Articles | Volume 7, issue 5
https://doi.org/10.5194/gmd-7-1919-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-1919-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
03 Sep 2014
Model description paper |
| 03 Sep 2014
Modeling radiocarbon dynamics in soils: SoilR version 1.1
C. A. Sierra
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
M. Müller
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
S. E. Trumbore
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany
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Biogeosciences, 22, 455–472, https://doi.org/10.5194/bg-22-455-2025, https://doi.org/10.5194/bg-22-455-2025, 2025
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Assessing the net carbon (C) budget of the Amazon entails considering the magnitude and timing of C absorption and losses through respiration (transit time of C). Radiocarbon-based estimates of the transit time of C in the Amazon Tall Tower Observatory (ATTO) suggest a change in the transit time from 6 ± 2 years and 18 ± 4 years within 2 years (October 2019 and December 2021, respectively). This variability indicates that only a fraction of newly fixed C can be stored for decades or longer.
Maximiliano González-Sosa, Carlos A. Sierra, J. Andrés Quincke, Walter E. Baethgen, Susan Trumbore, and M. Virginia Pravia
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Based on an approach that involved soil organic carbon (SOC) monitoring, radiocarbon measurement in bulk soil, and incubations from a long-term 60-year experiment, it was concluded that the avoidance of old carbon losses in the integrated crop–pasture systems is the main reason that explains their greater carbon storage capacities compared to continuous cropping. A better understanding of these processes is essential for making agronomic decisions to increase the carbon sequestration capacity.
Andrés Tangarife-Escobar, Georg Guggenberger, Xiaojuan Feng, Guohua Dai, Carolina Urbina-Malo, Mina Azizi-Rad, and Carlos A. Sierra
Biogeosciences, 21, 1277–1299, https://doi.org/10.5194/bg-21-1277-2024, https://doi.org/10.5194/bg-21-1277-2024, 2024
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Soil organic matter stability depends on future temperature and precipitation scenarios. We used radiocarbon (14C) data and model predictions to understand how the transit time of carbon varies under environmental change in grasslands and peatlands. Soil moisture affected the Δ14C of peatlands, while temperature did not have any influence. Our models show the correspondence between Δ14C and transit time and could allow understanding future interactions between terrestrial and atmospheric carbon
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
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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.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
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Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Song Wang, Carlos Sierra, Yiqi Luo, Jinsong Wang, Weinan Chen, Yahai Zhang, Aizhong Ye, and Shuli Niu
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-33, https://doi.org/10.5194/bg-2023-33, 2023
Manuscript not accepted for further review
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Nitrogen is important for plant growth and carbon uptake, which is uaually limited in nature and can constrain carbon storage and impact efforts to combat climate change. We developed a new method of combining data and models to determine if and how much an ecosystem is nitrogen limited. This new method can help determine if and to what extent an ecosystem is nitrogen-limited, providing insight into nutrient limitations on a global scale and guiding ecosystem management decisions.
Andrea Scheibe, Carlos A. Sierra, and Marie Spohn
Biogeosciences, 20, 827–838, https://doi.org/10.5194/bg-20-827-2023, https://doi.org/10.5194/bg-20-827-2023, 2023
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We explored carbon cycling in soils in three climate zones in Chile down to a depth of 6 m, using carbon isotopes. Our results show that microbial activity several meters below the soil surface is mostly fueled by recently fixed carbon and that strong decomposition of soil organic matter only occurs in the upper decimeters of the soils. The study shows that different layers of the critical zone are tightly connected and that processes in the deep soil depend on recently fixed carbon.
Carlos A. Sierra, Verónika Ceballos-Núñez, Henrik Hartmann, David Herrera-Ramírez, and Holger Metzler
Biogeosciences, 19, 3727–3738, https://doi.org/10.5194/bg-19-3727-2022, https://doi.org/10.5194/bg-19-3727-2022, 2022
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Empirical work that estimates the age of respired CO2 from vegetation tissue shows that it may take from years to decades to respire previously produced photosynthates. However, many ecosystem models represent respiration processes in a form that cannot reproduce these observations. In this contribution, we attempt to provide compelling evidence, based on recent research, with the aim to promote a change in the predominant paradigm implemented in ecosystem models.
Agustín Sarquis, Ignacio Andrés Siebenhart, Amy Theresa Austin, and Carlos A. Sierra
Earth Syst. Sci. Data, 14, 3471–3488, https://doi.org/10.5194/essd-14-3471-2022, https://doi.org/10.5194/essd-14-3471-2022, 2022
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Plant litter breakdown in aridlands is driven by processes different from those in more humid ecosystems. A better understanding of these processes will allow us to make better predictions of future carbon cycling. We have compiled aridec, a database of plant litter decomposition studies in aridlands and tested some modeling applications for potential users. Aridec is open for use and collaboration, and we hope it will help answer newer and more important questions as the database develops.
