Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-931-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-931-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
05 Feb 2024
Model description paper |
| 05 Feb 2024
| 05 Feb 2024
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
Sustainable Agroecosystems Group, Department of Environmental Systems Science, Swiss Federal Institute of Technology (ETH Zurich), Universitätstrasse 2, 8092 Zurich, Switzerland
Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, 70599 Stuttgart, Germany
Sergey Blagodatsky
Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, 70599 Stuttgart, Germany
Terrestrial Ecology Group, Institute of Zoology, University of Cologne, Zülpicher Str. 47b, 50674 Cologne, Germany
Marijn Van de Broek
Sustainable Agroecosystems Group, Department of Environmental Systems Science, Swiss Federal Institute of Technology (ETH Zurich), Universitätstrasse 2, 8092 Zurich, Switzerland
Samuel Schlichenmaier
Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, 70599 Stuttgart, Germany
Benjapon Kunlanit
Soil Organic Matter Management Research Group, Khon Kaen University, Khon Kaen, Thailand
Department of Agricultural Technology, Faculty of Technology, Mahasarakham University, Maha Sarakham, Thailand
Johan Six
Sustainable Agroecosystems Group, Department of Environmental Systems Science, Swiss Federal Institute of Technology (ETH Zurich), Universitätstrasse 2, 8092 Zurich, Switzerland
Patma Vityakon
Department of Soil Science and Environment, Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand
Soil Organic Matter Management Research Group, Khon Kaen University, Khon Kaen, Thailand
Georg Cadisch
Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, 70599 Stuttgart, Germany
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Soil C saturation has been tested in several recent studies and led to a debate about its existence. We argue that, to test C saturation, one should pay attention to six fundamental principles: the right measures, the right units, the right dispersive energy and application, the right soil type, the right clay type, and the right saturation level. Once we take care of those six rights across studies, we find support for a maximum of C stabilized by minerals and thus soil C saturation.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
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Johan Six, Sebastian Doetterl, Moritz Laub, Claude R. Müller, and Marijn Van de Broek
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We assessed the long-term impacts of no-till cropping systems on soil organic carbon and nitrogen dynamics down to 1 m depth under the annual upland crop productions (cassava, maize, and soybean) in the tropical climate of Cambodia. We showed that no-till systems combined with rotations and cover crops could store large amounts of carbon in top and subsoil, in both the mineral organic-matter and particulate organic matter fractions. It also questions nitrogen management in these systems.
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SOIL, 10, 151–165, https://doi.org/10.5194/soil-10-151-2024, https://doi.org/10.5194/soil-10-151-2024, 2024
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Conservation agriculture (CA), combining reduced or no tillage, permanent soil cover, and improved rotations, is often promoted as a climate-smart practice. However, our knowledge of the impact of CA on top- and subsoil soil organic carbon (SOC) stocks in the low-input cropping systems of sub-Saharan Africa is rather limited. Using two long-term experimental sites with different soil types, we found that mulch could increase top SOC stocks, but no tillage alone had a slightly negative impact.
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Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-37, https://doi.org/10.5194/hess-2024-37, 2024
Preprint under review for HESS
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While rainwater is a key resource in crop production, its productivity faces challenges from climate change. Using a simple model of climate, water, and crop yield interactions, we found that rain-scarce croplands in Ethiopia are likely to experience decreases in crop yield during the main growing season, primarily due to future temperature increases. These insights are crucial for shaping future water management plans, policies, and informed decision-making for climate adaptation.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
EGUsphere, https://doi.org/10.5194/egusphere-2023-1738, https://doi.org/10.5194/egusphere-2023-1738, 2023
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Moritz Laub, Marc Corbeels, Antoine Couëdel, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Magdalena Necpalova, Wycliffe Waswa, Marijn Van de Broek, Bernard Vanlauwe, and Johan Six
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Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-221, https://doi.org/10.5194/bg-2022-221, 2022
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Presented are measurement results from six agricultural fields operated by local farmers in southwestern Germany over 9 years. Six eddy-covariance stations measuring water, energy, and carbon fluxes between the vegetated soil surface and the atmosphere provided the backbone of the measurement sites and were supplemented by extensive soil and vegetation state monitoring. The dataset is ideal for testing process models characterizing fluxes at the vegetated soil surface and in the atmosphere.
Florian Lauryssen, Philippe Crombé, Tom Maris, Elliot Van Maldegem, Marijn Van de Broek, Stijn Temmerman, and Erik Smolders
Biogeosciences, 19, 763–776, https://doi.org/10.5194/bg-19-763-2022, https://doi.org/10.5194/bg-19-763-2022, 2022
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Philipp Baumann, Juhwan Lee, Emmanuel Frossard, Laurie Paule Schönholzer, Lucien Diby, Valérie Kouamé Hgaza, Delwende Innocent Kiba, Andrew Sila, Keith Sheperd, and Johan Six
SOIL, 7, 717–731, https://doi.org/10.5194/soil-7-717-2021, https://doi.org/10.5194/soil-7-717-2021, 2021
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This work delivers openly accessible and validated calibrations for diagnosing 26 soil properties based on mid-infrared spectroscopy. These were developed for four regions in Burkina Faso and Côte d'Ivoire, including 80 fields of smallholder farmers. The models can help to site-specifically and cost-efficiently monitor soil quality and fertility constraints to ameliorate soils and yields of yam or other staple crops in the four regions between the humid forest and the northern Guinean savanna.
Laura Summerauer, Philipp Baumann, Leonardo Ramirez-Lopez, Matti Barthel, Marijn Bauters, Benjamin Bukombe, Mario Reichenbach, Pascal Boeckx, Elizabeth Kearsley, Kristof Van Oost, Bernard Vanlauwe, Dieudonné Chiragaga, Aimé Bisimwa Heri-Kazi, Pieter Moonen, Andrew Sila, Keith Shepherd, Basile Bazirake Mujinya, Eric Van Ranst, Geert Baert, Sebastian Doetterl, and Johan Six
SOIL, 7, 693–715, https://doi.org/10.5194/soil-7-693-2021, https://doi.org/10.5194/soil-7-693-2021, 2021
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We present a soil mid-infrared library with over 1800 samples from central Africa in order to facilitate soil analyses of this highly understudied yet critical area. Together with an existing continental library, we demonstrate a regional analysis and geographical extrapolation to predict total carbon and nitrogen. Our results show accurate predictions and highlight the value that the data contribute to existing libraries. Our library is openly available for public use and for expansion.
