Articles | Volume 22, issue 7
https://doi.org/10.5194/bg-22-1907-2025
© Author(s) 2025. 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-22-1907-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Apr 2025
Research article |
| 17 Apr 2025
| 17 Apr 2025
Modelling the effect of climate–substrate interactions on soil organic matter decomposition with the Jena Soil Model
Marleen Pallandt
CORRESPONDING AUTHOR
Max Planck Institute for Biogeochemistry, Jena, Germany
International Max Planck Research School (IMPRS) for Global Biogeochemical Cycles, Jena, Germany
Department of Physical Geography, Stockholm University, Stockholm, Sweden
Marion Schrumpf
Max Planck Institute for Biogeochemistry, Jena, Germany
Holger Lange
Norwegian Institute of Bioeconomy Research, Ås, Norway
Markus Reichstein
Max Planck Institute for Biogeochemistry, Jena, Germany
Department of Earth System Sciences, Hamburg University, Hamburg, Germany
Bernhard Ahrens
Max Planck Institute for Biogeochemistry, Jena, Germany
Related authors
Xiankun Li, Marleen Pallandt, Dilip Naidu, Johannes Rousk, Gustaf Hugelius, and Stefano Manzoni
Biogeosciences, 22, 2691–2705, https://doi.org/10.5194/bg-22-2691-2025, https://doi.org/10.5194/bg-22-2691-2025, 2025
Short summary
Short summary
While laboratory studies have identified many drivers and their effects on the carbon emission pulse after rewetting of dry soils, a validation with field data is still missing. Here, we show that the carbon emission pulse in the laboratory and in the field increases with soil organic carbon and temperature, but their trends with pre-rewetting dryness and moisture increment at rewetting differ. We conclude that the laboratory findings can be partially validated.
Wenli Zhao, Alexander J. Winkler, Markus Reichstein, Rene Orth, and Pierre Gentine
EGUsphere, https://doi.org/10.5194/egusphere-2025-4082, https://doi.org/10.5194/egusphere-2025-4082, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
We used explainable machine learning that incorporates memory effects to study how plants respond to weather and drought. Using data from 90 sites worldwide, we show that memory plays a key role in regulating plant water stress. Forests and savannas rely on longer past conditions than grasslands, reflecting differences in rooting depth and water use. These insights improve our ability to anticipate ecosystem vulnerability as droughts intensify.
Basil Kraft, Jacob A. Nelson, Sophia Walther, Fabian Gans, Ulrich Weber, Gregory Duveiller, Markus Reichstein, Weijie Zhang, Marc Rußwurm, Devis Tuia, Marco Körner, Zayd Hamdi, and Martin Jung
Biogeosciences, 22, 3965–3987, https://doi.org/10.5194/bg-22-3965-2025, https://doi.org/10.5194/bg-22-3965-2025, 2025
Short summary
Short summary
This study evaluates machine learning approaches for upscaling evapotranspiration from the site to the global scale. Sequential models capture temporal dynamics better, especially with precipitation data, but all models show biases in data-scarce regions. Improved upscaling requires richer training data, informed covariate selection, and physical constraints to enhance robustness and reduce extrapolation errors.
Theertha Kariyathan, Ana Bastos, Markus Reichstein, Wouter Peters, and Julia Marshall
Atmos. Chem. Phys., 25, 7863–7878, https://doi.org/10.5194/acp-25-7863-2025, https://doi.org/10.5194/acp-25-7863-2025, 2025
Short summary
Short summary
The carbon uptake period (CUP) is the time period when land absorbs more CO2 than it emits. While atmospheric CO2 mole fraction measurements can be used to assess CUP changes, atmospheric transport and asynchronous timing across regions reduce the accuracy of the estimates. Forward model experiments show that only ~ 50 % of prescribed shifts in CUP timing applied to surface fluxes (ΔCUPNEE) are captured in simulated CO2 mole fraction data at monitoring sites like the Barrow Atmospheric Baseline Observatory.
Zavud Baghirov, Markus Reichstein, Basil Kraft, Bernhard Ahrens, Marco Körner, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2025-3123, https://doi.org/10.5194/egusphere-2025-3123, 2025
Short summary
Short summary
We introduce a new global model that links how water and carbon move through land ecosystems. By combining process knowledge with artificial intelligence that learns from observations, we model daily changes in vegetation, water and carbon cycle processes. This model outperforms both purely data-driven and traditional process models, especially in dry and tropical regions. This advance could improve current understanding of water-carbon cycle relationships.
Laura Nadolski, Tarek S. El-Madany, Jacob Nelson, Arnaud Carrara, Gerardo Moreno, Richard Nair, Yunpeng Luo, Anke Hildebrandt, Victor Rolo, Markus Reichstein, and Sung-Ching Lee
Biogeosciences, 22, 2935–2958, https://doi.org/10.5194/bg-22-2935-2025, https://doi.org/10.5194/bg-22-2935-2025, 2025
Short summary
Short summary
Semi-arid ecosystems are crucial for Earth's carbon balance and are sensitive to changes in nitrogen (N) and phosphorus (P) levels. Their carbon dynamics are complex and not fully understood. We studied how long-term nutrient changes affect carbon exchange. In summer, the addition of N+P changed plant composition and productivity. In transitional seasons, carbon exchange was less weather-dependent with N. The addition of N and N+P increases carbon-exchange variability, driven by grass greenness.
Xiankun Li, Marleen Pallandt, Dilip Naidu, Johannes Rousk, Gustaf Hugelius, and Stefano Manzoni
Biogeosciences, 22, 2691–2705, https://doi.org/10.5194/bg-22-2691-2025, https://doi.org/10.5194/bg-22-2691-2025, 2025
Short summary
Short summary
While laboratory studies have identified many drivers and their effects on the carbon emission pulse after rewetting of dry soils, a validation with field data is still missing. Here, we show that the carbon emission pulse in the laboratory and in the field increases with soil organic carbon and temperature, but their trends with pre-rewetting dryness and moisture increment at rewetting differ. We conclude that the laboratory findings can be partially validated.
Friedrich J. Bohn, Ana Bastos, Romina Martin, Anja Rammig, Niak Sian Koh, Giles B. Sioen, Bram Buscher, Louise Carver, Fabrice DeClerck, Moritz Drupp, Robert Fletcher, Matthew Forrest, Alexandros Gasparatos, Alex Godoy-Faúndez, Gregor Hagedorn, Martin C. Hänsel, Jessica Hetzer, Thomas Hickler, Cornelia B. Krug, Stasja Koot, Xiuzhen Li, Amy Luers, Shelby Matevich, H. Damon Matthews, Ina C. Meier, Mirco Migliavacca, Awaz Mohamed, Sungmin O, David Obura, Ben Orlove, Rene Orth, Laura Pereira, Markus Reichstein, Lerato Thakholi, Peter H. Verburg, and Yuki Yoshida
Biogeosciences, 22, 2425–2460, https://doi.org/10.5194/bg-22-2425-2025, https://doi.org/10.5194/bg-22-2425-2025, 2025
Short summary
Short summary
An interdisciplinary collaboration of 36 international researchers from 35 institutions highlights recent findings in biosphere research. Within eight themes, they discuss issues arising from climate change and other anthropogenic stressors and highlight the co-benefits of nature-based solutions and ecosystem services. Based on an analysis of these eight topics, we have synthesized four overarching insights.
