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Allometry and Dissipation of Ecological Flow Networks

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  • Jiang Zhang
  • Lingfei Wu

Abstract

Background: An ecological flow network is a weighted directed graph in which the nodes are species, the edges are “who eats whom” relationships and the weights are rates of energy or nutrient transferred between species. Allometric scaling is a ubiquitous feature for flow systems such as river basins, vascular networks and food webs. Methodology: The “ecological network analysis” can serve to reveal hidden allometries, the power law relationship between the throughflux and the indirect impact of node , directly from the original flow networks without any need to cut edges in the network. The dissipation law, which is another significant scaling relationship between the energy dissipation (respiration) and the throughflow of any species, is also obtained from an analysis of the empirical flow networks. Interestingly, the exponents of the allometric law () and the dissipation law () show a strong relationship for both empirical and simulated flow networks. The dissipation law exponent , rather than the topology of the network, is the most important factors that affect the allometric exponent . Conclusions: The exponent can be interpreted as the degree of centralization of the network, i.e., the concentration of impacts (direct and indirect influences on the entire network along all energy flow pathways) on hubs (the nodes with large throughflows). As a result, we find that as increases, the relative energy loss of large nodes increases, decreases, i.e., the relative importance of large species decreases. Moreover, the entire flow network is more decentralized. Therefore, network flow structure (allometry) and thermodynamic constraints (dissipation) are linked.

Suggested Citation

  • Jiang Zhang & Lingfei Wu, 2013. "Allometry and Dissipation of Ecological Flow Networks," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-8, September.
  • Handle: RePEc:plo:pone00:0072525
    DOI: 10.1371/journal.pone.0072525
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    References listed on IDEAS

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    Cited by:

    1. Wang, Cheng-Jun & Wu, Lingfei, 2016. "The scaling of attention networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 196-204.
    2. 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.
    3. Peiteng Shi & Jiang Zhang & Bo Yang & Jingfei Luo, 2014. "Hierarchicality of Trade Flow Networks Reveals Complexity of Products," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-10, June.
    4. Guo, Liangzhu & Lou, Xiaodan & Shi, Peiteng & Wang, Jun & Huang, Xiaohan & Zhang, Jiang, 2015. "Flow distances on open flow networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 235-248.
    5. Bin Shen & Jiang Zhang & Yixiao Li & Qiuhua Zheng & Xingsen Li, 2015. "International Trade Modelling Using Open Flow Networks: A Flow-Distance Based Analysis," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-16, November.

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