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Dynamical and system-wide properties of linear flow-quantified food webs

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  • Buzhdygan, Oksana Y.
  • Patten, Bernard C.
  • Kazanci, Caner
  • Ma, Qianqian
  • Rudenko, Svitlana S.

Abstract

This paper analyses the transient dynamics, steady states, and a set of diagnostic system-wide properties of a linear flow-quantified pastoral food web from the Chernivtsi Region of Ukraine. The web in question is one of 31 so-described; it contains 86 nodes and 496 links. On-line simulation and network analysis software EcoNet was used to quantify transient dynamics, steady states, and eleven system-wide index parameters. Food-web flows were classified into inputs, interior flows, and outputs. The last two (endogenous) were represented by linear, mass-balance, flow coefficients. The three sets, inputs plus these coefficients, were systematically manipulated in their entirety in different combinations over seven orders of magnitude to determine their effects on system properties. The results of these trials are described and interpreted. They show that linear descriptions of empirical food webs harbor considerable dynamic and relational complexity.

Suggested Citation

  • Buzhdygan, Oksana Y. & Patten, Bernard C. & Kazanci, Caner & Ma, Qianqian & Rudenko, Svitlana S., 2012. "Dynamical and system-wide properties of linear flow-quantified food webs," Ecological Modelling, Elsevier, vol. 245(C), pages 176-184.
    • Handle: RePEc:eee:ecomod:v:245:y:2012:i:c:p:176-184
    DOI: 10.1016/j.ecolmodel.2012.02.024
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    References listed on IDEAS

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    1. Kazanci, C. & Matamba, L. & Tollner, E.W., 2009. "Cycling in ecosystems: An individual based approach," Ecological Modelling, Elsevier, vol. 220(21), pages 2908-2914.
    2. Kazancı, Caner, 2007. "EcoNet: A new software for ecological modeling, simulation and network analysis," Ecological Modelling, Elsevier, vol. 208(1), pages 3-8.
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    1. Buzhdygan, O.Y. & Rudenko, S.S. & Patten, B.C. & Kostyshyn, S.S., 2014. "Food-web topology of Ukrainian mountain grasslands: Comparative properties and relations to ecosystem parameters," Ecological Modelling, Elsevier, vol. 293(C), pages 128-138.
    2. Burns, Thomas P. & Rose, Kenneth A. & Brenkert, Antoinette L., 2014. "Quantifying direct and indirect effects of perturbations using model ecosystems," Ecological Modelling, Elsevier, vol. 293(C), pages 69-80.
    3. Buzhdygan, Oksana Y. & Rudenko, Svitlana S. & Kazanci, Caner & Patten, Bernard C., 2016. "Effect of invasive black locust (Robinia pseudoacacia L.) on nitrogen cycle in floodplain ecosystem," Ecological Modelling, Elsevier, vol. 319(C), pages 170-177.
    4. Patten, Bernard C., 2015. "Link tracking: Quantifying network flows from qualitative node–link digraphs," Ecological Modelling, Elsevier, vol. 295(C), pages 47-58.
    5. Borrett, Stuart R. & Sheble, Laura & Moody, James & Anway, Evan C., 2018. "Bibliometric review of ecological network analysis: 2010–2016," Ecological Modelling, Elsevier, vol. 382(C), pages 63-82.
    6. Xu, Wanying & Zhou, Chuanbin & Cao, Aixin & Luo, Min, 2016. "Understanding the mechanism of food waste management by using stakeholder analysis and social network model: An industrial ecology perspective," Ecological Modelling, Elsevier, vol. 337(C), pages 63-72.

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