Samuel Upton, Markus Reichstein, Wouter Peters, Santiago Botía, Jacob A. Nelson, Sophia Walther, Martin Jung, Fabian Gans, László Haszpra, and Ana Bastos
EGUsphere, https://doi.org/10.5194/egusphere-2025-2097, https://doi.org/10.5194/egusphere-2025-2097, 2025
Short summary
Short summary
We create a hybrid ecosystem-level carbon flux model using both eddy-covariance observations and observations of the atmospheric mole fraction of CO2 at three tall-tower observatories. Our study uses an atmospheric transport model (STILT) to connect the atmospheric signal to the ecosystem-level model. We show that this inclusion of atmospheric information meaningfully improves the model's representation of the interannual variability of the global net flux of CO2.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
Geosci. Model Dev., 18, 2921–2943, https://doi.org/10.5194/gmd-18-2921-2025, https://doi.org/10.5194/gmd-18-2921-2025, 2025
Short summary
Short summary
We use an innovative approach to studying the Earth's water cycle by integrating advanced machine learning techniques with a traditional water cycle model. Our model is designed to learn from observational data, with a particular emphasis on understanding the influence of vegetation on water movement. By closely aligning with real-world observations, our model offers new possibilities for enhancing our understanding of the water cycle and its interactions with vegetation.
Na Li, Sebastian Sippel, Nora Linscheid, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
EGUsphere, https://doi.org/10.5194/egusphere-2025-1924, https://doi.org/10.5194/egusphere-2025-1924, 2025
Short summary
Short summary
The global land carbon sink has increased since the pre-industrial period, mainly caused by increasing atmospheric CO2 emissions and climate change. However, the large year-to-year variations can mask or amplify this trend. Here, we detect the time for the anthropogenic signal to emerge over natural variations in land carbon sink. We removed the circulation-induced variations in the global land carbon sink and effectively reduced the detection time of anthropogenic signal.
Marijn Van de Broek, Gerard Govers, Marion Schrumpf, and Johan Six
Biogeosciences, 22, 1427–1446, https://doi.org/10.5194/bg-22-1427-2025, https://doi.org/10.5194/bg-22-1427-2025, 2025
Short summary
Short summary
Soil organic carbon models are used to predict how soils affect the concentration of CO2 in the atmosphere. We show that equifinality – the phenomenon that different parameter values lead to correct overall model outputs, albeit with a different model behaviour – is an important source of model uncertainty. Our results imply that adding more complexity to soil organic carbon models is unlikely to lead to better predictions as long as more data to constrain model parameters are not available.
Wenli Zhao, Alexander J. Winkler, Markus Reichstein, Rene Orth, and Pierre Gentine
EGUsphere, https://doi.org/10.5194/egusphere-2025-365, https://doi.org/10.5194/egusphere-2025-365, 2025
Preprint archived
Short summary
Short summary
We developed a machine learning model that accounts for the memory effects of soil moisture and vegetation to predict Evaporative Fraction (EF) without relying on soil moisture as a direct input. The model accurately predicts EF during dry periods for the unseen sites, highlighting the key of meteorological memory effects. The learned memory effect related to rooting depth and soil water holding capacity could potentially serve as proxies for assessing the plant water stress.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
Short summary
Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Jasper M. C. Denissen, Adriaan J. Teuling, Sujan Koirala, Markus Reichstein, Gianpaolo Balsamo, Martha M. Vogel, Xin Yu, and René Orth
Earth Syst. Dynam., 15, 717–734, https://doi.org/10.5194/esd-15-717-2024, https://doi.org/10.5194/esd-15-717-2024, 2024
Short summary
Short summary
Heat extremes have severe implications for human health and ecosystems. Heat extremes are mostly introduced by large-scale atmospheric circulation but can be modulated by vegetation. Vegetation with access to water uses solar energy to evaporate water into the atmosphere. Under dry conditions, water may not be available, suppressing evaporation and heating the atmosphere. Using climate projections, we show that regionally less water is available for vegetation, intensifying future heat extremes.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
Short summary
Short summary
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Sinikka J. Paulus, Rene Orth, Sung-Ching Lee, Anke Hildebrandt, Martin Jung, Jacob A. Nelson, Tarek Sebastian El-Madany, Arnaud Carrara, Gerardo Moreno, Matthias Mauder, Jannis Groh, Alexander Graf, Markus Reichstein, and Mirco Migliavacca
Biogeosciences, 21, 2051–2085, https://doi.org/10.5194/bg-21-2051-2024, https://doi.org/10.5194/bg-21-2051-2024, 2024
Short summary
Short summary
Porous materials are known to reversibly trap water from the air, even at low humidity. However, this behavior is poorly understood for soils. In this analysis, we test whether eddy covariance is able to measure the so-called adsorption of atmospheric water vapor by soils. We find that this flux occurs frequently during dry nights in a Mediterranean ecosystem, while EC detects downwardly directed vapor fluxes. These results can help to map moisture uptake globally.
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
Short summary
Short summary
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.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Samuel Upton, Markus Reichstein, Fabian Gans, Wouter Peters, Basil Kraft, and Ana Bastos
Atmos. Chem. Phys., 24, 2555–2582, https://doi.org/10.5194/acp-24-2555-2024, https://doi.org/10.5194/acp-24-2555-2024, 2024
Short summary
Short summary
Data-driven eddy-covariance upscaled estimates of the global land–atmosphere net CO2 exchange (NEE) show important mismatches with regional and global estimates based on atmospheric information. To address this, we create a model with a dual constraint based on bottom-up eddy-covariance data and top-down atmospheric inversion data. Our model overcomes shortcomings of each approach, producing improved NEE estimates from local to global scale, helping to reduce uncertainty in the carbon budget.
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
Preprint archived
Short summary
Short summary
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.
Shane W. Stoner, Marion Schrumpf, Alison Hoyt, Carlos A. Sierra, Sebastian Doetterl, Valier Galy, and Susan Trumbore
Biogeosciences, 20, 3151–3163, https://doi.org/10.5194/bg-20-3151-2023, https://doi.org/10.5194/bg-20-3151-2023, 2023
Short summary
Short summary
Soils store more carbon (C) than any other terrestrial C reservoir, but the processes that control how much C stays in soil, and for how long, are very complex. Here, we used a recent method that involves heating soil in the lab to measure the range of C ages in soil. We found that most C in soil is decades to centuries old, while some stays for much shorter times (days to months), and some is thousands of years old. Such detail helps us to estimate how soil C may react to changing climate.
