- 1Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences IBG-3: Agrosphere, Germany
- 2University of Bonn, Institute of Crop Science and Resource Conservation, Germany
- 3University of Hohenheim, Institute of Soil Science and Land Evaluation, Department of Biogeophysics, Germany
- 4University of Hohenheim, Institute of Soil Science and Land Evaluation, Department of Soil Biology, Germany
Understanding the feedback mechanisms between roots and soil, and their effects on microbial communities, is crucial for predicting carbon cycling processes in agroecosystems. We developed a onedimensional axisymmetric rhizosphere model to simulate the spatially resolved dynamics of microorganisms and soil organic matter turnover around a single root segment to explore soil-root interactions. The model accounts for two functional microbial groups with different life history strategies (copiotrophs and oligotrophs), reflecting trade-offs in functional microbial traits related to substrate utilization and microbial metabolism. The model also considers substrates of different accessibility of soil organic matter, i.e. low and high molecular weight organic carbon compounds (LMW-OC, HMW-OC). The model was conditioned using Bayesian inference with constraint-based parameter sampling, which enabled the identification of parameter sets resulting in plausible model predictions in agreement with experimental evidence. Mimicking the behavior of growing roots, the model assumed 15 days of rhizodeposition for LMW-OC. As expected, the simulations show a decreasing concentration of dissolved LMW-OC away from the root surface. After 15 days, the microbial community close to the root surface (0–0.1 mm) was dominated by copiotrophs. The spatial patterns of functional microbial groups persisted after rhizodeposition ended, indicating a legacy effect of rhizodeposition on microbial communities, particularly on oligotrophic activity. Simulated microbial biomass exhibits a very rapid change within 0–0.2 mm away from the root surface, which points to the importance of resolving soil properties and states at submillimeter resolution. Microbial-explicit rhizosphere modeling thus facilitates elucidating spatiotemporal patterns of microorganisms and carbon turnover in the rhizosphere.
How to cite: Pagel, H., Sırcan, A. K., Schnepf, A., Giraud, M., Lattacher, A., Kandeler, E., Poll, C., and Streck, T.: Trait-based modeling of microbial interactions and carbon turnover in the rhizosphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16819, https://doi.org/10.5194/egusphere-egu25-16819, 2025.