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Patterns in soil organic carbon dynamics: Integrating microbial activity, chemotaxis and data-driven approaches

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  • Monti, Angela
  • Diele, Fasma
  • Lacitignola, Deborah
  • Marangi, Carmela

Abstract

Models of soil organic carbon (SOC) frequently overlook the effects of spatial dimensions and microbiological activities. In this paper, we focus on two reaction–diffusion chemotaxis models for SOC dynamics, both supporting chemotaxis-driven instability and exhibiting a variety of spatial patterns as stripes, spots and hexagons when the microbial chemotactic sensitivity is above a critical threshold. We use symplectic techniques to numerically approximate chemotaxis-driven spatial patterns and explore the effectiveness of the piecewise Dynamic Mode Decomposition (pDMD) to reconstruct them. Moreover, we analyse the predictive performance of the pDMD for moderate time horizons. Our findings show that pDMD is effective at precisely recreating and predicting chemotaxis-driven spatial patterns, therefore broadening the range of application of the method to classes of solutions different than Turing patterns. By validating its efficacy across a wider range of models, this research lays the groundwork for applying pDMD to experimental spatiotemporal data, advancing predictions crucial for soil microbial ecology and agricultural sustainability.

Suggested Citation

  • Monti, Angela & Diele, Fasma & Lacitignola, Deborah & Marangi, Carmela, 2025. "Patterns in soil organic carbon dynamics: Integrating microbial activity, chemotaxis and data-driven approaches," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 234(C), pages 86-101.
    • Handle: RePEc:eee:matcom:v:234:y:2025:i:c:p:86-101
    DOI: 10.1016/j.matcom.2025.02.019
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    References listed on IDEAS

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    1. Guillaume Patoine & Nico Eisenhauer & Simone Cesarz & Helen R. P. Phillips & Xiaofeng Xu & Lihua Zhang & Carlos A. Guerra, 2022. "Drivers and trends of global soil microbial carbon over two decades," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Lacitignola, Deborah & Diele, Fasma, 2021. "Using awareness to Z-control a SEIR model with overexposure: Insights on Covid-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    3. Mimura, Masayasu & Tsujikawa, Tohru, 1996. "Aggregating pattern dynamics in a chemotaxis model including growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 230(3), pages 499-543.
    4. Fasma Diele & Carmela Marangi, 2019. "Geometric Numerical Integration in Ecological Modelling," Mathematics, MDPI, vol. 8(1), pages 1-30, December.
    5. Katerina Georgiou & Rose Z. Abramoff & John Harte & William J. Riley & Margaret S. Torn, 2017. "Microbial community-level regulation explains soil carbon responses to long-term litter manipulations," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    6. Cordula Vogel & Carsten W. Mueller & Carmen Höschen & Franz Buegger & Katja Heister & Stefanie Schulz & Michael Schloter & Ingrid Kögel-Knabner, 2014. "Submicron structures provide preferential spots for carbon and nitrogen sequestration in soils," Nature Communications, Nature, vol. 5(1), pages 1-7, May.
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