Sergio Naranjo, Francelino A. Rodrigues Jr., Georg Cadisch, Santiago Lopez-Ridaura, Mariela Fuentes Ponce, and Carsten Marohn
Hydrol. Earth Syst. Sci., 25, 5561–5588, https://doi.org/10.5194/hess-25-5561-2021, https://doi.org/10.5194/hess-25-5561-2021, 2021
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We integrate a spatially explicit soil erosion model with plot- and watershed-scale characterization and high-resolution drone imagery to assess the effect of spatial resolution digital terrain models (DTMs) on discharge and soil loss. Results showed reduction in slope due to resampling down of DTM. Higher resolution translates to higher slope, denser fluvial system, and extremer values of soil loss, reducing concentration time and increasing soil loss at the outlet. The best resolution was 4 m.
Sebastian Doetterl, Rodrigue K. Asifiwe, Geert Baert, Fernando Bamba, Marijn Bauters, Pascal Boeckx, Benjamin Bukombe, Georg Cadisch, Matthew Cooper, Landry N. Cizungu, Alison Hoyt, Clovis Kabaseke, Karsten Kalbitz, Laurent Kidinda, Annina Maier, Moritz Mainka, Julia Mayrock, Daniel Muhindo, Basile B. Mujinya, Serge M. Mukotanyi, Leon Nabahungu, Mario Reichenbach, Boris Rewald, Johan Six, Anna Stegmann, Laura Summerauer, Robin Unseld, Bernard Vanlauwe, Kristof Van Oost, Kris Verheyen, Cordula Vogel, Florian Wilken, and Peter Fiener
Earth Syst. Sci. Data, 13, 4133–4153, https://doi.org/10.5194/essd-13-4133-2021, https://doi.org/10.5194/essd-13-4133-2021, 2021
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The African Tropics are hotspots of modern-day land use change and are of great relevance for the global carbon cycle. Here, we present data collected as part of the DFG-funded project TropSOC along topographic, land use, and geochemical gradients in the eastern Congo Basin and the Albertine Rift. Our database contains spatial and temporal data on soil, vegetation, environmental properties, and land management collected from 136 pristine tropical forest and cropland plots between 2017 and 2020.
Philipp Baumann, Anatol Helfenstein, Andreas Gubler, Armin Keller, Reto Giulio Meuli, Daniel Wächter, Juhwan Lee, Raphael Viscarra Rossel, and Johan Six
SOIL, 7, 525–546, https://doi.org/10.5194/soil-7-525-2021, https://doi.org/10.5194/soil-7-525-2021, 2021
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We developed the Swiss mid-infrared spectral library and a statistical model collection across 4374 soil samples with reference measurements of 16 properties. Our library incorporates soil from 1094 grid locations and 71 long-term monitoring sites. This work confirms once again that nationwide spectral libraries with diverse soils can reliably feed information to a fast chemical diagnosis. Our data-driven reduction of the library has the potential to accurately monitor carbon at the plot scale.
Mario Reichenbach, Peter Fiener, Gina Garland, Marco Griepentrog, Johan Six, and Sebastian Doetterl
SOIL, 7, 453–475, https://doi.org/10.5194/soil-7-453-2021, https://doi.org/10.5194/soil-7-453-2021, 2021
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In deeply weathered tropical rainforest soils of Africa, we found that patterns of soil organic carbon stocks differ between soils developed from geochemically contrasting parent material due to differences in the abundance of organo-mineral complexes, the presence/absence of chemical stabilization mechanisms of carbon with minerals and the presence of fossil organic carbon from sedimentary rocks. Physical stabilization mechanisms by aggregation provide additional protection of soil carbon.
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.
Anatol Helfenstein, Philipp Baumann, Raphael Viscarra Rossel, Andreas Gubler, Stefan Oechslin, and Johan Six
SOIL, 7, 193–215, https://doi.org/10.5194/soil-7-193-2021, https://doi.org/10.5194/soil-7-193-2021, 2021
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In this study, we show that a soil spectral library (SSL) can be used to predict soil carbon at new and very different locations. The importance of this finding is that it requires less time-consuming lab work than calibrating a new model for every local application, while still remaining similar to or more accurate than local models. Furthermore, we show that this method even works for predicting (drained) peat soils, using a SSL with mostly mineral soils containing much less soil carbon.
Simon Baumgartner, Marijn Bauters, Matti Barthel, Travis W. Drake, Landry C. Ntaboba, Basile M. Bazirake, Johan Six, Pascal Boeckx, and Kristof Van Oost
SOIL, 7, 83–94, https://doi.org/10.5194/soil-7-83-2021, https://doi.org/10.5194/soil-7-83-2021, 2021
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We compared stable isotope signatures of soil profiles in different forest ecosystems within the Congo Basin to assess ecosystem-level differences in N cycling, and we examined the local effect of topography on the isotopic signature of soil N. Soil δ15N profiles indicated that the N cycling in in the montane forest is more closed, whereas the lowland forest and Miombo woodland experienced a more open N cycle. Topography only alters soil δ15N values in forests with high erosional forces.
Simon Baumgartner, Matti Barthel, Travis William Drake, Marijn Bauters, Isaac Ahanamungu Makelele, John Kalume Mugula, Laura Summerauer, Nora Gallarotti, Landry Cizungu Ntaboba, Kristof Van Oost, Pascal Boeckx, Sebastian Doetterl, Roland Anton Werner, and Johan Six
Biogeosciences, 17, 6207–6218, https://doi.org/10.5194/bg-17-6207-2020, https://doi.org/10.5194/bg-17-6207-2020, 2020
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Soil respiration is an important carbon flux and key process determining the net ecosystem production of terrestrial ecosystems. The Congo Basin lacks studies quantifying carbon fluxes. We measured soil CO2 fluxes from different forest types in the Congo Basin and were able to show that, even though soil CO2 fluxes are similarly high in lowland and montane forests, the drivers were different: soil moisture in montane forests and C availability in the lowland forests.