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
Short summary
Short summary
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
Short summary
Short summary
We spatially attribute the variance in global terrestrial water storage (TWS) interannual variability (IAV) and its modeling error with two data-driven hydrological models. We find error hotspot regions that show a disproportionately large significance in the global mismatch and the association of the error regions with a smaller-scale lateral convergence of water. Our findings imply that TWS IAV modeling can be efficiently improved by focusing on model representations for the error hotspots.
Robert Vautard, Geert Jan van Oldenborgh, Rémy Bonnet, Sihan Li, Yoann Robin, Sarah Kew, Sjoukje Philip, Jean-Michel Soubeyroux, Brigitte Dubuisson, Nicolas Viovy, Markus Reichstein, Friederike Otto, and Iñaki Garcia de Cortazar-Atauri
Nat. Hazards Earth Syst. Sci., 23, 1045–1058, https://doi.org/10.5194/nhess-23-1045-2023, https://doi.org/10.5194/nhess-23-1045-2023, 2023
Short summary
Short summary
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 %].
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
Short summary
Short summary
In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
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
Short summary
Short summary
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.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
Short summary
Short summary
Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Jeffrey Prescott Beem-Miller, Craig Rasmussen, Alison May Hoyt, Marion Schrumpf, Georg Guggenberger, and Susan Trumbore
EGUsphere, https://doi.org/10.5194/egusphere-2022-1083, https://doi.org/10.5194/egusphere-2022-1083, 2022
Preprint withdrawn
Short summary
Short summary
We compared the age of persistent soil organic matter as well as active emissions of carbon dioxide from soils across a gradient of climate and geology. We found that clay minerals are more important than mean annual temperature for both persistent and actively cycling soil carbon, and that they may attenuate the sensitivity of soil organic matter decomposition to temperature. Accounting for geology and soil development could therefore improve estimates of soil carbon stocks and changes.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
Identifying drought legacy effects is challenging because they are superimposed on variability driven by climate conditions in the recovery period. We develop a residual-based approach to quantify legacies on gross primary productivity (GPP) from eddy covariance data. The GPP reduction due to legacy effects is comparable to the concurrent effects at two sites in Germany, which reveals the importance of legacy effects. Our novel methodology can be used to quantify drought legacies elsewhere.
Rachael Akinyede, Martin Taubert, Marion Schrumpf, Susan Trumbore, and Kirsten Küsel
Biogeosciences, 19, 4011–4028, https://doi.org/10.5194/bg-19-4011-2022, https://doi.org/10.5194/bg-19-4011-2022, 2022
Short summary
Short summary
Soils will likely become warmer in the future, and this can increase the release of carbon dioxide (CO2) into the atmosphere. As microbes can take up soil CO2 and prevent further escape into the atmosphere, this study compares the rate of uptake and release of CO2 at two different temperatures. With warming, the rate of CO2 uptake increases less than the rate of release, indicating that the capacity to modulate soil CO2 release into the atmosphere will decrease under future warming.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Marion Schrumpf, Klaus Kaiser, Allegra Mayer, Günter Hempel, and Susan Trumbore
Biogeosciences, 18, 1241–1257, https://doi.org/10.5194/bg-18-1241-2021, https://doi.org/10.5194/bg-18-1241-2021, 2021
Short summary
Short summary
A large amount of organic carbon (OC) in soil is protected against decay by bonding to minerals. We studied the release of mineral-bonded OC by NaF–NaOH extraction and H2O2 oxidation. Unexpectedly, extraction and oxidation removed mineral-bonded OC at roughly constant portions and of similar age distributions, irrespective of mineral composition, land use, and soil depth. The results suggest uniform modes of interactions between OC and minerals across soils in quasi-steady state with inputs.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
Short summary
Short summary
Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Abramoff, R., Davidson, E., and Finzi, A. C.: A parsimonious modular approach to building a mechanistic belowground carbon and nitrogen model, J. Geophys. Res.-Biogeo., 122, 2418–2434, https://doi.org/10.1002/2017JG003796, 2017.
Abramoff, R. Z., Torn, M. S., Georgiou, K., Tang, J., and Riley, W. J.: Soil Organic Matter Temperature Sensitivity Cannot be Directly Inferred From Spatial Gradients, Glob. Change Biol., 33, 761–776, https://doi.org/10.1029/2018GB006001, 2019.
Ahrens, B., Braakhekke, M. C., Guggenberger, G., Schrumpf, M., and Reichstein, M.: Contribution of sorption, DOC transport and microbial interactions to the 14C age of a soil organic carbon profile: Insights from a calibrated process model, Soil Biol. Biochem., 88, 390–402, https://doi.org/10.1016/j.soilbio.2015.06.008, 2015.
Ahrens, B., Guggenberger, G., Rethemeyer, J., John, S., Marschner, B., Heinze, S., Angst, G., Mueller, C. W., Kögel-Knabner, I., Leuschner, C., Hertel, D., Bachmann, J., Reichstein, M., and Schrumpf, M.: Combination of energy limitation and sorption capacity explains 14C depth gradients, Soil Biol. Biochem., 148, 107912, https://doi.org/10.1016/j.soilbio.2020.107912, 2020.
Allison, S. D., Wallenstein, M. D., and Bradford, M. A.: Soil-carbon response to warming dependent on microbial physiology, Nat. Geosci., 3, 336, https://doi.org/10.1038/ngeo846, 2010.
Allison, S. D., Romero-Olivares, A. L., Lu, L., Taylor, J. W., and Treseder, K. K.: Temperature acclimation and adaptation of enzyme physiology in Neurospora discreta, Fungal Ecol., 35, 78–86, https://doi.org/10.1016/j.funeco.2018.07.005, 2018a.
Allison, S. D., Romero-Olivares, A. L., Lu, Y., Taylor, J. W., and Treseder, K. K.: Temperature sensitivities of extracellular enzyme Vmax and Km across thermal environments, Glob. Change Biol., 24, 2884–2897, https://doi.org/10.1111/gcb.14045, 2018b.
Bauer, J., Herbst, M., Huisman, J. A., Weihermüller, L., and Vereecken, H.: Sensitivity of simulated soil heterotrophic respiration to temperature and moisture reduction functions, Geoderma, 145, 17–27, https://doi.org/10.1016/j.geoderma.2008.01.026, 2008.
Benbi, D. K., Boparai, A. K., and Brar, K.: Decomposition of particulate organic matter is more sensitive to temperature than the mineral associated organic matter, Soil Biol. Biochem., 70, 183–192, https://doi.org/10.1016/j.soilbio.2013.12.032, 2014.
Berg, A. and Sheffield, J.: Climate Change and Drought: the Soil Moisture Perspective, Curr. Clim. Change Rep., 4, 180–191, https://doi.org/10.1007/s40641-018-0095-0, 2018.
