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

IF 4.4 2区 数学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Angela Monti , Fasma Diele , Deborah Lacitignola , Carmela Marangi
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引用次数: 0

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.
土壤有机碳动态模式:整合微生物活动、趋化性和数据驱动方法
土壤有机碳(SOC)模型往往忽略了空间维度和微生物活动的影响。在本文中,我们重点研究了有机碳动力学的两种反应-扩散趋化模型,它们都支持趋化驱动的不稳定性,并且当微生物趋化敏感性高于临界阈值时,它们表现出条纹、斑点和六边形等多种空间模式。我们使用辛技术来数值近似趋化驱动的空间模式,并探索分段动态模式分解(pDMD)重建它们的有效性。此外,我们还分析了pDMD在中等时间范围内的预测性能。我们的研究结果表明,pDMD在精确重建和预测趋化驱动的空间模式方面是有效的,因此拓宽了该方法在不同于图灵模式的解决方案中的应用范围。通过在更广泛的模型中验证其有效性,本研究为将pDMD应用于实验时空数据,推进对土壤微生物生态和农业可持续性至关重要的预测奠定了基础。
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来源期刊
Mathematics and Computers in Simulation
Mathematics and Computers in Simulation 数学-计算机:跨学科应用
CiteScore
8.90
自引率
4.30%
发文量
335
审稿时长
54 days
期刊介绍: The aim of the journal is to provide an international forum for the dissemination of up-to-date information in the fields of the mathematics and computers, in particular (but not exclusively) as they apply to the dynamics of systems, their simulation and scientific computation in general. Published material ranges from short, concise research papers to more general tutorial articles. Mathematics and Computers in Simulation, published monthly, is the official organ of IMACS, the International Association for Mathematics and Computers in Simulation (Formerly AICA). This Association, founded in 1955 and legally incorporated in 1956 is a member of FIACC (the Five International Associations Coordinating Committee), together with IFIP, IFAV, IFORS and IMEKO. Topics covered by the journal include mathematical tools in: •The foundations of systems modelling •Numerical analysis and the development of algorithms for simulation They also include considerations about computer hardware for simulation and about special software and compilers. The journal also publishes articles concerned with specific applications of modelling and simulation in science and engineering, with relevant applied mathematics, the general philosophy of systems simulation, and their impact on disciplinary and interdisciplinary research. The journal includes a Book Review section -- and a "News on IMACS" section that contains a Calendar of future Conferences/Events and other information about the Association.
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