Carlos A. Sierra, Susan E. Crow, Martin Heimann, Holger Metzler, and Ernst-Detlef Schulze
Biogeosciences, 18, 1029–1048, https://doi.org/10.5194/bg-18-1029-2021, https://doi.org/10.5194/bg-18-1029-2021, 2021
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The climate benefit of carbon sequestration (CBS) is a metric developed to quantify avoided warming by two separate processes: the amount of carbon drawdown from the atmosphere and the time this carbon is stored in a reservoir. This metric can be useful for quantifying the role of forests and soils for climate change mitigation and to better quantify the benefits of carbon removals by sinks.
Christina Schädel, Jeffrey Beem-Miller, Mina Aziz Rad, Susan E. Crow, Caitlin E. Hicks Pries, Jessica Ernakovich, Alison M. Hoyt, Alain Plante, Shane Stoner, Claire C. Treat, and Carlos A. Sierra
Earth Syst. Sci. Data, 12, 1511–1524, https://doi.org/10.5194/essd-12-1511-2020, https://doi.org/10.5194/essd-12-1511-2020, 2020
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Carbon loss to the atmosphere via microbial decomposition is often assessed by laboratory soil incubation studies that measure greenhouse gases released from soils under controlled conditions. Here, we introduce the Soil Incubation Database (SIDb) version 1.0, a compilation of time series data from incubations, structured into a new, publicly available, open-access database of carbon dioxide and methane flux. We also provide guidance for database entry and the required variables.
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020, https://doi.org/10.5194/bg-17-945-2020, 2020
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Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems. It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered. This scale dependency should be considered for modeling land–atmosphere interactions.
Corey R. Lawrence, Jeffrey Beem-Miller, Alison M. Hoyt, Grey Monroe, Carlos A. Sierra, Shane Stoner, Katherine Heckman, Joseph C. Blankinship, Susan E. Crow, Gavin McNicol, Susan Trumbore, Paul A. Levine, Olga Vindušková, Katherine Todd-Brown, Craig Rasmussen, Caitlin E. Hicks Pries, Christina Schädel, Karis McFarlane, Sebastian Doetterl, Christine Hatté, Yujie He, Claire Treat, Jennifer W. Harden, Margaret S. Torn, Cristian Estop-Aragonés, Asmeret Asefaw Berhe, Marco Keiluweit, Ágatha Della Rosa Kuhnen, Erika Marin-Spiotta, Alain F. Plante, Aaron Thompson, Zheng Shi, Joshua P. Schimel, Lydia J. S. Vaughn, Sophie F. von Fromm, and Rota Wagai
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The International Soil Radiocarbon Database (ISRaD) is an an open-source archive of soil data focused on datasets including radiocarbon measurements. ISRaD includes data from bulk or
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Verónika Ceballos-Núñez, Andrew D. Richardson, and Carlos A. Sierra
Biogeosciences, 15, 1607–1625, https://doi.org/10.5194/bg-15-1607-2018, https://doi.org/10.5194/bg-15-1607-2018, 2018
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Will the terrestrial biosphere be a carbon source or sink in the future? Different model simulations cannot reach a consensus, so we need to diagnose the performance of these models. We implemented three models differing in their carbon allocation strategies and assessed their performance using three metrics. The most sensible metric was the distribution of carbon age and transit times. Thus, empirical measurements of these distributions could be key to reduce the model uncertainty.
Carlos A. Sierra, Saadatullah Malghani, and Henry W. Loescher
Biogeosciences, 14, 703–710, https://doi.org/10.5194/bg-14-703-2017, https://doi.org/10.5194/bg-14-703-2017, 2017
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Temperature, moisture, and oxygen are interacting variables that control the rates of soil organic matter decomposition. With a well-replicated experiment, the authors show that decomposition rates in a boreal forest soil are not limited at high temperatures in the presence of enough water and oxygen. Similarly, at high humidity, oxygen is the main limiting factor for decomposition. The authors conclude that interactions among the three variables are the main determinants of decomposition rates.
C. A. Sierra, E. M. Jiménez, B. Reu, M. C. Peñuela, A. Thuille, and C. A. Quesada
Biogeosciences, 10, 3455–3464, https://doi.org/10.5194/bg-10-3455-2013, https://doi.org/10.5194/bg-10-3455-2013, 2013
Ingrid Chanca, Ingeborg Levin, Susan Trumbore, Kita Macario, Jost Lavric, Carlos Alberto Quesada, Alessandro Carioca de Araújo, Cléo Quaresma Dias Júnior, Hella van Asperen, Samuel Hammer, and Carlos A. Sierra
Biogeosciences, 22, 455–472, https://doi.org/10.5194/bg-22-455-2025, https://doi.org/10.5194/bg-22-455-2025, 2025
Short summary
Short summary
Assessing the net carbon (C) budget of the Amazon entails considering the magnitude and timing of C absorption and losses through respiration (transit time of C). Radiocarbon-based estimates of the transit time of C in the Amazon Tall Tower Observatory (ATTO) suggest a change in the transit time from 6 ± 2 years and 18 ± 4 years within 2 years (October 2019 and December 2021, respectively). This variability indicates that only a fraction of newly fixed C can be stored for decades or longer.