Berg, A., Sheffield, J., and Milly, P. C. D.: Divergent surface and total soil moisture projections under global warming, Geophys. Res. Lett., 44, 236–244, https://doi.org/10.1002/2016GL071921, 2017.
Blankinship, J. C. and Schimel, J. P.: Biotic versus Abiotic Controls on Bioavailable Soil Organic Carbon, Soil Syst., 2, 10, https://doi.org/10.3390/soilsystems2010010, 2018.
Blume, H.-P., Brümmer, G. W., Fleige, H., Horn, R., Kandeler, E., Kögel-Knabner, I., Kretzschmar, R., Stahr, K., and Wilke, B.-M.: Soil Organic Matter, in: Scheffer/SchachtschabelSoil Science, edited by: Blume, H.-P., Brümmer, G. W., Fleige, H., Horn, R., Kandeler, E., Kögel-Knabner, I., Kretzschmar, R., Stahr, K., and Wilke, B.-M., Springer Berlin Heidelberg, Berlin, Heidelberg, 55–86, https://doi.org/10.1007/978-3-642-30942-7_3, 2016.
Bosatta, E. and Ågren, G. I.: Soil organic matter quality interpreted thermodynamically, Soil Biol. Biochem., 31, 1889–1891, https://doi.org/10.1016/S0038-0717(99)00105-4, 1999.
Bradford, M. A., Wieder, W. R., Bonan, G. B., Fierer, N., Raymond, P. A., and Crowther, T. W.: Managing uncertainty in soil carbon feedbacks to climate change, Nat. Clim. Change, 6, 751–758, https://doi.org/10.1038/nclimate3071, 2016.
Bradford, M. A., McCulley, R. L., Crowther, T. W., Oldfield, E. E., Wood, S. A., and Fierer, N.: Cross-biome patterns in soil microbial respiration predictable from evolutionary theory on thermal adaptation, Nat. Ecol. Evol., 3, 223–231, https://doi.org/10.1038/s41559-018-0771-4, 2019.
Braghiere, R. K., Fisher, J. B., Allen, K., Brzostek, E., Shi, M., Yang, X., Ricciuto, D. M., Fisher, R. A., Zhu, Q., and Phillips, R. P.: Modeling Global Carbon Costs of Plant Nitrogen and Phosphorus Acquisition, J. Adv. Model. Earth Syst., 14, e2022MS003204, https://doi.org/10.1029/2022MS003204, 2022.
Brunn, M., Krüger, J., and Lang, F.: Experimental drought increased the belowground sink strength towards higher topsoil organic carbon stocks in a temperate mature forest, Geoderma, 431, 116356, https://doi.org/10.1016/j.geoderma.2023.116356, 2023.
Buckeridge, K. M., Creamer, C., and Whitaker, J.: Deconstructing the microbial necromass continuum to inform soil carbon sequestration, Funct. Ecol., 36, 1396–1410, https://doi.org/10.1111/1365-2435.14014, 2022.
Carey, J. C., Tang, J., Templer, P. H., Kroeger, K. D., Crowther, T. W., Burton, A. J., Dukes, J. S., Emmett, B., Frey, S. D., Heskel, M. A., Jiang, L., Machmuller, M. B., Mohan, J., Panetta, A. M., Reich, P. B., Reinsch, S., Wang, X., Allison, S. D., Bamminger, C., Bridgham, S., Collins, S. L., de Dato, G., Eddy, W. C., Enquist, B. J., Estiarte, M., Harte, J., Henderson, A., Johnson, B. R., Larsen, K. S., Luo, Y., Marhan, S., Melillo, J. M., Penuelas, J., Pfeifer-Meister, L., Poll, C., Rastetter, E., Reinmann, A. B., Reynolds, L. L., Schmidt, I. K., Shaver, G. R., Strong, A. L., Suseela, V., and Tietema, A.: Temperature response of soil respiration largely unaltered with experimental warming, P. Natl. Acad. Sci. USA, 113, 13797–13802, https://doi.org/10.1073/pnas.1605365113, 2016.
Chen, Y., Qin, W., Zhang, Q., Wang, X., Feng, J., Han, M., Hou, Y., Zhao, H., Zhang, Z., He, J.-S., Torn, M. S., and Zhu, B.: Whole-soil warming leads to substantial soil carbon emission in an alpine grassland, Nat. Commun., 15, 4489, https://doi.org/10.1038/s41467-024-48736-w, 2024.
Conant, R. T., Ryan, M. G., Ågren, G. I., Birge, H. E., Davidson, E. A., Eliasson, P. E., Evans, S. E., Frey, S. D., Giardina, C. P., Hopkins, F. M., Hyvönen, R., Kirschbaum, M. U. F., Lavallee, J. M., Leifeld, J., Parton, W. J., Megan Steinweg, J., Wallenstein, M. D., Martin Wetterstedt, J. Å., and Bradford, M. A.: Temperature and soil organic matter decomposition rates – synthesis of current knowledge and a way forward, Glob. Change Biol., 17, 3392–3404, https://doi.org/10.1111/j.1365-2486.2011.02496.x, 2011.
Cook, B. I., Mankin, J. S., Marvel, K., Williams, A. P., Smerdon, J. E., and Anchukaitis, K. J.: Twenty-First Century Drought Projections in the CMIP6 Forcing Scenarios, Earths Future, 8, e2019EF001461, https://doi.org/10.1029/2019EF001461, 2020.
Cotrufo, M. F. and Lavallee, J. M.: Chapter One – Soil organic matter formation, persistence, and functioning: A synthesis of current understanding to inform its conservation and regeneration, in: Advances in Agronomy, vol. 172, edited by: Sparks, D. L., Academic Press, 1–66, https://doi.org/10.1016/bs.agron.2021.11.002, 2022.
Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K., and Paul, E.: The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter?, Glob. Change Biol., 19, 988–995, https://doi.org/10.1111/gcb.12113, 2013.
Crowther, T. W., van den Hoogen, J., Wan, J., Mayes, M. A., Keiser, A. D., Mo, L., Averill, C., and Maynard, D. S.: The global soil community and its influence on biogeochemistry, Science, 365, eaav0550, https://doi.org/10.1126/science.aav0550, 2019.
Davidson, E. A.: Carbon dioxide loss from tropical soils increases on warming, Nature, 584, 198–199, https://doi.org/10.1038/d41586-020-02266-9, 2020.
Davidson, E. A. and Janssens, I. A.: Temperature sensitivity of soil carbon decomposition and feedbacks to climate change, Nature, 440, 165, https://doi.org/10.1038/nature04514, 2006.
Davidson, E. A., Janssens, I. A., and Luo, Y.: On the variability of respiration in terrestrial ecosystems: moving beyond Q10, Glob. Change Biol., 12, 154–164, https://doi.org/10.1111/j.1365-2486.2005.01065.x, 2006.
