annual
Cycle of Surface Temperature, Nature, 457, 435–440,
https://doi.org/10.1038/nature07675, 2009. a, b
Tang, J., Baldocchi, D. D., and Xu, L.: Tree Photosynthesis Modulates Soil
Respiration on a Diurnal Time Scale, Glob. Change Biol., 11, 1298–1304,
https://doi.org/10.1111/j.1365-2486.2005.00978.x, 2005. a
Theil, H.: A Rank-Invariant Method of Linear and Polynomial
Regression Analysis, I, II, III, Proceedings of the Koninklijke
Nederlandse Akademie van Wetenschappen, 53, 386–392,
1950a. a
Theil, H.: A Rank-Invariant Method of Linear and Polynomial
Regression Analysis, I, II, III, Proceedings of the Koninklijke
Nederlandse Akademie van Wetenschappen, 53, 521–525, 1950b. a
Theil, H.: A Rank-Invariant Method of Linear and Polynomial
Regression Analysis, I, II, III, Proceedings of the Koninklijke
Nederlandse Akademie van Wetenschappen, 53, 1397–1412, 1950c. a
Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly,
B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L.,
Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D.: Predicting carbon
dioxide and energy fluxes across global FLUXNET sites with regression
algorithms, Biogeosciences, 13, 4291–4313,
https://doi.org/10.5194/bg-13-4291-2016, 2016. a, b, c, d, e, f, g, h, i, j, k
Van Der Maaten, L., Postma, E., and Van den Herik, J.: Dimensionality
Reduction: A Comparative Review, J. Mach. Learn. Res., 10, 66–71, 2009. a
van der Maaten, L., Schmidtlein, S., and Mahecha, M. D.: Analyzing Floristic
Inventories with Multiple Maps, Ecol. Inform., 9, 1–10,
https://doi.org/10.1016/j.ecoinf.2012.01.005, 2012. a
Verbesselt, J., Hyndman, R., Newnham, G., and Culvenor, D.: Detecting Trend and
Seasonal Changes in Satellite Image Time Series, Remote Sens.
Environ., 114, 106–115, https://doi.org/10.1016/j.rse.2009.08.014, 2010. a
Wilks, D. S.: Chapter 12 – Principal Component (EOF) Analysis, in:
International Geophysics, edited by Wilks, D. S., vol. 100 of Statistical Methods in the Atmospheric Sciences,
Academic Press, 519–562, https://doi.org/10.1016/B978-0-12-385022-5.00012-9, 2011. a
Wingate, L., Ogée, J., Cremonese, E., Filippa, G., Mizunuma, T.,
Migliavacca, M., Moisy, C., Wilkinson, M., Moureaux, C., Wohlfahrt, G.,
Hammerle, A., Hörtnagl, L., Gimeno, C., Porcar-Castell, A., Galvagno,
M., Nakaji, T., Morison, J., Kolle, O., Knohl, A., Kutsch, W., Kolari, P.,
Nikinmaa, E., Ibrom, A., Gielen, B., Eugster, W., Balzarolo, M., Papale, D.,
Klumpp, K., Köstner, B., Grünwald, T., Joffre, R., Ourcival, J.-M.,
Hellstrom, M., Lindroth, A., George, C., Longdoz, B., Genty, B., Levula, J.,
Heinesch, B., Sprintsin, M., Yakir, D., Manise, T., Guyon, D., Ahrends, H.,
Plaza-Aguilar, A., Guan, J. H., and Grace, J.: Interpreting Canopy
Development and Physiology Using a European Phenology Camera Network at
Flux Sites, Biogeosciences, 12, 5995–6015,
https://doi.org/10.5194/bg-12-5995-2015, 2015.
a
Wolter, K. and Timlin, M. S.: El Niño/Southern Oscillation
Behaviour since 1871 as Diagnosed in an Extended Multivariate ENSO Index
(MEI.Ext), Int. J. Climatol., 31, 1074–1087,
https://doi.org/10.1002/joc.2336, 2011. a
Yan, T., Song, H., Wang, Z., Teramoto, M., Wang, J., Liang, N., Ma, C., Sun,
Z., Xi, Y., Li, L., and Peng, S.: Temperature Sensitivity of Soil Respiration
across Multiple Time Scales in a Temperate Plantation Forest, Sci.
Total Environ., 688, 479–485, https://doi.org/10.1016/j.scitotenv.2019.06.318,
2019. a
Zeileis, A., Leisch, F., Hornik, K., and Kleiber, C.: Strucchange: An R
Package for Testing for Structural Change in Linear Regression
Models, J. Stat. Softw., 7, 1–38,
https://doi.org/10.18637/jss.v007.i02, 2002. a
Zeng, N., Zhao, F., Collatz, G. J., Kalnay, E., Salawitch, R. J., West, T. O.,
and Guanter, L.: Agricultural Green Revolution as a Driver of Increasing
Atmospheric CO2 Seasonal Amplitude, Nature, 515,
394–397, https://doi.org/10.1038/nature13893, 2014. a
Zhang, Q., Phillips, R. P., Manzoni, S., Scott, R. L., Oishi, A. C., Finzi, A.,
Daly, E., Vargas, R., and Novick, K. A.: Changes in Photosynthesis and Soil
Moisture Drive the Seasonal Soil Respiration-Temperature Hysteresis
Relationship, Agr. Forest Meteorol., 259, 184–195,
https://doi.org/10.1016/j.agrformet.2018.05.005, 2018. a
Zhou, L., Tian, Y., Myneni, R. B., Ciais, P., Saatchi, S., Liu, Y. Y., Piao,
S., Chen, H., Vermote, E. F., Song, C., and Hwang, T.: Widespread Decline of
Congo Rainforest Greenness in the Past Decade, Nature, 509, 86–90,
https://doi.org/10.1038/nature13265, 2014. a, b
Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z., Canadell, J. G., Ciais,
P., Sitch, S., Friedlingstein, P., Arneth, A., Cao, C., Cheng, L., Kato, E.,
Koven, C., Li, Y., Lian, X., Liu, Y., Liu, R., Mao, J., Pan, Y., Peng, S.,
Peñuelas, J., Poulter, B., Pugh, T. A. M., Stocker, B. D., Viovy, N., Wang,
X., Wang, Y., Xiao, Z., Yang, H., Zaehle, S., and Zeng, N.: Greening of the
Earth and Its Drivers, Nat. Clim. Change, 6, 791–795,
https://doi.org/10.1038/nclimate3004, 2016. a, b, c, d, e
Short summary
To closely monitor the state of our planet, we require systems that can monitor
the observation of many different properties at the same time. We create
indicators that resemble the behavior of many different simultaneous
observations. We apply the method to create indicators representing the
Earth's biosphere. The indicators show a productivity gradient and a water
gradient. The resulting indicators can detect a large number of changes and
extremes in the Earth system.
To closely monitor the state of our planet, we require systems that can monitor
the observation...
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