Long Ho, Ruben Jerves-Cobo, Matti Barthel, Johan Six, Samuel Bode, Pascal Boeckx, and Peter Goethals
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-311, https://doi.org/10.5194/bg-2020-311, 2020
Revised manuscript not accepted
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Rivers are being polluted by human activities, especially in urban areas. We studied the greenhouse gas (GHG) emissions from an urban river system. The results showed a clear trend between water quality and GHG emissions in which the more polluted the sites were, the higher were their emissions. When river water quality worsened, its contribution to global warming can go up by 10 times. Urban rivers emitted 4-times more than of the amount of GHGs compared to rivers in natural sites.
Marijn Van de Broek, Shiva Ghiasi, Charlotte Decock, Andreas Hund, Samuel Abiven, Cordula Friedli, Roland A. Werner, and Johan Six
Biogeosciences, 17, 2971–2986, https://doi.org/10.5194/bg-17-2971-2020, https://doi.org/10.5194/bg-17-2971-2020, 2020
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Four wheat cultivars were labeled with 13CO2 to quantify the effect of rooting depth and root biomass on the belowground transfer of organic carbon. We found no clear relation between the time since cultivar development and the amount of carbon inputs to the soil. Therefore, the hypothesis that wheat cultivars with a larger root biomass and deeper roots promote carbon stabilization was rejected. The amount of root biomass that will be stabilized in the soil on the long term is, however, unknown.
Stephen J. Harris, Jesper Liisberg, Longlong Xia, Jing Wei, Kerstin Zeyer, Longfei Yu, Matti Barthel, Benjamin Wolf, Bryce F. J. Kelly, Dioni I. Cendón, Thomas Blunier, Johan Six, and Joachim Mohn
Atmos. Meas. Tech., 13, 2797–2831, https://doi.org/10.5194/amt-13-2797-2020, https://doi.org/10.5194/amt-13-2797-2020, 2020
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The latest commercial laser spectrometers have the potential to revolutionize N2O isotope analysis. However, to do so, they must be able to produce trustworthy data. Here, we test the performance of widely used laser spectrometers for ambient air applications and identify instrument-specific dependencies on gas matrix and trace gas concentrations. We then provide a calibration workflow to facilitate the operation of these instruments in order to generate reproducible and accurate data.
Moritz Laub, Michael Scott Demyan, Yvonne Funkuin Nkwain, Sergey Blagodatsky, Thomas Kätterer, Hans-Peter Piepho, and Georg Cadisch
Biogeosciences, 17, 1393–1413, https://doi.org/10.5194/bg-17-1393-2020, https://doi.org/10.5194/bg-17-1393-2020, 2020
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Loss of soil carbon to the atmosphere represents a global challenge. We tested an innovative way to reduce the high uncertainty related to turnover of carbon stored in soils. With the use of infrared spectra of soils from model bare fallow systems, we were able to better assess the current state of soil carbon and predict its behavior in overdecadal time spans. In agreement with recent studies, carbon turnover seems faster than earlier assumed, with potential for high loss under mismanagement.
Karl Voglmeier, Johan Six, Markus Jocher, and Christof Ammann
Biogeosciences, 16, 1685–1703, https://doi.org/10.5194/bg-16-1685-2019, https://doi.org/10.5194/bg-16-1685-2019, 2019
Tino Colombi, Florian Walder, Lucie Büchi, Marlies Sommer, Kexing Liu, Johan Six, Marcel G. A. van der Heijden, Raphaël Charles, and Thomas Keller
SOIL, 5, 91–105, https://doi.org/10.5194/soil-5-91-2019, https://doi.org/10.5194/soil-5-91-2019, 2019
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The role of soil aeration in carbon sequestration in arable soils has only been explored little, especially at the farm level. The current study, which was conducted on 30 fields that belong to individual farms, reveals a positive relationship between soil gas transport capability and soil organic carbon content. We therefore conclude that soil aeration needs to be accounted for when developing strategies for carbon sequestration in arable soil.
Elizabeth Verhoeven, Matti Barthel, Longfei Yu, Luisella Celi, Daniel Said-Pullicino, Steven Sleutel, Dominika Lewicka-Szczebak, Johan Six, and Charlotte Decock
Biogeosciences, 16, 383–408, https://doi.org/10.5194/bg-16-383-2019, https://doi.org/10.5194/bg-16-383-2019, 2019
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This study utilized state-of-the-art measurements of nitrogen isotopes to evaluate nitrogen cycling and to assess the biological sources of the potent greenhouse gas, N2O, in response to water-saving practices in rice systems. Water-saving practices did emit more N2O, and high N2O production had a lower 15N isotope signature. Modeling and visual interpretation indicate that these emissions mostly came from denitrification or nitrifier denitrification, controlled upstream by nitrification rates.
Johanna I. F. Slaets, Hans-Peter Piepho, Petra Schmitter, Thomas Hilger, and Georg Cadisch
Hydrol. Earth Syst. Sci., 21, 571–588, https://doi.org/10.5194/hess-21-571-2017, https://doi.org/10.5194/hess-21-571-2017, 2017
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Determining measures of uncertainty on loads is not trivial, as a load is a product of concentration and discharge per time point, summed up over time. A bootstrap approach enables the calculation of confidence intervals on constituent loads. Ignoring the uncertainty on the discharge will typically underestimate the width of 95 % confidence intervals by around 10 %. Furthermore, confidence intervals are asymmetric, with the largest uncertainty on the upper limit.
