Articles | Volume 23, issue 14
https://doi.org/10.5194/bg-23-5205-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-23-5205-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Ideas and perspectives
| 
30 Jul 2026
Ideas and perspectives |
| 30 Jul 2026
| 30 Jul 2026
Ideas and perspectives: Using meta-omics to unravel biogeochemical changes from cell to planetary scales
Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA/CNRS/UVSQ, Orme des Merisiers, 91191, Gif sur Yvette, France
Christoph Keuschnig
GFZ Helmholtz Centre for Geosciences, 14473 Potsdam, Germany
Pierre Amato
Laboratoire Microorganismes: Génome et Environnement, UMR 6023 CNRS-Université Clermont Auvergne, 63178, Aubière, France
Chris Bowler
Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
CNRS Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans GOSEE, Paris, France
Eric Capo
Department of Ecology and Environmental Science, Umeå University, 90187, Umeå, Sweden
Alexander B. Chase
Department of Earth Sciences. Southern Methodist University, Dallas, TX, USA
Luciana Chavez Rodriguez
Soil Biology Group, Wageningen University & Research, Wageningen, Gelderland, the Netherlands
Abraham N. Dabengwa
Evolutionary Studies Institute, University of the Witwatersrand, Private Bag Wits 2050, Johannesburg, South Africa
Centre de Recherche et d'Enseignement des Géosciences de l'Environnement (CEREGE), CNRS UMR7330, Europole de l'Arbois, CEDEX 04, Aix-en-Provence 13545, France
Thomas Dussarrat
Department of Chemical Ecology, Bielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany
Thomas Guzman
INRAE UMR1391 ISPA, 33140 Villenave D'Ornon, France
Linnea K. Hernandez
Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
Jenni Hultman
Natural Resources Institute Finland, Helsinki, Finland
Kirsten Küsel
Institute of Biodiversity, Ecology, and Evolution, Friedrich Schiller University Jena, Jena, Germany
Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, Germany
Zhen Li
Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Anna Mankowski
Molecular Systems Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
William J. Riley
Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Scott R. Saleska
Department of Ecology and Evolutionary Biology. University of Arizona, Tucson, AZ 85721, USA
Lisa Wingate
INRAE UMR1391 ISPA, 33140 Villenave D'Ornon, France
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José Manuel Murúa Royo, Brittni Lin Bertolet, Luciana Chavez Rodriguez, Jeth Walkup, and Steven D. Allison
EGUsphere, https://doi.org/10.5194/egusphere-2026-3590, https://doi.org/10.5194/egusphere-2026-3590, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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Predictions of future climate change are done by models that represent real processes. Many models assume that soil microbes increase their production of CO2 when nutrients in their food are imbalanced, a behavior called overflow respiration. We demonstrate that alternative biological mechanisms avoid overflow from happening or completely revert its effect. Including these mechanisms in models could lead to very different CO2 predictions, impacting future scenarios of climate change.
Jinyun Tang, William J. Riley, Gianna L. Marschmann, and Eoin L. Brodie
Biogeosciences, 23, 3995–4010, https://doi.org/10.5194/bg-23-3995-2026, https://doi.org/10.5194/bg-23-3995-2026, 2026
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Carbon Use Efficiency (CUE) measures how biological organisms use carbon to synthesize new biomass, inferred to first increase and then decrease with specific growth rate. Our analysis of six biological growth models reveals that source-driven models fail to capture this relationship, while sink-driven models, using a reserve biomass pool, succeed. Existing biogeochemical models often depict a deterministic CUE-controlling factor relationship, which we find should be modeled dynamically instead.
Johannes Sakari Niemi, Miska Samuli Luoto, Anna-Maria Ilona Virkkala, Johanna Marika Lehtinen, and Jenni Johanna Hultman
EGUsphere, https://doi.org/10.5194/egusphere-2026-2936, https://doi.org/10.5194/egusphere-2026-2936, 2026
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We present 1273 greenhouse gas flux measurements from 144 locations across subarctic wetlands, tundra, and forests. Fluxes were strongly linked with soil temperature, moisture, and pH with pronounced seasonal variation. Key findings include significant N₂O sinks and CH₄ emissions from wetlands, increasing CH₄ emissions from melting permafrost, and small but consistent CH₄ sinks in forest and tundra. These results help to reduce uncertainties in global greenhouse gas budgets and measurements.