Luciano Emmert, Susan Trumbore, Joaquim dos Santos, Adriano Lima, Niro Higuchi, Robinson Negrón-Juárez, Cléo Dias-Júnior, Tarek El-Madany, Olaf Kolle, Gabriel Ribeiro, and Daniel Marra
EGUsphere, https://doi.org/10.5194/egusphere-2024-3234, https://doi.org/10.5194/egusphere-2024-3234, 2024
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For the first time, we documented wind gusts with the potential to damage trees in a forest in the Central Amazon. We used meteorological data collected at crown height over 24 months. We recorded 424 gusts, which occur more frequently and intensely in higher elevated areas and during the transition from the dry to the wet season. More intense rains showed the strongest relationship with extreme winds, highlighting the role of extreme events in tree mortality.
Luiz A. T. Machado, Jürgen Kesselmeier, Santiago Botía, Hella van Asperen, Meinrat O. Andreae, Alessandro C. de Araújo, Paulo Artaxo, Achim Edtbauer, Rosaria R. Ferreira, Marco A. Franco, Hartwig Harder, Sam P. Jones, Cléo Q. Dias-Júnior, Guido G. Haytzmann, Carlos A. Quesada, Shujiro Komiya, Jost Lavric, Jos Lelieveld, Ingeborg Levin, Anke Nölscher, Eva Pfannerstill, Mira L. Pöhlker, Ulrich Pöschl, Akima Ringsdorf, Luciana Rizzo, Ana M. Yáñez-Serrano, Susan Trumbore, Wanda I. D. Valenti, Jordi Vila-Guerau de Arellano, David Walter, Jonathan Williams, Stefan Wolff, and Christopher Pöhlker
Atmos. Chem. Phys., 24, 8893–8910, https://doi.org/10.5194/acp-24-8893-2024, https://doi.org/10.5194/acp-24-8893-2024, 2024
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Composite analysis of gas concentration before and after rainfall, during the day and night, gives insight into the complex relationship between trace gas variability and precipitation. The analysis helps us to understand the sources and sinks of trace gases within a forest ecosystem. It elucidates processes that are not discernible under undisturbed conditions and contributes to a deeper understanding of the trace gas life cycle and its intricate interactions with cloud dynamics in the Amazon.
Hella van Asperen, Thorsten Warneke, Alessandro Carioca de Araújo, Bruce Forsberg, Sávio José Filgueiras Ferreira, Thomas Röckmann, Carina van der Veen, Sipko Bulthuis, Leonardo Ramos de Oliveira, Thiago de Lima Xavier, Jailson da Mata, Marta de Oliveira Sá, Paulo Ricardo Teixeira, Julie Andrews de França e Silva, Susan Trumbore, and Justus Notholt
Biogeosciences, 21, 3183–3199, https://doi.org/10.5194/bg-21-3183-2024, https://doi.org/10.5194/bg-21-3183-2024, 2024
Short summary
Short summary
Carbon monoxide (CO) is regarded as an important indirect greenhouse gas. Soils can emit and take up CO, but, until now, uncertainty remains as to which process dominates in tropical rainforests. We present the first soil CO flux measurements from a tropical rainforest. Based on our observations, we report that tropical rainforest soils are a net source of CO. In addition, we show that valley streams and inundated areas are likely additional hot spots of CO in the ecosystem.
Maximiliano González-Sosa, Carlos A. Sierra, J. Andrés Quincke, Walter E. Baethgen, Susan Trumbore, and M. Virginia Pravia
SOIL, 10, 467–486, https://doi.org/10.5194/soil-10-467-2024, https://doi.org/10.5194/soil-10-467-2024, 2024
Short summary
Short summary
Based on an approach that involved soil organic carbon (SOC) monitoring, radiocarbon measurement in bulk soil, and incubations from a long-term 60-year experiment, it was concluded that the avoidance of old carbon losses in the integrated crop–pasture systems is the main reason that explains their greater carbon storage capacities compared to continuous cropping. A better understanding of these processes is essential for making agronomic decisions to increase the carbon sequestration capacity.
Andrés Tangarife-Escobar, Georg Guggenberger, Xiaojuan Feng, Guohua Dai, Carolina Urbina-Malo, Mina Azizi-Rad, and Carlos A. Sierra
Biogeosciences, 21, 1277–1299, https://doi.org/10.5194/bg-21-1277-2024, https://doi.org/10.5194/bg-21-1277-2024, 2024
Short summary
Short summary
Soil organic matter stability depends on future temperature and precipitation scenarios. We used radiocarbon (14C) data and model predictions to understand how the transit time of carbon varies under environmental change in grasslands and peatlands. Soil moisture affected the Δ14C of peatlands, while temperature did not have any influence. Our models show the correspondence between Δ14C and transit time and could allow understanding future interactions between terrestrial and atmospheric carbon
Adriana Simonetti, Raquel Fernandes Araujo, Carlos Henrique Souza Celes, Flávia Ranara da Silva e Silva, Joaquim dos Santos, Niro Higuchi, Susan Trumbore, and Daniel Magnabosco Marra
Biogeosciences, 20, 3651–3666, https://doi.org/10.5194/bg-20-3651-2023, https://doi.org/10.5194/bg-20-3651-2023, 2023
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We combined 2 years of monthly drone-acquired RGB (red–green–blue) imagery with field surveys in a central Amazon forest. Our results indicate that small gaps associated with branch fall were the most frequent. Biomass losses were partially controlled by gap area, with branch fall and snapping contributing the least and greatest relative values, respectively. Our study highlights the potential of drone images for monitoring canopy dynamics in dense tropical forests.