Marijn Van de Broek, Stijn Temmerman, Roel Merckx, and Gerard Govers
Biogeosciences, 13, 6611–6624, https://doi.org/10.5194/bg-13-6611-2016, https://doi.org/10.5194/bg-13-6611-2016, 2016
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The results of this study on the organic carbon (OC) stocks of tidal marshes show that variations in OC stocks along estuaries are important and should be taken into account to make accurate estimates of the total amount of OC stored in these ecosystems. Moreover, our results clearly show that most studies underestimate the variation in OC stocks along estuaries due to a shallow sampling depth, neglecting the variation in OC decomposition after burial along estuaries.
Johanna I. F. Slaets, Petra Schmitter, Thomas Hilger, Tran Duc Vien, and Georg Cadisch
Biogeosciences, 13, 3267–3281, https://doi.org/10.5194/bg-13-3267-2016, https://doi.org/10.5194/bg-13-3267-2016, 2016
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Maize production on steep slopes causes erosion. Where the eroded material ends up is not well understood. This study assessed transport of sediment in mountainous Vietnam, where maize is cultivated on slopes and rice is cultivated in valleys. Per year, 64 tons per hectare of sediments are brought into the rice fields and 28 tons of those are deposited there. The sediment fraction captured by the paddies is mostly sandy, while fertile silt and clay are exported. Upland erosion thus impacts rice production.
R. Hüppi, R. Felber, A. Neftel, J. Six, and J. Leifeld
SOIL, 1, 707–717, https://doi.org/10.5194/soil-1-707-2015, https://doi.org/10.5194/soil-1-707-2015, 2015
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Biochar is considered an opportunity to tackle major environmental issues in agriculture. Adding pyrolised organic residues to soil may sequester carbon, increase yields and reduce nitrous oxide emissions from soil. It is unknown, whether the latter is induced by changes in soil pH. We show that biochar application substantially reduces nitrous oxide emissions from a temperate maize cropping system. However, the reduction was only achieved with biochar but not with liming.
C. Decock, J. Lee, M. Necpalova, E. I. P. Pereira, D. M. Tendall, and J. Six
SOIL, 1, 687–694, https://doi.org/10.5194/soil-1-687-2015, https://doi.org/10.5194/soil-1-687-2015, 2015
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Further progress in understanding and mitigating N2O emissions from soil lies within transdisciplinary research that reaches across spatial scales and takes an ambitious look into the future.
M. S. Torn, A. Chabbi, P. Crill, P. J. Hanson, I. A. Janssens, Y. Luo, C. H. Pries, C. Rumpel, M. W. I. Schmidt, J. Six, M. Schrumpf, and B. Zhu
SOIL, 1, 575–582, https://doi.org/10.5194/soil-1-575-2015, https://doi.org/10.5194/soil-1-575-2015, 2015
B. Wolf, L. Merbold, C. Decock, B. Tuzson, E. Harris, J. Six, L. Emmenegger, and J. Mohn
Biogeosciences, 12, 2517–2531, https://doi.org/10.5194/bg-12-2517-2015, https://doi.org/10.5194/bg-12-2517-2015, 2015
S. Doetterl, J.-T. Cornelis, J. Six, S. Bodé, S. Opfergelt, P. Boeckx, and K. Van Oost
Biogeosciences, 12, 1357–1371, https://doi.org/10.5194/bg-12-1357-2015, https://doi.org/10.5194/bg-12-1357-2015, 2015
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We link the mineralogy of soils affected by erosion and deposition to the distribution of soil carbon fractions, their turnover and microbial activity. We show that the weathering status of soils and their history are controlling the stabilization of carbon with minerals. After burial, aggregated C is preserved more efficiently while non-aggregated C can be released and younger C re-sequestered more easily. Weathering changes the effectiveness of stabilization mechanism limiting this C sink.
E. C. Brevik, A. Cerdà, J. Mataix-Solera, L. Pereg, J. N. Quinton, J. Six, and K. Van Oost
SOIL, 1, 117–129, https://doi.org/10.5194/soil-1-117-2015, https://doi.org/10.5194/soil-1-117-2015, 2015
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This paper provides a brief accounting of some of the many ways that the study of soils can be interdisciplinary, therefore giving examples of the types of papers we hope to see submitted to SOIL.
M. S. Demyan, F. Rasche, M. Schütt, N. Smirnova, E. Schulz, and G. Cadisch
Biogeosciences, 10, 2897–2913, https://doi.org/10.5194/bg-10-2897-2013, https://doi.org/10.5194/bg-10-2897-2013, 2013
Related subject area
Biogeosciences
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
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
Quantifying the role of ozone-caused damage to vegetation in the Earth system: A new parameterization scheme for photosynthetic and stomatal responses
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
Exploring the Potential of History Matching for Land Surface Model Calibration
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
Using Deep Learning to integrate paleoclimate and global biogeochemistry over Phanerozoic time
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
EAT v0.9.6: a 1D testbed for physical-biogeochemical data assimilation in natural waters
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
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Assimilation of Carbonyl Sulfide (COS) fluxes within the adjoint-based data assimilation system–Nanjing University Carbon Assimilation System (NUCAS v1.0)
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
Modeling boreal forest’s mineral soil and peat C stock dynamics with Yasso07 model coupled with updated moisture modifier
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)
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.
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.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-6, https://doi.org/10.5194/gmd-2024-6, 2024
Revised manuscript accepted for GMD
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This study introduces a new scheme to simulate 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 response 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.
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.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2996, https://doi.org/10.5194/egusphere-2023-2996, 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. Here we test a technique called “History matching” against more common approaches. This method adapts well to these models, helping better understand how they work and therefore how to make them more realistic.
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.
Dongyu Zheng, Andrew Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-230, https://doi.org/10.5194/gmd-2023-230, 2024
Revised manuscript accepted for GMD
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This study uses a deep learning method to enhance the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model for more accurate predictions of climate shifts. The method may be critical in developing new fully-continuous methods that are able to translate over a moving continental surface in deep time with high-resolution at a reasonable computational expense.
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.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-242, https://doi.org/10.5194/gmd-2023-242, 2024
Revised manuscript accepted for GMD
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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 as 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.
