Articles | Volume 11, issue 2
https://doi.org/10.5194/soil-11-1053-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/soil-11-1053-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The potential of reed canary grass and the importance of field heterogeneity for reducing GHG emissions in a rewetting fen peatland
Andres F. Rodriguez
CORRESPONDING AUTHOR
Department of Agroecology, Aarhus University, Tjele, 8830, Denmark
Johannes W. M. Pullens
Department of Agroecology, Aarhus University, Tjele, 8830, Denmark
iCLIMATE Interdisciplinary Centre for Climate Change, Aarhus University, Roskilde, 4000, Denmark
Jesper R. Christiansen
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1958, Denmark
Klaus S. Larsen
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1958, Denmark
Poul E. Lærke
Department of Agroecology, Aarhus University, Tjele, 8830, Denmark
iCLIMATE Interdisciplinary Centre for Climate Change, Aarhus University, Roskilde, 4000, Denmark
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Annelie Skov Nielsen, Klaus Steenberg Larsen, Poul Erik Lærke, Andres Felipe Rodriguez, Johannes W. M. Pullens, Rasmus Jes Petersen, and Jesper Riis Christiansen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-123, https://doi.org/10.5194/essd-2025-123, 2025
Revised manuscript accepted for ESSD
Short summary
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Quantifying greenhouse gas emissions from wetlands are a crucial for improved climate mitigation. Our data of CO2, CH4, and N2O fluxes, measured with a high-precision system, shows that the exchange with the atmosphere is surprisingly dynamic over time and space where both long and short-term fluctuations of temperature and groundwater collectively shape both monthly to hourly scales. These data helps us important for our fundamental understanding, but also in developing models.
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Preprint under review for ESSD
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This dataset includes monthly measurements of carbon dioxide and methane exchange between land, water, and the atmosphere from over 1,000 sites in Arctic and boreal regions. It combines measurements from a variety of ecosystems, including wetlands, forests, tundra, lakes, and rivers, gathered by over 260 researchers from 1984–2024. This dataset can be used to improve and reduce uncertainty in carbon budgets in order to strengthen our understanding of climate feedbacks in a warming world.
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Short summary
Short summary
This study demonstrates that incorporating both temperature and temporal variability in water level in emission models significantly influences CO2 emission from peat soil. Especially the co-occurrence of elevated air temperature and low groundwater table significantly influence CO2 emissions under scenarios of rewetting and climate change.
Annelie Skov Nielsen, Klaus Steenberg Larsen, Poul Erik Lærke, Andres Felipe Rodriguez, Johannes W. M. Pullens, Rasmus Jes Petersen, and Jesper Riis Christiansen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-123, https://doi.org/10.5194/essd-2025-123, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Quantifying greenhouse gas emissions from wetlands are a crucial for improved climate mitigation. Our data of CO2, CH4, and N2O fluxes, measured with a high-precision system, shows that the exchange with the atmosphere is surprisingly dynamic over time and space where both long and short-term fluctuations of temperature and groundwater collectively shape both monthly to hourly scales. These data helps us important for our fundamental understanding, but also in developing models.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
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Short summary
This manuscript studies the potential of paludiculture to reduce greenhouse gas emissions (GHG) in rewetting peatlands. Results showed that the potential to mitigate GHG emissions could be maximized in nutrient enriched areas, while in low nutrient areas it might be more beneficial not to harvest the biomass. Results also showed that peatland heterogeneity and water table dynamics should be considered to accurately estimate emissions from rewetting peatlands.
This manuscript studies the potential of paludiculture to reduce greenhouse gas emissions (GHG)...