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.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
Short summary
Short summary
Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Song Wang, Carlos Sierra, Yiqi Luo, Jinsong Wang, Weinan Chen, Yahai Zhang, Aizhong Ye, and Shuli Niu
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-33, https://doi.org/10.5194/bg-2023-33, 2023
Manuscript not accepted for further review
Short summary
Short summary
Nitrogen is important for plant growth and carbon uptake, which is uaually limited in nature and can constrain carbon storage and impact efforts to combat climate change. We developed a new method of combining data and models to determine if and how much an ecosystem is nitrogen limited. This new method can help determine if and to what extent an ecosystem is nitrogen-limited, providing insight into nutrient limitations on a global scale and guiding ecosystem management decisions.
Andrea Scheibe, Carlos A. Sierra, and Marie Spohn
Biogeosciences, 20, 827–838, https://doi.org/10.5194/bg-20-827-2023, https://doi.org/10.5194/bg-20-827-2023, 2023
Short summary
Short summary
We explored carbon cycling in soils in three climate zones in Chile down to a depth of 6 m, using carbon isotopes. Our results show that microbial activity several meters below the soil surface is mostly fueled by recently fixed carbon and that strong decomposition of soil organic matter only occurs in the upper decimeters of the soils. The study shows that different layers of the critical zone are tightly connected and that processes in the deep soil depend on recently fixed carbon.
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
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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.
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.
Carlos A. Sierra, Verónika Ceballos-Núñez, Henrik Hartmann, David Herrera-Ramírez, and Holger Metzler
Biogeosciences, 19, 3727–3738, https://doi.org/10.5194/bg-19-3727-2022, https://doi.org/10.5194/bg-19-3727-2022, 2022
Short summary
Short summary
Empirical work that estimates the age of respired CO2 from vegetation tissue shows that it may take from years to decades to respire previously produced photosynthates. However, many ecosystem models represent respiration processes in a form that cannot reproduce these observations. In this contribution, we attempt to provide compelling evidence, based on recent research, with the aim to promote a change in the predominant paradigm implemented in ecosystem models.
Agustín Sarquis, Ignacio Andrés Siebenhart, Amy Theresa Austin, and Carlos A. Sierra
Earth Syst. Sci. Data, 14, 3471–3488, https://doi.org/10.5194/essd-14-3471-2022, https://doi.org/10.5194/essd-14-3471-2022, 2022
Short summary
Short summary
Plant litter breakdown in aridlands is driven by processes different from those in more humid ecosystems. A better understanding of these processes will allow us to make better predictions of future carbon cycling. We have compiled aridec, a database of plant litter decomposition studies in aridlands and tested some modeling applications for potential users. Aridec is open for use and collaboration, and we hope it will help answer newer and more important questions as the database develops.
Sophie F. von Fromm, Alison M. Hoyt, Markus Lange, Gifty E. Acquah, Ermias Aynekulu, Asmeret Asefaw Berhe, Stephan M. Haefele, Steve P. McGrath, Keith D. Shepherd, Andrew M. Sila, Johan Six, Erick K. Towett, Susan E. Trumbore, Tor-G. Vågen, Elvis Weullow, Leigh A. Winowiecki, and Sebastian Doetterl
SOIL, 7, 305–332, https://doi.org/10.5194/soil-7-305-2021, https://doi.org/10.5194/soil-7-305-2021, 2021
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We investigated various soil and climate properties that influence soil organic carbon (SOC) concentrations in sub-Saharan Africa. Our findings indicate that climate and geochemistry are equally important for explaining SOC variations. The key SOC-controlling factors are broadly similar to those for temperate regions, despite differences in soil development history between the two regions.
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
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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.
Carlos A. Sierra, Susan E. Crow, Martin Heimann, Holger Metzler, and Ernst-Detlef Schulze
Biogeosciences, 18, 1029–1048, https://doi.org/10.5194/bg-18-1029-2021, https://doi.org/10.5194/bg-18-1029-2021, 2021
Short summary
Short summary
The climate benefit of carbon sequestration (CBS) is a metric developed to quantify avoided warming by two separate processes: the amount of carbon drawdown from the atmosphere and the time this carbon is stored in a reservoir. This metric can be useful for quantifying the role of forests and soils for climate change mitigation and to better quantify the benefits of carbon removals by sinks.