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.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-238, https://doi.org/10.5194/gmd-2023-238, 2023
Revised manuscript accepted for GMD
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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. Here, we present EAT, a flexible and efficient testbed that allows any scientist to explore and further develop the state-of-the-art in data assimilation.
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.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
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Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
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The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
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We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
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Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
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We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
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Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
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In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
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Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1955, https://doi.org/10.5194/egusphere-2023-1955, 2023
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In this work, Nanjing University Carbon Assimilation System (NUCAS) was developed. Data assimilation experiments were conducted to demonstrate the robustness and to investigate the feasibility and applicability of NUCAS. The assimilation of COS significantly improved the model performance in gross primary productivity, sensible heat, latent heat and even soil moisture, demonstrating that COS can provide strong constraints on parameters relevant to water, energy and carbon processes.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
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This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
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Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Stefano Manzoni, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
EGUsphere, https://doi.org/10.5194/egusphere-2023-1523, https://doi.org/10.5194/egusphere-2023-1523, 2023
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Improving representation of peatlands in Earth system models (ESMs) (e.g., in Yasso soil C model coupled with JSBACH model) is rare. We updated Yasso07 moisture dependency for applications on both the mineral soils and peatlands of boreal forest. Our moisture function improved the simulated peatland C stocks and CO2 dynamics. However, due to nature of the measurements used for Bayesian MCMC data assimilation, it contrasts with functions in other ESMs (see graphical abstract).
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
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Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
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Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
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We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
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Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
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Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
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Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
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Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
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Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
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Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
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In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
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There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
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Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
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Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
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Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022, https://doi.org/10.5194/gmd-15-8153-2022, 2022
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We develop a demographic vegetation model to improve the representation of terrestrial vegetation dynamics and ecosystem biogeochemical cycles in the Goddard Institute for Space Studies ModelE. The individual-based competition for light and soil resources makes the modeling of eco-evolutionary optimality possible. This model will enable ModelE to simulate long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems at decadal to centurial temporal scales.
Cited articles
Abiven, S., Menasseri, S., Angers, D. A., and Leterme, P.: A Model to Predict Soil Aggregate Stability Dynamics following Organic Residue Incorporation under Field Conditions, Soil Sci. Soc. Am. J., 72, 119–125, https://doi.org/10.2136/sssaj2006.0018, 2008. a
Abramoff, R., Xu, X., Hartman, M., O’Brien, S., Feng, W., Davidson, E., Finzi, A., Moorhead, D., Schimel, J., Torn, M., and Mayes, M. A.: The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century, Biogeochemistry, 137, 51–71, https://doi.org/10.1007/s10533-017-0409-7, 2018. a, b, c, d
Abramoff, R. Z., Guenet, B., Zhang, H., Georgiou, K., Xu, X., Viscarra Rossel, R. A., Yuan, W., and Ciais, P.: Improved global-scale predictions of soil carbon stocks with Millennial Version 2, Soil Biol. Biochem., 164, 108466, https://doi.org/10.1016/j.soilbio.2021.108466, 2022. a, b, c, d, e, f, g, h, i