Mengze Li, Robert B. Jackson, Marielle Saunois, Philippe Ciais, Ben Poulter, Josep G. Canadell, Prabir K. Patra, Hanqin Tian, Zhen Zhang, Etienne Fluet-Chouinard, Zutao Ouyang, Ting Zhang, David J. Beerling, Dmitry A. Belikov, Philippe Bousquet, Danilo Custodio, Naveen Chandra, Xinyu Dou, Nicola Gedney, Peter O. Hopcroft, Alison M. Hoyt, Kazuhito Ichii, Akihito Ito, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Masayuki Kondo, Fa Li, Tingting Li, Xiangyu Liu, Shamil Maksyutov, Avni Malhotra, Adrien Martinez, Kyle McDonald, Joe R. Melton, Jurek Müller, Yosuke Niwa, Shufen Pan, Shushi Peng, Changhui Peng, Zhangcai Qin, Peter Raymond, William Riley, Arjo Segers, Rona L. Thompson, Aki Tsuruta, Yi Xi, Kunxiaojia Yuan, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 18, 3507–3524, https://doi.org/10.5194/essd-18-3507-2026, https://doi.org/10.5194/essd-18-3507-2026, 2026
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We proposed a framework that combines machine-learning and climate data to predict global natural vegetated wetland methane emissions for 2000–2025. We found that although total global emissions remained stable in the post-2020s, Northern Hemisphere emissions surged whilst tropical emissions fell. This approach allows us to rapidly monitor emissions and provides early warnings for climate impacts.
Pauline Nibert, Yi Wu, Muriel Joly, Pierre Amato, Paolo Cristofanelli, Francescopiero Calzolari, Jean-Luc Piro, Davide Putero, Simonetta Montaguti, Laura Renzi, Franziska Vogel, Marco Rapuano, Marcello Brigante, Christophe Verhaege, Jean-Luc Baray, Laurent Deguillaume, Angela Marinoni, Marco Zanatta, and Angelica Bianco
Atmos. Chem. Phys., 26, 6489–6506, https://doi.org/10.5194/acp-26-6489-2026, https://doi.org/10.5194/acp-26-6489-2026, 2026
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This study provides the first chemical and microbiological characterization of cloud samples collected at Mt. Cimone (acronym CMN in ACTRIS, ICOS and GAW) in the Mediterranean basin. The chemical characterization is deeply discussed in relationship with back-trajectories and cloud processing. Air mass history do not fully explain the variability observed in the chemical composition. This highlights the complexity of emission sources, multiphasique exchanges, and transformations in clouds.
Sławomir Sułowicz, Krzysztof Zawierucha, Anna Markowicz, Krystyna Kozioł, Wiktoria Zientak, Adam Nawrot, Krzesimir Tomaszewski, Christoph Keuschnig, Bartłomiej Luks, and Catherine Larose
Biogeosciences, 23, 3023–3038, https://doi.org/10.5194/bg-23-3023-2026, https://doi.org/10.5194/bg-23-3023-2026, 2026
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Our research shows that animals such as birds and mammals shaping the bacteria community structure found in Arctic snow. By analyzing snow samples from coastal Spitsbergen, we found that microbes linked to animal waste were common and influenced the types of bacteria present. This suggests that wildlife, not just wind or air, helps bring microbes into snow. Understanding this helps us better predict how Arctic ecosystems respond to environmental change and how life adapts in extreme conditions.
Frédéric Mathonat, François Enault, Raphaëlle Péguilhan, Muriel Joly, Mariline Théveniot, Jean-Luc Baray, Barbara Ervens, and Pierre Amato
Biogeosciences, 23, 2885–2907, https://doi.org/10.5194/bg-23-2885-2026, https://doi.org/10.5194/bg-23-2885-2026, 2026
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The atmosphere plays key roles in Earth’s biogeochemical cycles. Airborne microbes were demonstrated previously to participate in the processing of organic carbon in clouds. Using a combinaison of complementary methods, we examined here, for the first time, their potential contribution to the pool of nitrogen compounds. Airborne microorganisms interact with abundant forms of nitrogen in the air and cloud and we provide global estimates.
