Articles | Volume 23, issue 19
https://doi.org/10.5194/bg-23-6803-2026
© 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-23-6803-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying aggregation bias in marsh carbon flux estimates caused by rhizosphere oxygen heterogeneity
Youssef Saadaoui
CORRESPONDING AUTHOR
Institute of Plant Science and Microbiology, Department of Biology, Faculty of Mathematics, Informatics and Natural Sciences, Universität Hamburg, Ohnhorststr. 18, 22609 Hamburg, Germany
now at: Institute of Coastal Systems–Analysis and Modeling, Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
Christian Beer
Institute of Soil Science, Department of Earth System Sciences, Faculty of Mathematics, Informatics and Natural Sciences, Universität Hamburg, Allende-Platz 2, 20146 Hamburg, Germany
Center for Earth System Research and Sustainability, Universität Hamburg, Bundesstraße 53, 20146 Hamburg, Germany
Peter Mueller
Institute of Landscape Ecology, University of Münster, Heisenbergstr. 2, 48149 Münster, Germany
Friederike Neiske
Institute of Soil Science, Department of Earth System Sciences, Faculty of Mathematics, Informatics and Natural Sciences, Universität Hamburg, Allende-Platz 2, 20146 Hamburg, Germany
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Telegrafenberg A45, 14473 Potsdam, Germany
Joscha N. Becker
Institute of Soil Science, Department of Earth System Sciences, Faculty of Mathematics, Informatics and Natural Sciences, Universität Hamburg, Allende-Platz 2, 20146 Hamburg, Germany
Institute of Biology and Environmental Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
Annette Eschenbach
Institute of Soil Science, Department of Earth System Sciences, Faculty of Mathematics, Informatics and Natural Sciences, Universität Hamburg, Allende-Platz 2, 20146 Hamburg, Germany
Center for Earth System Research and Sustainability, Universität Hamburg, Bundesstraße 53, 20146 Hamburg, Germany
Philipp Porada
Institute of Plant Science and Microbiology, Department of Biology, Faculty of Mathematics, Informatics and Natural Sciences, Universität Hamburg, Ohnhorststr. 18, 22609 Hamburg, Germany
Center for Earth System Research and Sustainability, Universität Hamburg, Bundesstraße 53, 20146 Hamburg, Germany
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Philipp de Vrese, Tobias Stacke, Veronika Gayler, Helena Bergstedt, Clemens von Baeckmann, Melanie Thurner, Christian Beer, and Victor Brovkin
Geosci. Model Dev., 19, 9203–9234, https://doi.org/10.5194/gmd-19-9203-2026, https://doi.org/10.5194/gmd-19-9203-2026, 2026
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The spatial variability in the land surface properties is often not captured by the resolution of land surface models. To overcome this limitation, most models subdivide the grid cells into fractions with homogeneous characteristics, for which the land processes are calculated separately. In reality, the fractions interact via the lateral exchange of water and heat, and the present manuscript details an approach to include these fluxes in the land component of the ICON modeling framework.
Christian Knoblauch, Christian Beer, and Carolina Voigt
Biogeosciences, 23, 3615–3635, https://doi.org/10.5194/bg-23-3615-2026, https://doi.org/10.5194/bg-23-3615-2026, 2026
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Carbon release from thawing permafrost receives ample attention since it may cause rising greenhouse gas concentrations in the atmosphere. However, we demonstrate through a 9-year lasting incubation experiment that thawing permafrost stabilizes a substantial amount of fresh plant litter carbon from increasing plant productivity for decades. Although litter carbon is faster decomposed than the permafrost carbon it may contribute to the build-up of organic carbon in thawing permafrost soils.
Melanie Alexandra Thurner, Xavier Rodriguez-Lloveras, and Christian Beer
Geosci. Model Dev., 19, 3509–3530, https://doi.org/10.5194/gmd-19-3509-2026, https://doi.org/10.5194/gmd-19-3509-2026, 2026
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Soil texture varies over centimeters, which is overseen by large-scale models, likely causing simulation errors. We developed a 2-dimesional geophysical soil model (DynSoM-2D) with a resolution of 10 cm and ran it with different setups at a permafrost-affected site. Using high-resolution input, DynSoM-2D simulates a warmer soil, which thaws deeper and has an extended snow-free period in summer. These changes can impact ecosystem dynamics, but have little effect on yearly soil-air heat exchange.