Davidson, E. A., Sudeep, S., Samantha, S. C., and Savage, K.: The Dual Arrhenius and Michaelis–Menten kinetics model for decomposition of soil organic matter at hourly to seasonal time scales, Glob. Change Biol., 18, 371–384, https://doi.org/10.1111/j.1365-2486.2011.02546.x, 2012.
Deng, L., Peng, C., Kim, D.-G., Li, J., Liu, Y., Hai, X., Liu, Q., Huang, C., Shangguan, Z., and Kuzyakov, Y.: Drought effects on soil carbon and nitrogen dynamics in global natural ecosystems, Earth-Sci. Rev., 214, 103501, https://doi.org/10.1016/j.earscirev.2020.103501, 2021.
Dwivedi, D., Riley, W. J., Torn, M. S., Spycher, N., Maggi, F., and Tang, J. Y.: Mineral properties, microbes, transport, and plant-input profiles control vertical distribution and age of soil carbon stocks, Soil Biol. Biochem., 107, 244–259, https://doi.org/10.1016/j.soilbio.2016.12.019, 2017.
Fan, K., Slater, L., Zhang, Q., Sheffield, J., Gentine, P., Sun, S., and Wu, W.: Climate warming accelerates surface soil moisture drying in the Yellow River Basin, China, J. Hydrol., 615, 128735, https://doi.org/10.1016/j.jhydrol.2022.128735, 2022.
Fan, N., Koirala, S., Reichstein, M., Thurner, M., Avitabile, V., Santoro, M., Ahrens, B., Weber, U., and Carvalhais, N.: Apparent ecosystem carbon turnover time: uncertainties and robust features, Earth Syst. Sci. Data, 12, 2517–2536, https://doi.org/10.5194/essd-12-2517-2020, 2020.
Fanin, N., Mooshammer, M., Sauvadet, M., Meng, C., Alvarez, G., Bernard, L., Bertrand, I., Blagodatskaya, E., Bon, L., Fontaine, S., Niu, S., Lashermes, G., Maxwell, T. L., Weintraub, M. N., Wingate, L., Moorhead, D., and Nottingham, A. T.: Soil enzymes in response to climate warming: Mechanisms and feedbacks, Funct. Ecol., 36, 1378–1395, https://doi.org/10.1111/1365-2435.14027, 2022.
García-García, A., Cuesta-Valero, F. J., Miralles, D. G., Mahecha, M. D., Quaas, J., Reichstein, M., Zscheischler, J., and Peng, J.: Soil heat extremes can outpace air temperature extremes, Nat. Clim. Change, 13, 1237–1241, https://doi.org/10.1038/s41558-023-01812-3, 2023.
Garnier, S., Ross, N., boB Rudis, Filipovic-Pierucci, A., Galili, T., Timelyportfolio, O'Callaghan, A., Greenwell, B., Sievert, C., Harris, D. J., Sciaini, M., and Chen, J. J.: sjmgarnier/viridis: CRAN release v0.6.3, Zenodo [software], https://doi.org/10.5281/ZENODO.4679423, 2023.
Gentsch, N., Wild, B., Mikutta, R., Čapek, P., Diáková, K., Schrumpf, M., Turner, S., Minnich, C., Schaarschmidt, F., Shibistova, O., Schnecker, J., Urich, T., Gittel, A., Šantrůčková, H., Bárta, J., Lashchinskiy, N., Fuß, R., Richter, A., and Guggenberger, G.: Temperature response of permafrost soil carbon is attenuated by mineral protection, Glob. Change Biol., 24, 3401–3415, https://doi.org/10.1111/gcb.14316, 2018.
Georgiou, K., Koven, C. D., Wieder, W. R., Hartman, M. D., Riley, W. J., Pett-Ridge, J., Bouskill, N. J., Abramoff, R. Z., Slessarev, E. W., Ahlström, A., Parton, W. J., Pellegrini, A. F. A., Pierson, D., Sulman, B. N., Zhu, Q., and Jackson, R. B.: Emergent temperature sensitivity of soil organic carbon driven by mineral associations, Nat. Geosci., 17, 205–212, https://doi.org/10.1038/s41561-024-01384-7, 2024.
Gershenson, A., Bader, N. E., and Cheng, W.: Effects of substrate availability on the temperature sensitivity of soil organic matter decomposition, Glob. Change Biol., 15, 176–183, https://doi.org/10.1111/j.1365-2486.2008.01827.x, 2009.
Ghezzehei, T. A., Sulman, B., Arnold, C. L., Bogie, N. A., and Berhe, A. A.: On the role of soil water retention characteristic on aerobic microbial respiration, Biogeosciences, 16, 1187–1209, https://doi.org/10.5194/bg-16-1187-2019, 2019.
Gillabel, J., Cebrian-Lopez, B., Six, J., and Merckx, R.: Experimental evidence for the attenuating effect of SOM protection on temperature sensitivity of SOM decomposition, Glob. Change Biol., 16, 2789–2798, https://doi.org/10.1111/j.1365-2486.2009.02132.x, 2010.
Hao, W., Xia, B., Li, J., and Xu, M.: Deep soil CO2 flux with strong temperature dependence contributes considerably to soil-atmosphere carbon flux, Ecol. Inform., 74, 101957, https://doi.org/10.1016/j.ecoinf.2022.101957, 2023.
Hartley, I. P., Hill, T. C., Chadburn, S. E., and Hugelius, G.: Temperature effects on carbon storage are controlled by soil stabilisation capacities, Nat. Commun., 12, 6713, https://doi.org/10.1038/s41467-021-27101-1, 2021.
Hicks Pries, C., Ryals, R., Zhu, B., Min, K., Cooper, A., Goldsmith, S., Pett-Ridge, J., Torn, M., and Asefaw Berhe, A.: The Deep Soil Organic Carbon Response to Global Change, Annu. Rev. Ecol. Evol. Syst., 54, 375–401, https://doi.org/10.1146/annurev-ecolsys-102320-085332, 2023.
Hicks Pries, C. E., Castanha, C., Porras, R., and Torn, M. S.: The whole-soil carbon flux in response to warming, Science, 355, 1420–1423, https://doi.org/10.1126/science.aal1319, 2017.
Hsu, H. and Dirmeyer, P. A.: Uncertainty in Projected Critical Soil Moisture Values in CMIP6 Affects the Interpretation of a More Moisture-Limited World, Earths Future, 11, e2023EF003511, https://doi.org/10.1029/2023EF003511, 2023.
Jarvis, N. J., Taylor, A., Larsbo, M., Etana, A., and Rosén, K.: Modelling the effects of bioturbation on the re-distribution of 137Cs in an undisturbed grassland soil, Eur. J. Soil Sci., 61, 24–34, https://doi.org/10.1111/j.1365-2389.2009.01209.x, 2010.
Kallenbach, C. M., Frey, S. D., and Grandy, A. S.: Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls, Nat. Commun., 7, 13630, https://doi.org/10.1038/ncomms13630, 2016.