Jeffrey Beem-Miller, William J. Riley, Peter B. Reich, Michael W. I. Schmidt, Yuxuan Bai, Raimundo Bermudez Villanueva, Zach Brown, Abad Chabbi, Susan E. Crow, Wenxu Dong, Serita D. Frey, Paul J. Hanson, Kai Jensen, Melissa A. Knorr, Emma Lathrop, Avni Malhotra, Patrick Megonigal, Adrienne Nicotra, Andrew Nottingham, Genevieve L. Noyce, Roy L. Rich, Heidi Rodenhizer, Agustín Sarquis, Andreas Schindlbacher, Edward A. G. Schuur, Zheng Shi, Artur Stefanski, Viktoria Unger, Tana E. Wood, Yuanhe Yang, Zhijie Yang, Jizhong Zhou, Biao Zhu, and Margaret S. Torn
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-23, https://doi.org/10.5194/essd-2026-23, 2026
Preprint under review for ESSD
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The Soil Warming to Depth Data Integration Effort (SWEDDIE) synthesizes data from deep soil warming experiments around the world (n = 23), offering new insight into warming responses of both surface and subsoils. We demonstrate that variation in soil warming with depth is driven largely by warming methodology, while soil moisture changes due to warming differ by ecosystem. This work serves a foundation for future syntheses with SWEDDIE.
Lisa Ardoin, Catherine Larose, Jean-Louis Tison, Christoph Keuschnig, Vasileios Gkinis, Saïda El Amri, Pierre-Henry Blard, Paul Bierman, Thomas Blunier, Dorthe Dahl-Jensen, Charlotte Maistriau, Jørgen-Peder Steffensen, Thomas Röckmann, and François Fripiat
EGUsphere, https://doi.org/10.5194/egusphere-2025-6204, https://doi.org/10.5194/egusphere-2025-6204, 2026
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We investigated gas dynamics at the ice–bed interface of two Greenland ice cores to assess methane and carbon dioxide behaviour beneath ice sheets. At Camp Century, methane diffuses into the ice and is partly oxidized. At GRIP, methane remains preserved despite oxygen. These contrasts suggest that methane oxidation is controlled by local basal conditions, including ice thickness and substrate availability.
Ashley Brereton, Zelalem A. Mekonnen, Bhavna Arora, William J. Riley, Kunxiaojia Yuan, Yi Xu, Yu Zhang, Qing Zhu, Tyler L. Anthony, and Adina Paytan
Geosci. Model Dev., 18, 8157–8173, https://doi.org/10.5194/gmd-18-8157-2025, https://doi.org/10.5194/gmd-18-8157-2025, 2025
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Wetlands absorb carbon dioxide (CO2), helping slow climate change, but they also release methane, a potent warming gas. We developed a collection of AI-based models to estimate magnitudes of CO2 and methane exchanged between the land and the atmosphere, for wetlands on a regional scale. This approach helps to inform land-use planning, restoration, and greenhouse gas accounting, while also creating a foundation for future advancements in prediction accuracy.
Sophie L. Baartman, Steven M. Driever, Maarten L. J. Wassenaar, Linda M. J. Kooijmans, Nerea Ubierna, Leon Mossink, Maria E. Popa, Ara Cho, Lisa Wingate, Thomas Röckmann, Steven M. A. C. van Heuven, and Maarten C. Krol
Biogeosciences, 22, 5683–5703, https://doi.org/10.5194/bg-22-5683-2025, https://doi.org/10.5194/bg-22-5683-2025, 2025
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Carbonyl sulfide (COS) is a proposed tracer for gross primary production. For the first time, COS and carbon dioxide (CO2) uptake fluxes and isotope discrimination were jointly measured in sunflower and papyrus plants, using a flow-through plant chamber approach and varying light availability. COS isotope discrimination did not differ significantly between the species, nor with changes in light. CO2 fluxes and isotope values provided additional valuable information for data interpretation.