Christina Schädel, Jeffrey Beem-Miller, Mina Aziz Rad, Susan E. Crow, Caitlin E. Hicks Pries, Jessica Ernakovich, Alison M. Hoyt, Alain Plante, Shane Stoner, Claire C. Treat, and Carlos A. Sierra
Earth Syst. Sci. Data, 12, 1511–1524, https://doi.org/10.5194/essd-12-1511-2020, https://doi.org/10.5194/essd-12-1511-2020, 2020
Short summary
Short summary
Carbon loss to the atmosphere via microbial decomposition is often assessed by laboratory soil incubation studies that measure greenhouse gases released from soils under controlled conditions. Here, we introduce the Soil Incubation Database (SIDb) version 1.0, a compilation of time series data from incubations, structured into a new, publicly available, open-access database of carbon dioxide and methane flux. We also provide guidance for database entry and the required variables.
Ann-Sophie Lehnert, Thomas Behrendt, Alexander Ruecker, Georg Pohnert, and Susan E. Trumbore
Atmos. Meas. Tech., 13, 3507–3520, https://doi.org/10.5194/amt-13-3507-2020, https://doi.org/10.5194/amt-13-3507-2020, 2020
Short summary
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Volatile organic compounds (VOCs) like scents can appear and disappear quickly. For example, when a bug starts on a tree, the tree releases VOCs that warn the trees around him. Thus, one needs instruments measuring their concentration in real time and identify which VOC is measured. In our study, we compared two instruments doing that, PTR-MS and SIFT-MS. Both work similarly, but we found that the PTR-MS can measure lower concentrations, but the SIFT-MS can identify VOCs better.
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020, https://doi.org/10.5194/bg-17-945-2020, 2020
Short summary
Short summary
Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems. It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered. This scale dependency should be considered for modeling land–atmosphere interactions.
Corey R. Lawrence, Jeffrey Beem-Miller, Alison M. Hoyt, Grey Monroe, Carlos A. Sierra, Shane Stoner, Katherine Heckman, Joseph C. Blankinship, Susan E. Crow, Gavin McNicol, Susan Trumbore, Paul A. Levine, Olga Vindušková, Katherine Todd-Brown, Craig Rasmussen, Caitlin E. Hicks Pries, Christina Schädel, Karis McFarlane, Sebastian Doetterl, Christine Hatté, Yujie He, Claire Treat, Jennifer W. Harden, Margaret S. Torn, Cristian Estop-Aragonés, Asmeret Asefaw Berhe, Marco Keiluweit, Ágatha Della Rosa Kuhnen, Erika Marin-Spiotta, Alain F. Plante, Aaron Thompson, Zheng Shi, Joshua P. Schimel, Lydia J. S. Vaughn, Sophie F. von Fromm, and Rota Wagai
Earth Syst. Sci. Data, 12, 61–76, https://doi.org/10.5194/essd-12-61-2020, https://doi.org/10.5194/essd-12-61-2020, 2020
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The International Soil Radiocarbon Database (ISRaD) is an an open-source archive of soil data focused on datasets including radiocarbon measurements. ISRaD includes data from bulk or
whole soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil surface.
Shaun R. Levick, Anna E. Richards, Garry D. Cook, Jon Schatz, Marcus Guderle, Richard J. Williams, Parash Subedi, Susan E. Trumbore, and Alan N. Andersen
Biogeosciences, 16, 1493–1503, https://doi.org/10.5194/bg-16-1493-2019, https://doi.org/10.5194/bg-16-1493-2019, 2019
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We used airborne lidar to map the three-dimensional structure and model the biomass of plant canopies across a long-term fire experiment in the Northern Territory of Australia. Our results show that late season fires occurring every 2 years reduce the amount of carbon stored above-ground by 50 % relative to unburnt control plots. We also show how increased fire intensity removes the shrub layer from savannas and discuss the implications for biodiversity conservation.
Thomas Behrendt, Elisa C. P. Catão, Rüdiger Bunk, Zhigang Yi, Elena Schweer, Steffen Kolb, Jürgen Kesselmeier, and Susan Trumbore
SOIL, 5, 121–135, https://doi.org/10.5194/soil-5-121-2019, https://doi.org/10.5194/soil-5-121-2019, 2019
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We measured net fluxes of OCS from nine soils with different land use in a dynamic chamber system and analyzed for one soil RNA relative abundance and gene transcripts. Our data suggest that indeed carbonic anhydrase (CA) plays an important role for OCS exchange, but the role of other enzymes might have been underestimated. Our study is the first assessment of the environmental significance of different microbial groups producing and consuming OCS by various enzymes other than CA.