Kirschbaum, M. U. F.: The temperature dependence of organic-matter decomposition–still a topic of debate, Soil Biol. Biochem., 38, 2510–2518, https://doi.org/10.1016/j.soilbio.2006.01.030, 2006.
Koven, C. D., Hugelius, G., Lawrence, D. M., and Wieder, W. R.: Higher climatological temperature sensitivity of soil carbon in cold than warm climates, Nat. Clim. Change, 7, 817–822, https://doi.org/10.1038/nclimate3421, 2017.
Le Noë, J., Manzoni, S., Abramoff, R., Bölscher, T., Bruni, E., Cardinael, R., Ciais, P., Chenu, C., Clivot, H., Derrien, D., Ferchaud, F., Garnier, P., Goll, D., Lashermes, G., Martin, M., Rasse, D., Rees, F., Sainte-Marie, J., Salmon, E., Schiedung, M., Schimel, J., Wieder, W., Abiven, S., Barré, P., Cécillon, L., and Guenet, B.: Soil organic carbon models need independent time-series validation for reliable prediction, Commun. Earth Environ., 4, 1–8, https://doi.org/10.1038/s43247-023-00830-5, 2023.
Li, J., Pei, J., Pendall, E., Reich, P. B., Noh, N. J., Li, B., Fang, C., and Nie, M.: Rising Temperature May Trigger Deep Soil Carbon Loss Across Forest Ecosystems, Adv. Sci., 7, 2001242, https://doi.org/10.1002/advs.202001242, 2020.
Liang, C., Schimel, J. P., and Jastrow, J. D.: The importance of anabolism in microbial control over soil carbon storage, Nat. Microbiol., 2, 1–6, https://doi.org/10.1038/nmicrobiol.2017.105, 2017.
Liang, J., Wang, G., Singh, S., Jagadamma, S., Gu, L., Schadt, C. W., Wood, J. D., Hanson, P. J., and Mayes, M. A.: Intensified Soil Moisture Extremes Decrease Soil Organic Carbon Decomposition: A Mechanistic Modeling Analysis, J. Geophys. Res.-Biogeo., 126, e2021JG006392, https://doi.org/10.1029/2021JG006392, 2021.
Liu, C., Tian, H., Gu, X., Li, N., Zhao, X., Lei, M., Alharbi, H., Megharaj, M., He, W., and Kuzyakov, Y.: Catalytic efficiency of soil enzymes explains temperature sensitivity: Insights from physiological theory, Sci. Total Environ., 822, 153365, https://doi.org/10.1016/j.scitotenv.2022.153365, 2022.
Liu, Y., Tian, J., He, N., and Tiemann, L.: Global microbial necromass contribution to soil organic matter, https://doi.org/10.21203/rs.3.rs-473688/v1, preprint, 2021.
Manzoni, S., Schaeffer, S. M., Katul, G., Porporato, A., and Schimel, J. P.: A theoretical analysis of microbial eco-physiological and diffusion limitations to carbon cycling in drying soils, Soil Biol. Biochem., 73, 69–83, https://doi.org/10.1016/j.soilbio.2014.02.008, 2014.
Meier, I. C. and Leuschner, C.: Variation of soil and biomass carbon pools in beech forests across a precipitation gradient, Glob. Change Biol., 16, 1035–1045, https://doi.org/10.1111/j.1365-2486.2009.02074.x, 2010.
Michaelis, L. and Menten, M. L.: Michaelis: Die kinetik der invertinwirkung, Biochem. Z., 49, 33–369, 1913.
Moinet, G. Y. K., Moinet, M., Hunt, J. E., Rumpel, C., Chabbi, A., and Millard, P.: Temperature sensitivity of decomposition decreases with increasing soil organic matter stability, Sci. Total Env., 704, 135460, https://doi.org/10.1016/j.scitotenv.2019.135460, 2020.
Moyano, F. E., Manzoni, S., and Chenu, C.: Responses of soil heterotrophic respiration to moisture availability: An exploration of processes and models, Soil Biol. Biochem., 59, 72–85, https://doi.org/10.1016/j.soilbio.2013.01.002, 2013.
Moyano, F. E., Vasilyeva, N., and Menichetti, L.: Diffusion limitations and Michaelis–Menten kinetics as drivers of combined temperature and moisture effects on carbon fluxes of mineral soils, Biogeosciences, 15, 5031–5045, https://doi.org/10.5194/bg-15-5031-2018, 2018.
Nottingham, A. T., Turner, B. L., Whitaker, J., Ostle, N., Bardgett, R. D., McNamara, N. P., Salinas, N., and Meir, P.: Temperature sensitivity of soil enzymes along an elevation gradient in the Peruvian Andes, Biogeochemistry, 127, 217–230, https://doi.org/10.1007/s10533-015-0176-2, 2016.
Ofiti, N. O. E., Zosso, C. U., Soong, J. L., Solly, E. F., Torn, M. S., Wiesenberg, G. L. B., and Schmidt, M. W. I.: Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter, Soil Biol. Biochem., 156, 108185, https://doi.org/10.1016/j.soilbio.2021.108185, 2021.
Pallandt, M., Ahrens, B., Koirala, S., Lange, H., Reichstein, M., Schrumpf, M., and Zaehle, S.: Vertically Divergent Responses of SOC Decomposition to Soil Moisture in a Changing Climate, J. Geophys. Res.-Biogeo., 127, e2021JG006684, https://doi.org/10.1029/2021JG006684, 2022.
Parton, W. J., Scurlock, J. M. O., Ojima, D. S., Gilmanov, T. G., Scholes, R. J., Schimel, D. S., Kirchner, T., Menaut, J.-C., Seastedt, T., Garcia Moya, E., Kamnalrut, A., and Kinyamario, J. I.: Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide, Glob. Change Biol., 7, 785–809, https://doi.org/10.1029/93GB02042, 1993.
Posit team. RStudio: Integrated Development Environment for R, version 2024.04.01. Posit Software, PBC, Boston, MA [software], https://docs.posit.co/previous-versions/rstudio.html#section-6 (last access: 25 March 2025), 2024.
Qin, S., Chen, L., Fang, K., Zhang, Q., Wang, J., Liu, F., Yu, J., and Yang, Y.: Temperature sensitivity of SOM decomposition governed by aggregate protection and microbial communities, Sci. Adv., 5, eaau1218, https://doi.org/10.1126/sciadv.aau1218, 2019.
R Core Team: R: A language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, version 4.3.1, [software], https://cran.r-project.org/bin/windows/base/old/4.3.1/ (last access: 21 March 2025), 2023.
Reichstein, M., Subke, J.-A., Angeli, A. C., and Tenhunen, J. D.: Does the temperature sensitivity of decomposition of soil organic matter depend upon water content, soil horizon, or incubation time?, Glob. Change Biol., 11, 1754–1767, https://doi.org/10.1111/j.1365-2486.2005.001010.x, 2005.