Baptiste Hulin, Scott Saleska, Didier Jehanno, Simon Chollet, Katerina Dontsova, Hannes Bauser, Valerie Milici, and Samuel Abiven
EGUsphere, https://doi.org/10.5194/egusphere-2025-4243, https://doi.org/10.5194/egusphere-2025-4243, 2025
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Studying biogeochemical processes requires expertise in many disciplines. To meet this challenge, we set up an experimental facility that combines 15 lysimeters and a climate chamber. We developed instrumentation that would enable us to monitor the water cycle and facilitate sampling for all lysimeters, thus allowing replication. By providing automated access to a variety of data, this facility fosters interdisciplinarity and offers an alternative to field and laboratory studies.
Pearse J. Buchanan, Juan J. Pierella Karlusich, Robyn E. Tuerena, Roxana Shafiee, E. Malcolm S. Woodward, Chris Bowler, and Alessandro Tagliabue
Biogeosciences, 22, 4865–4883, https://doi.org/10.5194/bg-22-4865-2025, https://doi.org/10.5194/bg-22-4865-2025, 2025
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Ammonium is a form of nitrogen that may become more important for growth of marine primary producers (i.e., phytoplankton) in the future. Because some phytoplankton taxa have a greater affinity for ammonium than others, the relative increase in ammonium could cause shifts in community composition. We quantify ammonium enrichment, identify its drivers and isolate the possible effect on phytoplankton community composition under a high-emissions scenario.
Sylvain Schmitt, Fabian J. Fischer, James G. C. Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy W. Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
Geosci. Model Dev., 18, 5205–5243, https://doi.org/10.5194/gmd-18-5205-2025, https://doi.org/10.5194/gmd-18-5205-2025, 2025
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We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity, dynamics, and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote sensing products. The model realistically predicts the structure and composition as well as the seasonality of carbon and water fluxes at both sites.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Jinyun Tang and William J. Riley
Biogeosciences, 22, 1809–1819, https://doi.org/10.5194/bg-22-1809-2025, https://doi.org/10.5194/bg-22-1809-2025, 2025
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A new mathematical formulation of the dynamic energy budget model is presented for the growth of biological organisms. This new formulation combines mass conservation law and chemical kinetics theory and is computationally faster than the standard formulation of dynamic energy budget models. In simulating the growth of Thalassiosira weissflogii in a nitrogen-limiting chemostat, the new model is as good as the standard dynamic energy budget model using almost the same parameter values.
Raphaëlle Péguilhan, Florent Rossi, Muriel Joly, Engy Nasr, Bérénice Batut, François Enault, Barbara Ervens, and Pierre Amato
Biogeosciences, 22, 1257–1275, https://doi.org/10.5194/bg-22-1257-2025, https://doi.org/10.5194/bg-22-1257-2025, 2025
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Using comparative metagenomics and metatranscriptomics, we examined the functioning of airborne microorganisms in clouds and a clear atmosphere. Clouds are atmospheric masses where multiple microbial processes are promoted compared with a clear atmosphere. Overrepresented microbial functions of interest include the processing of chemical compounds, biomass production, and regulation of oxidants. This has implications for biogeochemical cycles and microbial ecology.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Barbara Ervens, Pierre Amato, Kifle Aregahegn, Muriel Joly, Amina Khaled, Tiphaine Labed-Veydert, Frédéric Mathonat, Leslie Nuñez López, Raphaëlle Péguilhan, and Minghui Zhang
Biogeosciences, 22, 243–256, https://doi.org/10.5194/bg-22-243-2025, https://doi.org/10.5194/bg-22-243-2025, 2025
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Atmospheric microorganisms are a small fraction of Earth's microbiome, with bacteria being a significant part. Aerosolized bacteria are airborne for a few days, encountering unique chemical and physical conditions affecting stress levels and survival. We explore chemical and microphysical conditions bacteria encounter, highlighting potential nutrient and oxidant limitations and diverse effects by pollutants, which may ultimately impact the microbiome's role in global ecosystems and biodiversity.
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024, https://doi.org/10.5194/bg-21-5173-2024, 2024
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Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Using machine learning, we develop and compare predictive relationships in observations (Obs) and ESMs. We find different relationships between environmental factors and SOC stocks in Obs and ESMs. SOC prediction in ESMs may be improved by representing the functional relationships of environmental controllers in a way consistent with observations.