Ahrens, B., Reichstein, M., Borken, W., Muhr, J., Trumbore, S. E., and Wutzler, T.: Bayesian calibration of a soil organic carbon model using Δ14C measurements of soil organic carbon and heterotrophic respiration as joint constraints, Biogeosciences, 11, 2147–2168, https://doi.org/10.5194/bg-11-2147-2014, 2014. a
Anderson, J. M. and Ingram, J. S. I.: Tropical Soil Biology and Fertility: A Handbook of Methods., CAB international, Wallingford, 2nd edn., ISBN 0-85198-821-0, https://doi.org/10.2307/2261129, 1993. a, b
Angst, G., Mueller, K. E., Nierop, K. G. J., and Simpson, M. J.: Plant- or microbial-derived? A review on the molecular composition of stabilized soil organic matter, Soil Biol. Biochem., 156, 108189, https://doi.org/10.1016/j.soilbio.2021.108189, 2021. a, b, c
Bettermann, A., Zethof, J. H. T., Babin, D., Cammeraat, E. L. H., Solé-Benet, A., Lázaro, R., Luna, L., Nesme, J., Sørensen, S. J., Kalbitz, K., Smalla, K., and Vogel, C.: Importance of microbial communities at the root-soil interface for extracellular polymeric substances and soil aggregation in semiarid grasslands, Soil Biol. Biochem., 159, 108301, https://doi.org/10.1016/j.soilbio.2021.108301, 2021. a
Blagodatsky, S. A. and Richter, O.: Microbial growth in soil and nitrogen turnover: a theoretical model considering the activity state of microorganisms, Soil Biol. Biochem., 30, 1743–1755, https://doi.org/10.1016/S0038-0717(98)00028-5, 1998. a
Bossuyt, H., Denef, K., Six, J., Frey, S. D., Merckx, R., and Paustian, K.: Influence of microbial populations and residue quality on aggregate stability, Appl. Soil Ecol., 16, 195–208, https://doi.org/10.1016/S0929-1393(00)00116-5, 2001. a
Bucka, F. B., Kölbl, A., Uteau, D., Peth, S., and Kögel-Knabner, I.: Organic matter input determines structure development and aggregate formation in artificial soils, Geoderma, 354, 113881–113881, https://doi.org/10.1016/j.geoderma.2019.113881, 2019. a
Bucka, F. B., Felde, V. J. M. N. L., Peth, S., and Kögel-Knabner, I.: Disentangling the effects of OM quality and soil texture on microbially mediated structure formation in artificial model soils, Geoderma, 403, 115213, https://doi.org/10.1016/j.geoderma.2021.115213, 2021. a, b
Campbell, E. E., Parton, W. J., Soong, J. L., Paustian, K., Hobbs, N. T., and Cotrufo, M. F.: Using litter chemistry controls on microbial processes to partition litter carbon fluxes with the Litter Decomposition and Leaching (LIDEL) model, Soil Biol. Biochem., 100, 160–174, https://doi.org/10.1016/j.soilbio.2016.06.007, 2016. a, b, c
Castellano, M. J., Mueller, K. E., Olk, D. C., Sawyer, J. E., and Six, J.: Integrating plant litter quality, soil organic matter stabilization, and the carbon saturation concept, Global Change Biol., 21, 3200–3209, https://doi.org/10.1111/gcb.12982, 2015. a
Christensen, B. T.: Physical fractionation of soil and structural and functional complexity in organic matter turnover, Eur. J. Soil Sci., 52, 345–353, https://doi.org/10.1046/j.1365-2389.2001.00417.x, 2001. a
Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K., and Paul, E.: The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter?, Global Change Biol., 19, 988–995, https://doi.org/10.1111/gcb.12113, 2013. a, b, c
Crouzet, O., Consentino, L., Pétraud, J.-P., Marrauld, C., Aguer, J.-P., Bureau, S., Le Bourvellec, C., Touloumet, L., and Bérard, A.: Soil Photosynthetic Microbial Communities Mediate Aggregate Stability: Influence of Cropping Systems and Herbicide Use in an Agricultural Soil, Front. Microbiol., 10, 1319, https://doi.org/10.3389/fmicb.2019.01319, 2019. a
de Aguiar, T. C., de Oliveira Torchia, D. F., van Tol de Castro, T. A., Tavares, O. C. H., de Abreu Lopes, S., de Souza da Silva, L., Castro, R. N., Berbara, R. L. L., Pereira, M. G., and García, A. C.: Spectroscopic–chemometric modeling of 80 humic acids confirms the structural pattern identity of humified organic matter despite different formation environments, Sci. Total Environ., 833, 155133, https://doi.org/10.1016/j.scitotenv.2022.155133, 2022. a
Denef, K., Six, J., Bossuyt, H., Frey, S. D., Elliott, E. T., Merckx, R., and Paustian, K.: Influence of dry–wet cycles on the interrelationship between aggregate, particulate organic matter, and microbial community dynamics, Soil Biol. Biochem., 33, 1599–1611, https://doi.org/10.1016/S0038-0717(01)00076-1, 2001. a
Dijkstra, P., Martinez, A., Thomas, S. C., Seymour, C. O., Wu, W., Dippold, M. A., Megonigal, J. P., Schwartz, E., and Hungate, B. A.: On maintenance and metabolisms in soil microbial communities, Plant Soil, 476, 385–396, https://doi.org/10.1007/s11104-022-05382-9, 2022. a
Gargulak, J. D., Lebo, S. E., and McNally, T. J.: Lignin, in: Kirk-Othmer Encyclopedia of Chemical Technology, 1–26, John Wiley & Sons, Ltd, ISBN 978-0-471-23896-6, https://doi.org/10.1002/0471238961.12090714120914.a01.pub3, 2015. a
Gauch, H. G., Hwang, J. T. G., and Fick, G. W.: Model Evaluation by Comparison of Model-Based Predictions and Measured Values, Agronomy J., 95, 1442–1442, https://doi.org/10.2134/agronj2003.1442, 2003. a, b
Georgiou, K., Jackson, R. B., Vindušková, O., Abramoff, R. Z., Ahlström, A., Feng, W., Harden, J. W., Pellegrini, A. F. A., Polley, H. W., Soong, J. L., Riley, W. J., and Torn, M. S.: Global stocks and capacity of mineral-associated soil organic carbon, Nat. Commun., 13, 3797, https://doi.org/10.1038/s41467-022-31540-9, 2022. a
Gurung, R. B., Ogle, S. M., Breidt, F. J., Williams, S. A., and Parton, W. J.: Bayesian calibration of the DayCent ecosystem model to simulate soil organic carbon dynamics and reduce model uncertainty, Geoderma, 376, 114529, https://doi.org/10.1016/j.geoderma.2020.114529, 2020. a
Kallenbach, C. M., Frey, S. D., and Grandy, A. S.: Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls, Nat. Commun., 7, 1–10, https://doi.org/10.1038/ncomms13630, 2016. a, b
