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Measuring sensitivity of robustness and network indices for an estuarine food web model under perturbations

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  • Mukherjee, Joyita
  • Scharler, Ursula M.
  • Fath, Brian D.
  • Ray, Santanu

Abstract

Robustness is a universal feature of ecological systems which promotes sustainability over time. Robustness of an aquatic ecosystem, specifically an estuarine system, is investigated here using indicators derived from ecological network analysis. Estuaries provide us with many ecosystem services and these are consequently prone to face anthropogenic stresses. In South Africa, temporarily open/closed estuaries occupy a significant percentage of coastal boundaries. One of the South African estuaries, namely Mdloti, is studied here using network-based, Ecopath software. The estuarine energy flow networks are perturbed following different scenarios, which are assumed to be a result of selected anthropogenic stresses (eutrophication, overfishing) to the system. Several network indices such as total system throughput (TST), redundancy (R), Finn’s Cycling Index (FCI) and ascendency over development capacity ratio (A/C) are calculated and analyzed for the original field-based network and three perturbed networks under different scenarios (change of autotrophic biomass, fish yield, and detritus import). The change of ecosystem robustness from the unperturbed network is more pronounced in the perturbed networks of fish biomass change and detritus import than change in autotrophic biomass scenario. These indicators reliably reflected the relative change of flow pattern if any changes occur and magnitude in the networks in different scenarios. From the present study, we show that certain common network indices as mentioned above provide a measure of robustness and can be used for the assessment of ecosystem organization and function. ENA properties and also robustness change depending on the type and magnitude of stress imposed on the system.

Suggested Citation

  • Mukherjee, Joyita & Scharler, Ursula M. & Fath, Brian D. & Ray, Santanu, 2015. "Measuring sensitivity of robustness and network indices for an estuarine food web model under perturbations," Ecological Modelling, Elsevier, vol. 306(C), pages 160-173.
  • Handle: RePEc:eee:ecomod:v:306:y:2015:i:c:p:160-173
    DOI: 10.1016/j.ecolmodel.2014.10.027
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    2. Ali Kharrazi & Brian D. Fath & Harald Katzmair, 2016. "Advancing Empirical Approaches to the Concept of Resilience: A Critical Examination of Panarchy, Ecological Information, and Statistical Evidence," Sustainability, MDPI, vol. 8(9), pages 1-17, September.
    3. Ali Kharrazi & Elena Rovenskaya & Brian D Fath, 2017. "Network structure impacts global commodity trade growth and resilience," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.
    4. Francisco Orlando Rosales & Brian D. Fath & Grace Yolanda Llerena, 2023. "Quantifying a virtual water metabolic network of the Metropolitan District of Quito, Ecuador using ecological network methods," Journal of Industrial Ecology, Yale University, vol. 27(5), pages 1304-1318, October.
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    6. Solovjova, N.V., 2019. "Ecological risk modelling in developing resources of ecosystems characterized by varying vulnerability levels," Ecological Modelling, Elsevier, vol. 406(C), pages 60-72.

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