Boaz Hilman, Jan Muhr, Susan E. Trumbore, Norbert Kunert, Mariah S. Carbone, Päivi Yuval, S. Joseph Wright, Gerardo Moreno, Oscar Pérez-Priego, Mirco Migliavacca, Arnaud Carrara, José M. Grünzweig, Yagil Osem, Tal Weiner, and Alon Angert
Biogeosciences, 16, 177–191, https://doi.org/10.5194/bg-16-177-2019, https://doi.org/10.5194/bg-16-177-2019, 2019
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Combined measurement of CO2 / O2 fluxes in tree stems suggested that on average 41 % of the respired CO2 was not emitted locally to the atmosphere. This finding strengthens the recognition that CO2 efflux from tree stems is not an accurate measure of respiration. The CO2 / O2 fluxes did not vary as expected if CO2 dissolution in the xylem sap was the main driver for the CO2 retention. We suggest the examination of refixation of respired CO2 as a possible mechanism for CO2 retention.
Verónika Ceballos-Núñez, Andrew D. Richardson, and Carlos A. Sierra
Biogeosciences, 15, 1607–1625, https://doi.org/10.5194/bg-15-1607-2018, https://doi.org/10.5194/bg-15-1607-2018, 2018
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Will the terrestrial biosphere be a carbon source or sink in the future? Different model simulations cannot reach a consensus, so we need to diagnose the performance of these models. We implemented three models differing in their carbon allocation strategies and assessed their performance using three metrics. The most sensible metric was the distribution of carbon age and transit times. Thus, empirical measurements of these distributions could be key to reduce the model uncertainty.
Bernd Kohlhepp, Robert Lehmann, Paul Seeber, Kirsten Küsel, Susan E. Trumbore, and Kai U. Totsche
Hydrol. Earth Syst. Sci., 21, 6091–6116, https://doi.org/10.5194/hess-21-6091-2017, https://doi.org/10.5194/hess-21-6091-2017, 2017
Martin E. Nowak, Valérie F. Schwab, Cassandre S. Lazar, Thomas Behrendt, Bernd Kohlhepp, Kai Uwe Totsche, Kirsten Küsel, and Susan E. Trumbore
Hydrol. Earth Syst. Sci., 21, 4283–4300, https://doi.org/10.5194/hess-21-4283-2017, https://doi.org/10.5194/hess-21-4283-2017, 2017
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In the present study we combined measurements of dissolved inorganic carbon (DIC) isotopes with a set of different geochemical and microbiological methods in order to get a comprehensive view of biogeochemical cycling and groundwater flow in two limestone aquifer assemblages. This allowed us to understand interactions and feedbacks between microbial communities, their carbon sources, and water chemistry.
Valérie F. Schwab, Martina Herrmann, Vanessa-Nina Roth, Gerd Gleixner, Robert Lehmann, Georg Pohnert, Susan Trumbore, Kirsten Küsel, and Kai U. Totsche
Biogeosciences, 14, 2697–2714, https://doi.org/10.5194/bg-14-2697-2017, https://doi.org/10.5194/bg-14-2697-2017, 2017
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We used phospholipid fatty acids (PLFAs) to link specific microbial markers to the spatio-temporal changes of groundwater physico-chemistry. PLFA-based functional groups were directly supported by DNA/RNA results. O2 resulted in increased eukaryotic biomass and abundance of nitrite-oxidizing bacteria but impeded anammox, sulphate-reducing and iron-reducing bacteria. Our study demonstrates the power of PLFA-based approaches to study the nature and activity of microorganisms in pristine aquifers.
Carlos A. Sierra, Saadatullah Malghani, and Henry W. Loescher
Biogeosciences, 14, 703–710, https://doi.org/10.5194/bg-14-703-2017, https://doi.org/10.5194/bg-14-703-2017, 2017
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Temperature, moisture, and oxygen are interacting variables that control the rates of soil organic matter decomposition. With a well-replicated experiment, the authors show that decomposition rates in a boreal forest soil are not limited at high temperatures in the presence of enough water and oxygen. Similarly, at high humidity, oxygen is the main limiting factor for decomposition. The authors conclude that interactions among the three variables are the main determinants of decomposition rates.
Lesego Khomo, Susan Trumbore, Carleton R. Bern, and Oliver A. Chadwick
SOIL, 3, 17–30, https://doi.org/10.5194/soil-3-17-2017, https://doi.org/10.5194/soil-3-17-2017, 2017
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We evaluated mineral control of organic carbon dynamics by relating the content and age of carbon stored in soils of varied mineralogical composition found in the landscapes of Kruger National Park, South Africa. Carbon associated with smectite clay minerals, which have stronger surface–organic matter interactions, averaged about a thousand years old, while most soil carbon was only decades to centuries old and was associated with iron and aluminum oxide minerals.
Daniel Magnabosco Marra, Niro Higuchi, Susan E. Trumbore, Gabriel H. P. M. Ribeiro, Joaquim dos Santos, Vilany M. C. Carneiro, Adriano J. N. Lima, Jeffrey Q. Chambers, Robinson I. Negrón-Juárez, Frederic Holzwarth, Björn Reu, and Christian Wirth
Biogeosciences, 13, 1553–1570, https://doi.org/10.5194/bg-13-1553-2016, https://doi.org/10.5194/bg-13-1553-2016, 2016
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Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases.