Luana S. Basso, Goran Georgievski, Victor Brovkin, Christian Beer, Christian Rödenbeck, and Mathias Göckede
Biogeosciences, 23, 2815–2830, https://doi.org/10.5194/bg-23-2815-2026, https://doi.org/10.5194/bg-23-2815-2026, 2026
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This study examines how combining atmospheric inversion with process-based modelling can reduce discrepancies in estimates of Arctic wetland CH4 emissions. We conducted a series of inversion experiments, each incorporating CH4 wetland fluxes from process-based models with different CH4 production parameterizations. Our results showed that no single parameterization captures the complexity of Arctic–Boreal emissions; instead, region-specific adjustments are needed to reduce discrepancies.
Marius Moser, Lara Kaiser, Victor Brovkin, and Christian Beer
Biogeosciences, 23, 605–621, https://doi.org/10.5194/bg-23-605-2026, https://doi.org/10.5194/bg-23-605-2026, 2026
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Arctic warming might lead to increased carbon dioxide and methane emissions. Process-based prediction of their ratio is important for projecting the future carbon cycle. However, land surface models often assume a constant ratio. To overcome this limitation, we identify three core processes for representing methanogenesis accurately in land surface models: fermentation, acetoclastic methanogenesis, and hydrogenotrophic methanogenesis.
Marina Falke, Leena Leppänen, Jaakko Nissilä, and Christian Beer
EGUsphere, https://doi.org/10.5194/egusphere-2025-5771, https://doi.org/10.5194/egusphere-2025-5771, 2025
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The study examined spatial and temporal variability of taiga snowpack during spring melt using weekly measurements of height, stratigraphy, temperature, and density at four Sodankylä sites. Snow height peaked on 30 Mar. Density increased through melt, reaching ~ 500 kg/m³ by late Apr–early May. Snow structure shifted from depth hoar to melt forms, and temperatures reached 0 °C throughout. By 10 May, snow cover disappeared. Findings highlight evolving, heterogeneous melt-season snow properties.
Lin Yu, Thomas Kleinen, Min Jung Kwon, Christian Knoblauch, and Christian Beer
EGUsphere, https://doi.org/10.5194/egusphere-2025-4648, https://doi.org/10.5194/egusphere-2025-4648, 2025
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We studied how adding biochar to soils might affect future climate. Using computer simulations, we found that while global averages of temperature and rainfall change little, extreme events respond more clearly. Heat waves and heavy rain are reduced in many regions, though drought risks rise in some dry areas. These results suggest that biochar could help moderate harmful climate extremes, especially on land, but with region-specific effects.
Christian Beer
Earth Syst. Dynam., 16, 1527–1537, https://doi.org/10.5194/esd-16-1527-2025, https://doi.org/10.5194/esd-16-1527-2025, 2025
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Fauna and flora respire carbon dioxide into the atmosphere, which is a major carbon flux into the atmosphere. The underlying biochemical processes are complex, and we generalize them either assuming a first-order chemical reaction of carbon and oxygen to carbon dioxide or assuming enzymatic reactions. Here, we show that these assumptions lead to large differences in estimating the carbon–climate feedback until 2100 and the remaining carbon budget to keep warming below 2°C.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
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We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Hao Tang, Stefanie Nolte, Kai Jensen, Roy Rich, Julian Mittmann-Goetsch, and Peter Mueller
Biogeosciences, 20, 1925–1935, https://doi.org/10.5194/bg-20-1925-2023, https://doi.org/10.5194/bg-20-1925-2023, 2023
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In order to gain the first mechanistic insight into warming effects and litter breakdown dynamics across whole-soil profiles, we used a unique field warming experiment and standardized plant litter to investigate the degree to which rising soil temperatures can accelerate belowground litter breakdown in coastal wetland ecosystems. We found warming strongly increases the initial rate of labile litter decomposition but has less consistent effects on the stabilization of this material.
Suman Halder, Susanne K. M. Arens, Kai Jensen, Tais W. Dahl, and Philipp Porada
Geosci. Model Dev., 15, 2325–2343, https://doi.org/10.5194/gmd-15-2325-2022, https://doi.org/10.5194/gmd-15-2325-2022, 2022
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A dynamic vegetation model, designed to estimate potential impacts of early vascular vegetation, namely, lycopsids, on the biogeochemical cycle at a local scale. Lycopsid Model (LYCOm) estimates the productivity and physiological properties of lycopsids across a broad climatic range along with natural selection, which is then utilized to adjudge their weathering potential. It lays the foundation for estimation of their impacts during their long evolutionary history starting from the Ordovician.
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Short summary
In marsh soils, oxygen concentrations are high close to plant roots and decline to near zero within millimetres. Microorganisms do not decompose organic matter in proportion to oxygen. Many models nevertheless use a single average oxygen concentration. Using Elbe River soils, we compared this approach with a calculation over the full range. The single average overestimated carbon dioxide release by about 12 %. Marsh soils may therefore store more carbon than models predict.
In marsh soils, oxygen concentrations are high close to plant roots and decline to near zero...
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