Kamolmanit, B., Vityakon, P., Kaewpradit, W., Cadisch, G., and Rasche, F.: Soil fungal communities and enzyme activities in a sandy, highly weathered tropical soil treated with biochemically contrasting organic inputs, Biol. Fert. Soils, 49, 905–917, https://doi.org/10.1007/s00374-013-0785-7, 2013. a
Kandeler, E., Tscherko, D., and Spiegel, H.: Long-term monitoring of microbial biomass, N mineralisation and enzyme activities of a Chernozem under different tillage management, Biol. Fert. Soils, 28, 343–351, https://doi.org/10.1007/s003740050502, 1999. a
Kögel-Knabner, I., Guggenberger, G., Kleber, M., Kandeler, E., Kalbitz, K., Scheu, S., Eusterhues, K., and Leinweber, P.: Organo-mineral associations in temperate soils: Integrating biology, mineralogy, and organic matter chemistry, J. Plant Nutr. Soil Sci., 171, 61–82, https://doi.org/10.1002/jpln.200700048, 2008. a
Kopittke, P. M., Hernandez-Soriano, M. C., Dalal, R. C., Finn, D., Menzies, N. W., Hoeschen, C., and Mueller, C. W.: Nitrogen-rich microbial products provide new organo-mineral associations for the stabilization of soil organic matter, Global Change Biol., 24, 1762–1770, https://doi.org/10.1111/gcb.14009, 2018. a
Kopittke, P. M., Dalal, R. C., Hoeschen, C., Li, C., Menzies, N. W., and Mueller, C. W.: Soil organic matter is stabilized by organo-mineral associations through two key processes: The role of the carbon to nitrogen ratio, Geoderma, 357, 113974–113974, https://doi.org/10.1016/j.geoderma.2019.113974, 2020. a
Kpemoua, T. P. I., Barré, P., Chevallier, T., Houot, S., and Chenu, C.: Drivers of the amount of organic carbon protected inside soil aggregates estimated by crushing: A meta-analysis, Geoderma, 427, 116089, https://doi.org/10.1016/j.geoderma.2022.116089, 2022. a
Krause, L., Biesgen, D., Treder, A., Schweizer, S. A., Klumpp, E., Knief, C., and Siebers, N.: Initial microaggregate formation: Association of microorganisms to montmorillonite-goethite aggregates under wetting and drying cycles, Geoderma, 351, 250–260, https://doi.org/10.1016/j.geoderma.2019.05.001, 2019. a
Laub, M.: Author Comment 1, https://doi.org/10.5194/egusphere-2023-1414-AC1, 2023a. a
Laub, M.: mol4ub/SAMM_model: SAMM model v1.0 including data used in the calibration and evaluation process. (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.8086828, 2023b. a
Laub, M., Demyan, M. S., Nkwain, Y. F., Blagodatsky, S., Kätterer, T., Piepho, H.-P., and Cadisch, G.: DRIFTS band areas as measured pool size proxy to reduce parameter uncertainty in soil organic matter models, Biogeosciences, 17, 1393–1413, https://doi.org/10.5194/bg-17-1393-2020, 2020. a
Lavallee, J. M., Conant, R. T., Paul, E. A., and Cotrufo, M. F.: Incorporation of shoot versus root-derived 13C and 15N into mineral-associated organic matter fractions: results of a soil slurry incubation with dual-labelled plant material, Biogeochemistry, 137, 379–393, https://doi.org/10.1007/s10533-018-0428-z, 2018. a
Lavallee, J. M., Soong, J. L., and Cotrufo, M. F.: Conceptualizing soil organic matter into particulate and mineral-associated forms to address global change in the 21st century, Global Change Biol., 26, 261–273, https://doi.org/10.1111/gcb.14859, 2020. a, b
Loague, K. and Green, R. E.: Statistical and graphical methods for evaluating solute transport models: Overview and application, J. Contam. Hydrol., 7, 51–73, https://doi.org/10.1016/0169-7722(91)90038-3, 1991. a
Luo, Z., Baldock, J., and Wang, E.: Modelling the dynamic physical protection of soil organic carbon: Insights into carbon predictions and explanation of the priming effect, Global Change Biol., 23, 5273–5283, https://doi.org/10.1111/gcb.13793, 2017. a, b
Manzoni, S., Taylor, P., Richter, A., Porporato, A., and Ågren, G. I.: Environmental and stoichiometric controls on microbial carbon-use efficiency in soils, New Phytologist, 196, 79–91, https://doi.org/10.1111/j.1469-8137.2012.04225.x, 2012. a, b
Marschmann, G. L., Pagel, H., Kügler, P., and Streck, T.: Equifinality, sloppiness, and emergent structures of mechanistic soil biogeochemical models, Environ. Model. Softw., 122, 104518, https://doi.org/10.1016/j.envsoft.2019.104518, 2019. a
Mueller, T., Jensen, L. S. S., Magid, J., and Nielsen, N. E. E.: Temporal variation of C and N turnover in soil after oilseed rape straw incorporation in the field: simulations with the soil-plant-atmosphere model DAISY, Ecol. Model., 99, 247–262, https://doi.org/10.1016/S0304-3800(97)01959-5, 1997. a
Necpálová, M., Anex, R. P., Fienen, M. N., Del Grosso, S. J., Castellano, M. J., Sawyer, J. E., Iqbal, J., Pantoja, J. L., and Barker, D. W.: Understanding the DayCent model: Calibration, sensitivity, and identifiability through inverse modeling, Environ. Model. Softw., 66, 110–130, https://doi.org/10.1016/j.envsoft.2014.12.011, 2015. a, b
Oldfield, E. E., Crowther, T. W., and Bradford, M. A.: Substrate identity and amount overwhelm temperature effects on soil carbon formation, Soil Biol. Biochem., 124, 218–226, https://doi.org/10.1016/j.soilbio.2018.06.014, 2018. a
Puttaso, A., Vityakon, P., Saenjan, P., Trelo-ges, V., and Cadisch, G.: Relationship between residue quality, decomposition patterns, and soil organic matter accumulation in a tropical sandy soil after 13 years, Nutr. Cycl. Agroecosyst., 89, 159–174, https://doi.org/10.1007/s10705-010-9385-1, 2011. a, b, c, d, e, f
Puttaso, A., Vityakon, P., Rasche, F., Saenjan, P., Treloges, V., and Cadisch, G.: Does Organic Residue Quality Influence Carbon Retention in a Tropical Sandy Soil?, Soil Sci. Soc. Am. J., 77, 1001–1001, https://doi.org/10.2136/sssaj2012.0209, 2013. a, b, c
Schrumpf, M., Kaiser, K., Guggenberger, G., Persson, T., Kögel-Knabner, I., and Schulze, E.-D.: Storage and stability of organic carbon in soils as related to depth, occlusion within aggregates, and attachment to minerals, Biogeosciences, 10, 1675–1691, https://doi.org/10.5194/bg-10-1675-2013, 2013. a
Scrucca, L.: GA: A Package for Genetic Algorithms in R, J. Stat. Softw., 53, 1–37, https://doi.org/10.18637/jss.v053.i04, 2013. a
