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Fuzzy modeling of plankton networks

Author

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  • de Andrade, Lúcio Pereira
  • Espíndola, Rogério Pinto
  • Pereira, Gilberto Carvalho
  • Ebecken, Nelson Francisco Favilla

Abstract

This work aims to show the trophic structure of a real plankton community from Angra dos Reis estuary using in situ flow cytometry for data acquisition, and how competition, as a non-trophic interaction, is structured amid the trophic interactions – predation and herbivory. As no previous information is given, a great research challenge is how to mathematically represent such relations and their interaction strengths. For this purpose, such data were modeled by a fuzzy complex network through a multigraph view. To reduce its complexity, an ant colony algorithm was employed to detect its substructures called communities or compartiments. These approaches have allowed the discrimination and the quantification of relevant linkages and process, search into topological characteristics as triangles or loop distribution to the node degrees, and access the number of communities within network. Futhermore, it was considered the distribution of organisms acording to their sizes and ecological roles. Comparisons with other network indices and patterns found in the literature and in nature, respectively, indicate that our approach is adequate.

Suggested Citation

  • de Andrade, Lúcio Pereira & Espíndola, Rogério Pinto & Pereira, Gilberto Carvalho & Ebecken, Nelson Francisco Favilla, 2016. "Fuzzy modeling of plankton networks," Ecological Modelling, Elsevier, vol. 337(C), pages 149-155.
  • Handle: RePEc:eee:ecomod:v:337:y:2016:i:c:p:149-155
    DOI: 10.1016/j.ecolmodel.2016.06.015
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    References listed on IDEAS

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    1. Zhou, Xu & Liu, Yanheng & Zhang, Jindong & Liu, Tuming & Zhang, Di, 2015. "An ant colony based algorithm for overlapping community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 289-301.
    2. Wen-chuan Wang & Dong-mei Xu & Kwok-wing Chau & Guan-jun Lei, 2014. "Assessment of River Water Quality Based on Theory of Variable Fuzzy Sets and Fuzzy Binary Comparison Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4183-4200, September.
    3. Pereira, Gilberto C. & Evsukoff, Alexandre & Ebecken, Nelson F.F., 2009. "Fuzzy modelling of chlorophyll production in a Brazilian upwelling system," Ecological Modelling, Elsevier, vol. 220(12), pages 1506-1512.
    4. Ji, Junzhong & Song, Xiangjing & Liu, Chunnian & Zhang, Xiuzhen, 2013. "Ant colony clustering with fitness perception and pheromone diffusion for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3260-3272.
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    Cited by:

    1. Pereira, G.C. & Andrade, L.P. & Espíndola, R.P. & Ebecken, N.F.F., 2019. "Ecological networks simulation by fuzzy ecotoxicological rules," Ecological Modelling, Elsevier, vol. 409(C), pages 1-1.

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