Leandro T. dos Santos, Daniel Magnabosco Marra, Susan Trumbore, Plínio B. de Camargo, Robinson I. Negrón-Juárez, Adriano J. N. Lima, Gabriel H. P. M. Ribeiro, Joaquim dos Santos, and Niro Higuchi
Biogeosciences, 13, 1299–1308, https://doi.org/10.5194/bg-13-1299-2016, https://doi.org/10.5194/bg-13-1299-2016, 2016
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In the Amazon forest, wind disturbances can create canopy gaps of many hundreds of hectares. We show that inputs of plant litter associated with large windthrows cause a short-term increase in soil carbon stock. The degree of increase is related to soil clay content and tree mortality intensity. The higher carbon content and potentially higher nutrient availability in soils from areas recovering from windthrows may favor forest regrowth and increase vegetation resilience.
M. E. Nowak, F. Beulig, J. von Fischer, J. Muhr, K. Küsel, and S. E. Trumbore
Biogeosciences, 12, 7169–7183, https://doi.org/10.5194/bg-12-7169-2015, https://doi.org/10.5194/bg-12-7169-2015, 2015
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Microorganisms have been recognized as an important source of soil organic matter (SOM). Autotrophic microorganisms utilize CO2 instead of organic carbon. Microbial CO2 fixation is accompanied with high 13C isotope discrimination. Because autotrophs are abundant in soils, they might be a significant factor influencing 13C signatures of SOM. Thus, it is important to asses the importance of autotrophs for C isotope signatures in soils, in order to use isotopes as a tracer for soil C dynamics.
M. O. Andreae, O. C. Acevedo, A. Araùjo, P. Artaxo, C. G. G. Barbosa, H. M. J. Barbosa, J. Brito, S. Carbone, X. Chi, B. B. L. Cintra, N. F. da Silva, N. L. Dias, C. Q. Dias-Júnior, F. Ditas, R. Ditz, A. F. L. Godoi, R. H. M. Godoi, M. Heimann, T. Hoffmann, J. Kesselmeier, T. Könemann, M. L. Krüger, J. V. Lavric, A. O. Manzi, A. P. Lopes, D. L. Martins, E. F. Mikhailov, D. Moran-Zuloaga, B. W. Nelson, A. C. Nölscher, D. Santos Nogueira, M. T. F. Piedade, C. Pöhlker, U. Pöschl, C. A. Quesada, L. V. Rizzo, C.-U. Ro, N. Ruckteschler, L. D. A. Sá, M. de Oliveira Sá, C. B. Sales, R. M. N. dos Santos, J. Saturno, J. Schöngart, M. Sörgel, C. M. de Souza, R. A. F. de Souza, H. Su, N. Targhetta, J. Tóta, I. Trebs, S. Trumbore, A. van Eijck, D. Walter, Z. Wang, B. Weber, J. Williams, J. Winderlich, F. Wittmann, S. Wolff, and A. M. Yáñez-Serrano
Atmos. Chem. Phys., 15, 10723–10776, https://doi.org/10.5194/acp-15-10723-2015, https://doi.org/10.5194/acp-15-10723-2015, 2015
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This paper describes the Amazon Tall Tower Observatory (ATTO), a new atmosphere-biosphere observatory located in the remote Amazon Basin. It presents results from ecosystem ecology, meteorology, trace gas, and aerosol measurements collected at the ATTO site during the first 3 years of operation.
B. Ahrens, M. Reichstein, W. Borken, J. Muhr, S. E. Trumbore, and T. Wutzler
Biogeosciences, 11, 2147–2168, https://doi.org/10.5194/bg-11-2147-2014, https://doi.org/10.5194/bg-11-2147-2014, 2014
M. S. Torn, M. Kleber, E. S. Zavaleta, B. Zhu, C. B. Field, and S. E. Trumbore
Biogeosciences, 10, 8067–8081, https://doi.org/10.5194/bg-10-8067-2013, https://doi.org/10.5194/bg-10-8067-2013, 2013
E. Solly, I. Schöning, S. Boch, J. Müller, S. A. Socher, S. E. Trumbore, and M. Schrumpf
Biogeosciences, 10, 4833–4843, https://doi.org/10.5194/bg-10-4833-2013, https://doi.org/10.5194/bg-10-4833-2013, 2013
C. A. Sierra, E. M. Jiménez, B. Reu, M. C. Peñuela, A. Thuille, and C. A. Quesada
Biogeosciences, 10, 3455–3464, https://doi.org/10.5194/bg-10-3455-2013, https://doi.org/10.5194/bg-10-3455-2013, 2013
Related subject area
Biogeosciences
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
Parameterisation toolbox for physical-biogeochemical model compatible with FABM. Case study: the coupled 1D GOTM-ECOSMO E2E for the Sylt-Romo Bight, North Sea
China Wildfire Emission (ChinaWED v1) for the period 2012–2022
H2MV (v1.0): Global Physically-Constrained Deep Learning Water Cycle Model with Vegetation
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Including the Phosphorus cycle into the LPJ-GUESS Dynamic Global Vegetation Model (v4.1, r10994) – Global patterns and temporal trends of N and P primary production limitation
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Sources of Uncertainty in the Global Fire Model SPITFIRE: Development of LPJmL-SPITFIRE1.9 and Directions for Future Improvements
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
A comprehensive land surface vegetation model for multi-stream data assimilation, D&B v1.0
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Process-based Modeling of Solar-induced Chlorophyll Fluorescence with VISIT-SIF version 1.0
The unicellular NUM v.0.91: A trait-based plankton model evaluated in two contrasting biogeographic provinces
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
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Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
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Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
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Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-223, https://doi.org/10.5194/gmd-2024-223, 2024
Revised manuscript accepted for GMD
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Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions have changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
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The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
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In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
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The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
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This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
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We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
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Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
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We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
EGUsphere, https://doi.org/10.5194/egusphere-2024-2710, https://doi.org/10.5194/egusphere-2024-2710, 2024
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Parameterisation is key in modeling to reproduce observations well but is often done manually. This study presents a Particle Swarm Optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, thus providing different insights into ecosystem dynamics, (2) optimized model complexity.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-170, https://doi.org/10.5194/gmd-2024-170, 2024
Revised manuscript accepted for GMD
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Wildfires release large amounts of greenhouse gases, contributing to global warming. We developed a new model that provides near-real-time estimates of wildfire emissions in China. Our model improves the accuracy of burned area measurements and incorporates advanced data in fuel loads and emission factors. We found that most emissions come from agricultural fires, while emissions from forests and grasslands are decreasing. This model will help reduce the environmental impacts of wildfires.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