Saifuddin, M., Abramoff, R. Z., Davidson, E. A., Dietze, M. C., and Finzi, A. C.: Identifying Data Needed to Reduce Parameter Uncertainty in a Coupled Microbial Soil C and N Decomposition Model, J. Geophys. Res.-Biogeo., 126, e2021JG006593, https://doi.org/10.1029/2021JG006593, 2021.
Schimel, J. P.: Life in Dry Soils: Effects of Drought on Soil Microbial Communities and Processes, Annu. Rev. Ecol. Evol. Syst., 49, 409–432, https://doi.org/10.1146/annurev-ecolsys-110617-062614, 2018.
Schmidt, M. W. I., Torn, M. S., Abiven, S., Dittmar, T., Guggenberger, G., Janssens, I. A., Kleber, M., Kögel-Knabner, I., Lehmann, J., Manning, D. A. C., Nannipieri, P., Rasse, D. P., Weiner, S., and Trumbore, S. E.: Persistence of soil organic matter as an ecosystem property, Nature, 478, 49, https://doi.org/10.1038/nature10386, 2011.
Sierra, C. A., Trumbore, S. E., Davidson, E. A., Vicca, S., and Janssens, I.: Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture, J. Adv. Model. Earth Syst., 7, 335–356, https://doi.org/10.1002/2014MS000358, 2015.
Skopp, J., Jawson, M. D., and Doran, J. W.: Steady-state aerobic microbial activity as a function of soil water content, Soil Sci. Soc. Am. J., 54, 1619–1625, https://doi.org/10.2136/sssaj1990.03615995005400060018x, 1990.
Sokol, N. W., Whalen, E. D., Jilling, A., Kallenbach, C., Pett-Ridge, J., and Georgiou, K.: Global distribution, formation and fate of mineral-associated soil organic matter under a changing climate: A trait-based perspective, Funct. Ecol., 36, 1411–1429, https://doi.org/10.1111/1365-2435.14040, 2022.
Soong, J. L., Phillips, C. L., Ledna, C., Koven, C. D., and Torn, M. S.: CMIP5 Models Predict Rapid and Deep Soil Warming Over the 21st Century, J. Geophys. Res.-Biogeo., 125, e2019JG005266, https://doi.org/10.1029/2019JG005266, 2020.
Soong, J. L., Castanha, C., Hicks Pries, C. E., Ofiti, N., Porras, R. C., Riley, W. J., Schmidt, M. W. I., and Torn, M. S.: Five years of whole-soil warming led to loss of subsoil carbon stocks and increased CO2 efflux, Sci. Adv., 7, eabd1343, https://doi.org/10.1126/sciadv.abd1343, 2021.
Stone, M. M., Weiss, M. S., Goodale, C. L., Adams, M. B., Fernandez, I. J., German, D. P., and Allison, S. D.: Temperature sensitivity of soil enzyme kinetics under -fertilization in two temperate forests, Glob. Change Biol., 18, 1173–1184, https://doi.org/10.1111/j.1365-2486.2011.02545.x, 2012.
Subke, J.-A. and Bahn, M.: On the “temperature sensitivity” of soil respiration: Can we use the immeasurable to predict the unknown?, Soil Biol. Biochem., 42, 1653–1656, https://doi.org/10.1016/j.soilbio.2010.05.026, 2010.
Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E., and Pacala, S. W.: Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2, Nat. Clim. Change, 4, 1099, https://doi.org/10.1038/nclimate2436, 2014.
Sulman, B. N., Moore, J. A. M., Abramoff, R., Averill, C., Kivlin, S., Georgiou, K., Sridhar, B., Hartman, M. D., Wang, G., Wieder, W. R., Bradford, M. A., Luo, Y., Mayes, M. A., Morrison, E., Riley, W. J., Salazar, A., Schimel, J. P., Tang, J., and Classen, A. T.: Multiple models and experiments underscore large uncertainty in soil carbon dynamics, Biogeochemistry, 141, 109–123, https://doi.org/10.1007/s10533-018-0509-z, 2018.
Tang, J. and Riley, W. J.: Weaker soil carbon–climate feedbacks resulting from microbial and abiotic interactions, Nat. Clim. Change, 5, 56–60, https://doi.org/10.1038/nclimate2438, 2015.
Tang, J. and Riley, W. J.: Competitor and substrate sizes and diffusion together define enzymatic depolymerization and microbial substrate uptake rates, Soil Biol. Biochem., 139, 107624, https://doi.org/10.1016/j.soilbio.2019.107624, 2019.
Tang, J. and Riley, W. J.: A chemical kinetics theory for interpreting the non-monotonic temperature dependence of enzymatic reactions, Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, 2024.
Tang, J., Bradford, M. A., Carey, J., Crowther, T. W., Machmuller, M. B., Mohan, J. E., and Todd-Brown, K.: Chapter 8 – Temperature sensitivity of soil carbon, in: Ecosystem Consequences of Soil Warming, edited by: Mohan, J. E., Academic Press, 175–208, https://doi.org/10.1016/B978-0-12-813493-1.00009-0, 2019.
Tang, J. Y.: On the relationships between the Michaelis–Menten kinetics, reverse Michaelis–Menten kinetics, equilibrium chemistry approximation kinetics, and quadratic kinetics, Geosci. Model Dev., 8, 3823–3835, https://doi.org/10.5194/gmd-8-3823-2015, 2015.
Thum, T., Caldararu, S., Engel, J., Kern, M., Pallandt, M., Schnur, R., Yu, L., and Zaehle, S.: A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996), Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, 2019 (code available at: https://www.gnu.org/licenses/gpl-3.0.en.html, last access: 27 January 2025).
Thurner, M. A., Caldararu, S., Engel, J., Rammig, A., and Zaehle, S.: Modelled forest ecosystem carbon–nitrogen dynamics with integrated mycorrhizal processes under elevated CO2, Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, 2024.
Todd-Brown, K., Zheng, B., and Crowther, T. W.: Field-warmed soil carbon changes imply high 21st-century modeling uncertainty, Biogeosciences, 15, 3659–3671, https://doi.org/10.5194/bg-15-3659-2018, 2018.
Todd-Brown, K. E. O., Randerson, J. T., Hopkins, F., Arora, V., Hajima, T., Jones, C., Shevliakova, E., Tjiputra, J., Volodin, E., Wu, T., Zhang, Q., and Allison, S. D.: Changes in soil organic carbon storage predicted by Earth system models during the 21st century, Biogeosciences, 11, 2341–2356, https://doi.org/10.5194/bg-11-2341-2014, 2014.
Varney, R. M., Chadburn, S. E., Friedlingstein, P., Burke, E. J., Koven, C. D., Hugelius, G., and Cox, P. M.: A spatial emergent constraint on the sensitivity of soil carbon turnover to global warming, Nat. Commun., 11, 5544, https://doi.org/10.1038/s41467-020-19208-8, 2020.