Šimůnek, J., van Genuchten, M. T., and Šejna, M.: The HYDRUS-1D Software Package for Simulating the Movement of Water, Heat, and Multiple Solutes in Variably Saturated Media, Version 3.0, HYDRUS Software Series 1, Department of Environmental Sciences, University of California Riverside, Riverside, California, USA, https://www.ars.usda.gov/ARSUserFiles/20360500/software/97/HYDRUS1D_3.pdf (last access: 31 January 2024), 2005. a, b
Sinsabaugh, R. L., Turner, B. L., Talbot, J. M., Waring, B. G., Powers, J. S., Kuske, C. R., Moorhead, D. L., and Follstad Shah, J. J.: Stoichiometry of microbial carbon use efficiency in soils, Ecol. Monogr., 86, 172–189, https://doi.org/10.1890/15-2110.1, 2016. a
Six, J. and Paustian, K.: Aggregate-associated soil organic matter as an ecosystem property and a measurement tool, Soil Biol. Biochem., 68, A4–A9, https://doi.org/10.1016/j.soilbio.2013.06.014, 2014. a
Six, J., Elliott, E., and Paustian, K.: Soil macroaggregate turnover and microaggregate formation: a mechanism for C sequestration under no-tillage agriculture, Soil Biol. Biochem., 32, 2099–2103, https://doi.org/10.1016/S0038-0717(00)00179-6, 2000. a
Six, J., Feller, C., Denef, K., Ogle, S. M., Sa, J. C. d. M., and Albrecht, A.: Soil organic matter, biota and aggregation in temperate and tropical soils - Effects of no-tillage, Agronomie, 22, 755–775, https://doi.org/10.1051/agro:2002043, 2002. a, b
Six, J., Frey, S. D., Thiet, R. K., and Batten, K. M.: Bacterial and Fungal Contributions to Carbon Sequestration in Agroecosystems, Soil Sci. Soc. Am. J., 70, 555–569, https://doi.org/10.2136/sssaj2004.0347, 2006. a
Soetaert, K., Petzoldt, T., and Setzer, R. W.: Solving Differential Equations in R: Package deSolve, J. Stat. Softw., 33, 1–25, https://doi.org/10.18637/jss.v033.i09, 2010. a
Tang, J. and Riley, W. J.: Weaker soil carbon–climate feedbacks resulting from microbial and abiotic interactions, Nat. Clim. Change, 5, 56–60, https://doi.org/10.1038/nclimate2438, 2015. a
Tang, J. and Riley, W. J.: Competitor and substrate sizes and diffusion together define enzymatic depolymerization and microbial substrate uptake rates, Soil Biol. Biochem., 139, 107624, https://doi.org/10.1016/j.soilbio.2019.107624, 2019. a
Totsche, K. U., Amelung, W., Gerzabek, M. H., Guggenberger, G., Klumpp, E., Knief, C., Lehndorff, E., Mikutta, R., Peth, S., Prechtel, A., Ray, N., and Kögel-Knabner, I.: Microaggregates in soils, J. Plant Nutr. Soil Sci., 181, 104–136, https://doi.org/10.1002/jpln.201600451, 2018. a
Vance, E., Brookes, P., and Jenkinson, D.: An extraction method for measuring soil microbial biomass C, Soil Biol. Biochem., 19, 703–707, https://doi.org/10.1016/0038-0717(87)90052-6, 1987. a
Van Soest, P. J. and Wine, R. H.: Determination of Lignin and Cellulose in Acid-Detergent Fiber with Permanganate, J. AOAC Int., 51, 780–785, https://doi.org/10.1093/jaoac/51.4.780, 1968. a, b
Vityakon, P.: Degradation and restoration of sandy soils under different agricultural land uses in northeast Thailand: A review, Land Degrad. Develop., 18, 567–577, https://doi.org/10.1002/ldr.798, 2007. a, b
Vityakon, P., Meepech, S., Cadisch, G., and Toomsan, B.: Soil organic matter and nitrogen transformation mediated by plant residues of different qualities in sandy acid upland and paddy soils, NJAS – Wageningen Journal of Life Sciences, 48, 75–90, https://doi.org/10.1016/S1573-5214(00)80006-8, 2000. a, b, c, d, e
Walkley, A. and Black, I. A.: An examination of the degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method, Soil Sci., 37, 29–38, https://doi.org/10.1097/00010694-193401000-00003, 1934. a
Wallach, D., Makowski, D., Jones, J. W., and Brun, F.: Chapter 8 - Parameter Estimation With Bayesian Methods, in: Working with Dynamic Crop Models (Third Edition), edited by: Wallach, D., Makowski, D., Jones, J. W., and Brun, F., 275–309, Academic Press, ISBN 978-0-12-811756-9, https://doi.org/10.1016/B978-0-12-811756-9.00008-3, 2019. a
Wang, G., Post, W. M., and Mayes, M. A.: Development of microbial-enzyme-mediated decomposition model parameters through steady-state and dynamic analyses, Ecol. Appl., 23, 255–272, https://doi.org/10.1890/12-0681.1, 2013. a, b, c, d
Wang, G., Jagadamma, S., Mayes, M. A., Schadt, C. W., Megan Steinweg, J., Gu, L., and Post, W. M.: Microbial dormancy improves development and experimental validation of ecosystem model, The ISME J., 9, 226–237, https://doi.org/10.1038/ismej.2014.120, 2015. a, b
Wang, S., Redmile-Gordon, M., Shahbaz, M., Ge, T., Zhang, M., Wu, Y., Liu, J., Huang, Q., and Cai, P.: Microbial formation and stabilisation of soil organic carbon is regulated by carbon substrate identity and mineral composition, Geoderma, 414, 115762, https://doi.org/10.1016/j.geoderma.2022.115762, 2022. a, b, c
Wieder, W. R., Grandy, A. S., Kallenbach, C. M., and Bonan, G. B.: Integrating microbial physiology and physio-chemical principles in soils with the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, Biogeosciences, 11, 3899–3917, https://doi.org/10.5194/bg-11-3899-2014, 2014. a
Yudina, A. and Kuzyakov, Y.: Saving the face of soil aggregates, Global Change Biology, 25, 3574–3577, https://doi.org/10.1111/gcb.14779, 2019. a
Zech, S., Schweizer, S. A., Bucka, F. B., Ray, N., Kögel-Knabner, I., and Prechtel, A.: Explicit spatial modeling at the pore scale unravels the interplay of soil organic carbon storage and structure dynamics, Global Change Biol., 28, 4589–4604, https://doi.org/10.1111/gcb.16230, 2022. a
Zhang, Y., Lavallee, J. M., Robertson, A. D., Even, R., Ogle, S. M., Paustian, K., and Cotrufo, M. F.: Simulating measurable ecosystem carbon and nitrogen dynamics with the mechanistically defined MEMS 2.0 model, Biogeosciences, 18, 3147–3171, https://doi.org/10.5194/bg-18-3147-2021, 2021. a
Short summary
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.
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that...