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
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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.
Elizabeth S. Duan, Luciana Chavez Rodriguez, Nicole Hemming-Schroeder, Baptiste Wijas, Habacuc Flores-Moreno, Alexander W. Cheesman, Lucas A. Cernusak, Michael J. Liddell, Paul Eggleton, Amy E. Zanne, and Steven D. Allison
Biogeosciences, 21, 3321–3338, https://doi.org/10.5194/bg-21-3321-2024, https://doi.org/10.5194/bg-21-3321-2024, 2024
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Understanding the link between climate and carbon fluxes is crucial for predicting how climate change will impact carbon sinks. We estimated carbon dioxide (CO2) fluxes from deadwood in tropical Australia using wood moisture content and temperature. Our model predicted that the majority of deadwood carbon is released as CO2, except when termite activity is detected. Future models should also incorporate wood traits, like species and chemical composition, to better predict fluxes.
Leslie Nuñez López, Pierre Amato, and Barbara Ervens
Atmos. Chem. Phys., 24, 5181–5198, https://doi.org/10.5194/acp-24-5181-2024, https://doi.org/10.5194/acp-24-5181-2024, 2024
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Living bacteria comprise a small particle fraction in the atmosphere. Our model study shows that atmospheric bacteria in clouds may efficiently biodegrade formic and acetic acids that affect the acidity of rain. We conclude that current atmospheric models underestimate losses of these acids as they only consider chemical processes. We suggest that biodegradation can affect atmospheric concentration not only of formic and acetic acids but also of other volatile, moderately soluble organics.
Maud Leriche, Pierre Tulet, Laurent Deguillaume, Frédéric Burnet, Aurélie Colomb, Agnès Borbon, Corinne Jambert, Valentin Duflot, Stéphan Houdier, Jean-Luc Jaffrezo, Mickaël Vaïtilingom, Pamela Dominutti, Manon Rocco, Camille Mouchel-Vallon, Samira El Gdachi, Maxence Brissy, Maroua Fathalli, Nicolas Maury, Bert Verreyken, Crist Amelynck, Niels Schoon, Valérie Gros, Jean-Marc Pichon, Mickael Ribeiro, Eric Pique, Emmanuel Leclerc, Thierry Bourrianne, Axel Roy, Eric Moulin, Joël Barrie, Jean-Marc Metzger, Guillaume Péris, Christian Guadagno, Chatrapatty Bhugwant, Jean-Mathieu Tibere, Arnaud Tournigand, Evelyn Freney, Karine Sellegri, Anne-Marie Delort, Pierre Amato, Muriel Joly, Jean-Luc Baray, Pascal Renard, Angelica Bianco, Anne Réchou, and Guillaume Payen
Atmos. Chem. Phys., 24, 4129–4155, https://doi.org/10.5194/acp-24-4129-2024, https://doi.org/10.5194/acp-24-4129-2024, 2024
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Aerosol particles in the atmosphere play a key role in climate change and air pollution. A large number of aerosol particles are formed from the oxidation of volatile organic compounds (VOCs and secondary organic aerosols – SOA). An important field campaign was organized on Réunion in March–April 2019 to understand the formation of SOA in a tropical atmosphere mostly influenced by VOCs emitted by forest and in the presence of clouds. This work synthesizes the results of this campaign.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Roy El Hourany, Juan Pierella Karlusich, Lucie Zinger, Hubert Loisel, Marina Levy, and Chris Bowler
Ocean Sci., 20, 217–239, https://doi.org/10.5194/os-20-217-2024, https://doi.org/10.5194/os-20-217-2024, 2024
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Satellite observations offer valuable information on phytoplankton abundance and community structure. Here, we employ satellite observations to infer seven phytoplankton groups at a global scale based on a new molecular method from Tara Oceans. The link has been established using machine learning approaches. The output of this work provides excellent tools to collect essential biodiversity variables and a foundation to monitor the evolution of marine biodiversity.
Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
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We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
Karel Castro-Morales, Anna Canning, Sophie Arzberger, Will A. Overholt, Kirsten Küsel, Olaf Kolle, Mathias Göckede, Nikita Zimov, and Arne Körtzinger
Biogeosciences, 19, 5059–5077, https://doi.org/10.5194/bg-19-5059-2022, https://doi.org/10.5194/bg-19-5059-2022, 2022
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Permafrost thaw releases methane that can be emitted into the atmosphere or transported by Arctic rivers. Methane measurements are lacking in large Arctic river regions. In the Kolyma River (northeast Siberia), we measured dissolved methane to map its distribution with great spatial detail. The river’s edge and river junctions had the highest methane concentrations compared to other river areas. Microbial communities in the river showed that the river’s methane likely is from the adjacent land.
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
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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.
Javier de la Casa, Adrià Barbeta, Asun Rodríguez-Uña, Lisa Wingate, Jérôme Ogée, and Teresa E. Gimeno
Hydrol. Earth Syst. Sci., 26, 4125–4146, https://doi.org/10.5194/hess-26-4125-2022, https://doi.org/10.5194/hess-26-4125-2022, 2022
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Recently, studies have been reporting mismatches in the water isotopic composition of plants and soils. In this work, we reviewed worldwide isotopic composition data of field and laboratory studies to see if the mismatch is generalised, and we found it to be true. This contradicts theoretical expectations and may underlie an non-described phenomenon that should be forward investigated and implemented in ecohydrological models to avoid erroneous estimations of water sources used by vegetation.
Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
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Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
Jinyun Tang, William J. Riley, and Qing Zhu
Geosci. Model Dev., 15, 1619–1632, https://doi.org/10.5194/gmd-15-1619-2022, https://doi.org/10.5194/gmd-15-1619-2022, 2022
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We here describe version 2 of BeTR, a reactive transport model created to help ease the development of biogeochemical capability in Earth system models that are used for quantifying ecosystem–climate feedbacks. We then coupled BeTR-v2 to the Energy Exascale Earth System Model to quantify how different numerical couplings of plants and soils affect simulated ecosystem biogeochemistry. We found that different couplings lead to significant uncertainty that is not correctable by tuning parameters.
Jing Tao, Qing Zhu, William J. Riley, and Rebecca B. Neumann
The Cryosphere, 15, 5281–5307, https://doi.org/10.5194/tc-15-5281-2021, https://doi.org/10.5194/tc-15-5281-2021, 2021
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We improved the DOE's E3SM land model (ELMv1-ECA) simulations of soil temperature, zero-curtain period durations, cold-season CH4, and CO2 emissions at several Alaskan Arctic tundra sites. We demonstrated that simulated CH4 emissions during zero-curtain periods accounted for more than 50 % of total emissions throughout the entire cold season (Sep to May). We also found that cold-season CO2 emissions largely offset warm-season net uptake currently and showed increasing trends from 1950 to 2017.
Soleil E. Worthy, Anand Kumar, Yu Xi, Jingwei Yun, Jessie Chen, Cuishan Xu, Victoria E. Irish, Pierre Amato, and Allan K. Bertram
Atmos. Chem. Phys., 21, 14631–14648, https://doi.org/10.5194/acp-21-14631-2021, https://doi.org/10.5194/acp-21-14631-2021, 2021
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We studied the effect of (NH4)2SO4 on the immersion freezing of non-mineral dust ice-nucleating substances (INSs) and mineral dusts. (NH4)2SO4 had no effect on the median freezing temperature of 9 of the 10 tested non-mineral dust INSs, slightly decreased that of the other, and increased that of all the mineral dusts. The difference in the response of mineral dust and non-mineral dust INSs to (NH4)2SO4 suggests that they nucleate ice and/or interact with (NH4)2SO4 via different mechanisms.
Cited articles
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Short summary
Meta-omics technologies offer new tools to understand how microbial and plant functional diversity shape biogeochemical cycles across ecosystems. This perspective explores how integrating omics data with ecological and modeling approaches can improve our understanding of greenhouse gas fluxes and nutrient dynamics, from soils to clouds, and from the past to the future. We highlight challenges and opportunities for scaling omics insights from local processes to Earth system models.
Meta-omics technologies offer new tools to understand how microbial and plant functional...
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