Walker, T. W. N., Kaiser, C., Strasser, F., Herbold, C. W., Leblans, N. I. W., Woebken, D., Janssens, I. A., Sigurdsson, B. D., and Richter, A.: Microbial temperature sensitivity and biomass change explain soil carbon loss with warming, Nat. Clim. Change, 8, 885–889, https://doi.org/10.1038/s41558-018-0259-x, 2018.
Wang, B., An, S., Liang, C., Liu, Y., and Kuzyakov, Y.: Microbial necromass as the source of soil organic carbon in global ecosystems, Soil Biol. Biochem., 162, 108422, https://doi.org/10.1016/j.soilbio.2021.108422, 2021.
Wang, G., Post, W. M., Mayes, M. A., Frerichs, J. T., and Sindhu, J.: Parameter estimation for models of ligninolytic and cellulolytic enzyme kinetics, Soil Biol. Biochem., 48, 28–38, https://doi.org/10.1016/j.soilbio.2012.01.011, 2012.
Wang, G., Post, W. M., and Mayes, M. A.: Development of microbial-enzyme-mediated decomposition model parameters through steady-state and dynamic analyses, Ecol. Appl., 23, 255–272, https://doi.org/10.1890/12-0681.1, 2013.
Wang, G., Jagadamma, S., Mayes, M. A., Schadt, C. W., Megan Steinweg, J., Gu, L., and Post, W. M.: Microbial dormancy improves development and experimental validation of ecosystem model, ISME J., 9, 226–237, https://doi.org/10.1038/ismej.2014.120, 2015.
Wang, G., Huang, W., Zhou, G., Mayes, M. A., and Zhou, J.: Modeling the processes of soil moisture in regulating microbial and carbon-nitrogen cycling, J. Hydrol., 585, 124777, https://doi.org/10.1016/j.jhydrol.2020.124777, 2020.
Wang, M., Guo, X., Zhang, S., Xiao, L., Mishra, U., Yang, Y., Zhu, B., Wang, G., Mao, X., Qian, T., Jiang, T., Shi, Z., and Luo, Z.: Global soil profiles indicate depth-dependent soil carbon losses under a warmer climate, Nat. Commun., 13, 5514, https://doi.org/10.1038/s41467-022-33278-w, 2022a.
Wang, Y., Mao, J., Hoffman, F. M., Bonfils, C. J. W., Douville, H., Jin, M., Thornton, P. E., Ricciuto, D. M., Shi, X., Chen, H., Wullschleger, S. D., Piao, S., and Dai, Y.: Quantification of human contribution to soil moisture-based terrestrial aridity, Nat. Commun., 13, 6848, https://doi.org/10.1038/s41467-022-34071-5, 2022b.
Wickham, H.: ggplot2, Springer International Publishing [software], Cham, https://doi.org/10.1007/978-3-319-24277-4, 2016.
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T., Miller, E., Bache, S., Müller, K., Ooms, J., Robinson, D., Seidel, D., Spinu, V., Takahashi, K., Vaughan, D., Wilke, C., Woo, K., and Yutani, H.: Welcome to the Tidyverse, J. Open Source Softw. [software], 4, 1686, https://doi.org/10.21105/joss.01686, 2019.
Wieder, W. R., Grandy, A. S., Kallenbach, C. M., and Bonan, G. B.: Integrating microbial physiology and physio-chemical principles in soils with the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, Biogeosciences, 11, 3899–3917, https://doi.org/10.5194/bg-11-3899-2014, 2014.
Wieder, W. R., Allison, S. D., Davidson, E. A., Georgiou, K., Hararuk, O., He, Y., Hopkins, F., Luo, Y., Smith, M. J., Sulman, B., Todd-Brown, K., Wang, Y.-P., Xia, J., and Xu, X.: Explicitly representing soil microbial processes in Earth system models, Glob. Change Biol., 29, 1782–1800, https://doi.org/10.1002/2015GB005188, 2015.
Wieder, W. R., Hartman, M. D., Sulman, B. N., Wang, Y.-P., Koven, C. D., and Bonan, G. B.: Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models, Glob. Change Biol., 24, 1563–1579, https://doi.org/10.1111/gcb.13979, 2018.
Wu, Y., Zhou, H., Sun, W., Zhao, Q., Liang, M., Chen, W., Guo, Z., Jiang, Y., Jiang, Y., Liu, G., and Xue, S.: Temperature sensitivity of soil enzyme kinetics under N and P fertilization in an alpine grassland, China, Sci. Total Environ., 838, 156042, https://doi.org/10.1016/j.scitotenv.2022.156042, 2022.
Xiao, K.-Q., Zhao, Y., Liang, C., Zhao, M., Moore, O. W., Otero-Fariña, A., Zhu, Y.-G., Johnson, K., and Peacock, C. L.: Introducing the soil mineral carbon pump, Nat. Rev. Earth Environ., 4, 135–136, https://doi.org/10.1038/s43017-023-00396-y, 2023.
Yan, Y., Wang, J., Tian, D., Luo, Y., Xue, X., Peng, F., He, J.-S., Liu, L., Jiang, L., Wang, X., Wang, Y., Song, L., and Niu, S.: Sustained increases in soil respiration accompany increased carbon input under long-term warming across global grasslands, Geoderma, 428, 116157, https://doi.org/10.1016/j.geoderma.2022.116157, 2022.
Yan, Z., Bond-Lamberty, B., Todd-Brown, K. E., Bailey, V. L., Li, S., Liu, C., and Liu, C.: A moisture function of soil heterotrophic respiration that incorporates microscale processes, Nat. Commun., 9, 2562, https://doi.org/10.1038/s41467-018-04971-6, 2018.
Yu, L., Ahrens, B., Wutzler, T., Schrumpf, M., and Zaehle, S.: Jena Soil Model (JSM v1.0; revision 1934): a microbial soil organic carbon model integrated with nitrogen and phosphorus processes, Geosci. Model Dev., 13, 783–803, https://doi.org/10.5194/gmd-13-783-2020, 2020 (code available at: https://git.bgc-jena.mpg.de/quincy/quincy-model-releases, last access: 21 March 2025).
Zhang, X., Xie, Z., Ma, Z., Barron-Gafford, G. A., Scott, R. L., and Niu, G.-Y.: A Microbial-Explicit Soil Organic Carbon Decomposition Model (MESDM): Development and Testing at a Semiarid Grassland Site, J. Adv. Model. Earth Syst., 14, e2021MS002485, https://doi.org/10.1029/2021MS002485, 2022.
Short summary
As soils warm due to climate change, soil organic carbon (SOC) decomposes faster due to increased microbial activity, given sufficient available moisture. We modelled the microbial decomposition of plant litter and residue at different depths and found that deep soil layers are more sensitive than topsoils. Warming causes SOC loss, but its extent depends on the litter type and its temperature sensitivity, which can either counteract or amplify losses. Droughts may also counteract warming-induced SOC losses.
As soils warm due to climate change, soil organic carbon (SOC) decomposes faster due to...
Altmetrics
Final-revised paper
Preprint