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Dynamic Ecological System Analysis

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  • Coskun, Huseyin

Abstract

This article develops a new mathematical method for holistic analysis of nonlinear dynamic compartmental systems through the system decomposition theory. The method is based on the novel dynamic system and subsystem partitioning methodologies through which compartmental systems are decomposed to the utmost level. The dynamic system and subsystem partitioning enable tracking the evolution of the initial stocks, environmental inputs, and intercompartmental system flows, as well as the associated storages derived from these stocks, inputs, and flows individually and separately within the system. Moreover, the transient and the dynamic direct, indirect, acyclic, cycling, and transfer (diact) flows and associated storages transmitted along a given flow path or from one compartment, directly or indirectly, to any other are analytically characterized, systematically classified, and mathematically formulated. Further, the article develops a dynamic technique based on the diact transactions for the quantitative classification of interspecific interactions and the determination of their strength within food webs. Major concepts and quantities of the current static network analyses are also extended to nonlinear dynamic settings and integrated with the proposed dynamic measures and indices within the proposed unifying mathematical framework. Therefore, the proposed methodology enables a holistic view and analysis of ecological systems. We consider that this methodology brings a novel complex system theory to the service of urgent and challenging environmental problems of the day and has the potential to lead the way to a more formalistic ecological science.

Suggested Citation

  • Coskun, Huseyin, 2018. "Dynamic Ecological System Analysis," OSF Preprints 35xkb, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:35xkb
    DOI: 10.31219/osf.io/35xkb
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    References listed on IDEAS

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    1. Ma, Q. & Kazanci, C., 2013. "Analysis of indirect effects within ecosystem models using pathway-based methodology," Ecological Modelling, Elsevier, vol. 252(C), pages 238-245.
    2. Reid Bailey & Bert Bras & Janet K. Allen, 2004. "Applying Ecological Input‐Output Flow Analysis to Material Flows in Industrial Systems: Part II: Flow Metrics," Journal of Industrial Ecology, Yale University, vol. 8(1‐2), pages 69-91, January.
    3. Allen, Timothy & Giampietro, Mario, 2014. "Holons, creaons, genons, environs, in hierarchy theory: Where we have gone," Ecological Modelling, Elsevier, vol. 293(C), pages 31-41.
    4. Shevtsov, Jane & Kazanci, Caner & Patten, Bernard C., 2009. "Dynamic environ analysis of compartmental systems: A computational approach," Ecological Modelling, Elsevier, vol. 220(22), pages 3219-3224.
    5. Tollner, E.W. & Schramski, J.R. & Kazanci, C. & Patten, B.C., 2009. "Implications of network particle tracking (NPT) for ecological model interpretation," Ecological Modelling, Elsevier, vol. 220(16), pages 1904-1912.
    6. Kazanci, C. & Ma, Q., 2012. "Extending ecological network analysis measures to dynamic ecosystem models," Ecological Modelling, Elsevier, vol. 242(C), pages 180-188.
    7. Kazanci, C. & Matamba, L. & Tollner, E.W., 2009. "Cycling in ecosystems: An individual based approach," Ecological Modelling, Elsevier, vol. 220(21), pages 2908-2914.
    8. Reid Bailey & Janet K. Allen & Bert Bras, 2004. "Applying Ecological Input‐Output Flow Analysis to Material Flows in Industrial Systems: Part I: Tracing Flows," Journal of Industrial Ecology, Yale University, vol. 8(1‐2), pages 45-68, January.
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