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Ecological networks simulation by fuzzy ecotoxicological rules

Author

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  • Pereira, G.C.
  • Andrade, L.P.
  • Espíndola, R.P.
  • Ebecken, N.F.F.

Abstract

This paper emphasizes the integration of ecology and ecotoxicology. The main objective is to present the development of an early warning tool for environmental risk assessment. First, a reference ecological network of a plankton community was built from in situ flow cytometry data. Next, a set of fuzzy ecotoxicological rules to explain impacts from three pollutants were constructed from the scientific literature and expert knowledge. These rules were applied to the plankton network to simulate disturbance and produce an impacted network. Network indices were used to assess the consequences of this simulated disturbance, and a regime shift in the planktonic system was noted. Coastal zone ecosystem managers could use this type of model to anticipate early warnings in disturbance scenarios, allowing estimates of possible impacts to the marine ecosystem.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecomod:v:409:y:2019:i:c:9
    DOI: 10.1016/j.ecolmodel.2019.108733
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    References listed on IDEAS

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    1. Fath, Brian D. & Scharler, Ursula M. & Baird, Dan, 2013. "Dependence of network metrics on model aggregation and throughflow calculations: Demonstration using the Sylt–Rømø Bight Ecosystem," Ecological Modelling, Elsevier, vol. 252(C), pages 214-219.
    2. Kones, Julius K. & Soetaert, Karline & van Oevelen, Dick & Owino, John O., 2009. "Are network indices robust indicators of food web functioning? A Monte Carlo approach," Ecological Modelling, Elsevier, vol. 220(3), pages 370-382.
    3. 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.
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    Cited by:

    1. Olusoji, Oluwafemi D. & Spaak, Jurg W. & Holmes, Mark & Neyens, Thomas & Aerts, Marc & De Laender, Frederik, 2021. "cyanoFilter: An R package to identify phytoplankton populations from flow cytometry data using cell pigmentation and granularity," Ecological Modelling, Elsevier, vol. 460(C).

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