EGUsphere, https://doi.org/10.5194/egusphere-2024-2044, https://doi.org/10.5194/egusphere-2024-2044, 2024
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We use an innovative approach to study the Earth's water cycle by blending advanced computer learning techniques with a traditional water cycle model. We developed a model that learns from meteorological data, with a special focus on understanding how vegetation influences water movement. Our model closely aligns with real-world observations, yet there are areas that need improvement. This study opens up new possibilities to better understand the water cycle and its interactions with vegetation.
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.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
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The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
EGUsphere, https://doi.org/10.5194/egusphere-2024-2592, https://doi.org/10.5194/egusphere-2024-2592, 2024
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Our study maps global nitrogen (N) and phosphorus (P) availability and how they’ve changed from 1901 to 2018. We found that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation has increased, especially in the tropics, while N limitation has decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
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In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
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A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
EGUsphere, https://doi.org/10.5194/egusphere-2024-1914, https://doi.org/10.5194/egusphere-2024-1914, 2024
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Under climate change, the conditions for wildfires to form are becoming more frequent in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a crucial platform for future developments.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
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A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
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We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
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To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
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This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, Luke Smallmann, Susan Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zähle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek El-Madany, Mirco Migliavacca, Marika Honkanen, Yann Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaetan Pique, Amanda Ojasalo, Shaun Quegan, Peter Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
EGUsphere, https://doi.org/10.5194/egusphere-2024-1534, https://doi.org/10.5194/egusphere-2024-1534, 2024
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When it comes to climate change, the land surfaces are where the vast majority of impacts happen. The task of monitoring those across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us see what changes on our lands.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
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Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
EGUsphere, https://doi.org/10.5194/egusphere-2024-1542, https://doi.org/10.5194/egusphere-2024-1542, 2024
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Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical process-based model developed to represent the global SIF observed by GOSAT. Our model simulation reproduced the global distribution and seasonal variations of GOSAT SIF. The model can be utilized to improve photosynthetic process through the combination of biogeochemical modeling and GOSAT SIF.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-53, https://doi.org/10.5194/gmd-2024-53, 2024
Revised manuscript accepted for GMD
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We describe and test the size-based NUM model, that define organisms by a single set of parameters, on planktonic unicellular ecosystems in a eutrophic and an oligotrophic site. Results show both sites can be modelled with similar parameters, and a robust performance over a wide range of parameters. The study show that the NUM model is useful for non-experts and applicable for modelling domains with limited ecosystem data. It holds promise for evolutionary scenarios and deep-time climate models.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
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We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1360, https://doi.org/10.5194/egusphere-2024-1360, 2024
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Our research uses deep learning to predict organic carbon stocks in ocean sediments, crucial for understanding their role in the global carbon cycle. By analyzing over 22,000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate the top 10 cm of ocean sediments hold about 171 petagrams of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
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Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
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Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
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Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
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We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
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By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
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
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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.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
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Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
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Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
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By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
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Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
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Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
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To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
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Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
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Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
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This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
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Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
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We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Cited articles
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Brovkin, V., Cherkinsky, A., and Goryachkin, S.: Estimating soil carbon turnover using radiocarbon data: a case-study for European Russia, Ecol. Model., 216, 178–187, https://doi.org/10.1016/j.ecolmodel.2008.03.018, 2008.
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