Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-931-2024
https://doi.org/10.5194/gmd-17-931-2024
Model description paper
 | 
05 Feb 2024
Model description paper |  | 05 Feb 2024

SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation

Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch

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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
Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., and Walter, P.: Molecular Biology of the Cell, Garland Science, 4th edn., ISBN 978-0-8153-3218-3 978-0-8153-4072-0, 2002. a, b
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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.