27 Jul 2023
 | 27 Jul 2023
Status: this preprint is open for discussion.

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

Abstract. In light of the large role that soil organic matter (SOM) plays in maintaining healthy and productive agricultural soils, it is crucial to understand the processes of SOM protection including the role of soil aggregate protection. Yet, few numerical process models include aggregate formation and even fewer represent the important connection between microbial growth and aggregate formation. Here, we propose a model of Soil Aggregation through Microbial Mediation (SAMM), which consist of measurable pools and 5 couples soil aggregate formation to microbial growth. The model was evaluated against data from a long term bare-fallow experiment in a tropical sandy soil, subject to plant litter additions of different compositions. The SAMM model effectively represented the microbial growth response after litter addition and the following formation and later disruption of aggregates. Model parameter correlation was low (all r < 0.5; r > 0.4 for only 4 of 22 parameters) showing that SAMM is well parameterized. Differences between treatments resulting from different litter compositions could be captured by SAMM for soil organic carbon (Nash-Sutcliffe modelling efficiency (EF) of 0.68), microbial nitrogen (EF of 0.24) and litter carbon (EF of 0.80). Aggregate-related fractions, i.e., carbon inside aggregates (EF of 0.60) and also carbon in the free silt and clay fraction (EF of 0.24) were simulated very well to satisfactory. Analysis of model parameters led to further noteworthy insights. For example, model results suggested that up to 50 % of carbon in the soil is stabilized through aggregate protection, even in a sandy soil, and that both microbial activity and physical aggregate formation coexist. When aggregate formation was deactivated, the model failed to stabilize soil organic carbon (EF dropped to -3.68) and microbial nitrogen was represented less well (EF of 0.13). By re-calibrating the model version with deactivated aggregates, it was possible to partly correct for removing the aggregate formation, i.e., by reducing the decomposition rate of mineral attached carbon by about 85 % (EF of 0.68, 0.75 and 0.18 for SOC, litter carbon and microbial nitrogen, respectively). Yet, the overall slightly better evaluation statistics (e.g., Akaike information critereon of 5351 vs 5554) show the potential importance of representing aggregate dynamics within SOM models. Our results indicate that current models without aggregate formation partly compensate the missing protection effect by lowering turnover rates of other pools and thus may still be suitable options where data on aggregate associated carbon is not available.

Moritz Laub et al.

Status: open (until 21 Oct 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Moritz Laub et al.

Data sets

mol4ub/SAMM_model: SAMM model v1.0 including data used in the calibration and evaluation process. Patma Vityakon, Benjapon Kunlanit, Georg Cadisch, Moritz Laub, Samuel Schlichenmaier

Model code and software

mol4ub/SAMM_model: SAMM model v1.0 including data used in the calibration and evaluation process. Moritz Laub

Moritz Laub et al.


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Short summary
To manage soil organic matter sustainably, we need to better understand the role that soil microbes play in aggregate protection. Here, we propose a 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.