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Forecasting the ongoing invasion of Lagocephalus sceleratus in the Mediterranean Sea

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  • Coro, Gianpaolo
  • Vilas, Luis Gonzalez
  • Magliozzi, Chiara
  • Ellenbroek, Anton
  • Scarponi, Paolo
  • Pagano, Pasquale

Abstract

Invasive species from the Suez Canal, also named “Lessepsian species”, often have an ecological and financial impact on marine life, fisheries, human well-being and health in the Mediterranean Sea. Among these, the silver-cheeked toad-fish Lagocephalus sceleratus (Gmelin, 1789) has rapidly colonised the eastern Mediterranean basin and is currently moving westwards. This pufferfish has a highly opportunistic behaviour, it attacks fish captured in nets and lines and seriously damages fishing gears and catch. It is a highly-toxic species with no immediate economic value for the Mediterranean market, although it currently represents 4% of the weight of the total artisanal catches. Consequently, the possible effects on Mediterranean fisheries and health require to enhance our understanding about the future geographical distribution of this pufferfish in the whole basin.

Suggested Citation

  • Coro, Gianpaolo & Vilas, Luis Gonzalez & Magliozzi, Chiara & Ellenbroek, Anton & Scarponi, Paolo & Pagano, Pasquale, 2018. "Forecasting the ongoing invasion of Lagocephalus sceleratus in the Mediterranean Sea," Ecological Modelling, Elsevier, vol. 371(C), pages 37-49.
    • Handle: RePEc:eee:ecomod:v:371:y:2018:i:c:p:37-49
    DOI: 10.1016/j.ecolmodel.2018.01.007
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    References listed on IDEAS

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    1. Coro, Gianpaolo & Magliozzi, Chiara & Vanden Berghe, Edward & Bailly, Nicolas & Ellenbroek, Anton & Pagano, Pasquale, 2016. "Estimating absence locations of marine species from data of scientific surveys in OBIS," Ecological Modelling, Elsevier, vol. 323(C), pages 61-76.
    2. Pouteau, Robin & Meyer, Jean-Yves & Stoll, Benoît, 2011. "A SVM-based model for predicting distribution of the invasive tree Miconia calvescens in tropical rainforests," Ecological Modelling, Elsevier, vol. 222(15), pages 2631-2641.
    3. Coro, Gianpaolo & Magliozzi, Chiara & Ellenbroek, Anton & Pagano, Pasquale, 2015. "Improving data quality to build a robust distribution model for Architeuthis dux," Ecological Modelling, Elsevier, vol. 305(C), pages 29-39.
    4. Ready, Jonathan & Kaschner, Kristin & South, Andy B. & Eastwood, Paul D. & Rees, Tony & Rius, Josephine & Agbayani, Eli & Kullander, Sven & Froese, Rainer, 2010. "Predicting the distributions of marine organisms at the global scale," Ecological Modelling, Elsevier, vol. 221(3), pages 467-478.
    5. Sadeghi, Roghayeh & Zarkami, Rahmat & Sabetraftar, Karim & Van Damme, Patrick, 2012. "Use of support vector machines (SVMs) to predict distribution of an invasive water fern Azolla filiculoides (Lam.) in Anzali wetland, southern Caspian Sea, Iran," Ecological Modelling, Elsevier, vol. 244(C), pages 117-126.
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    1. G. Mateo, Rubén & Aroca-Fernández, María José & Gastón, Aitor & Gómez-Rubio, Virgilio & Saura, Santiago & García-Viñas, Juan Ignacio, 2019. "Looking for an optimal hierarchical approach for ecologically meaningful niche modelling," Ecological Modelling, Elsevier, vol. 409(C), pages 1-1.
    2. Fabio Boschetti & Michael Hughes & Cheryl Jones & Hector Lozano-Montes, 2018. "On Decision Makers’ Perceptions of What an Ecological Computer Model is, What It Does, and Its Impact on Limiting Model Acceptance," Sustainability, MDPI, vol. 10(8), pages 1-10, August.
    3. Coro, Gianpaolo, 2020. "A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate," Ecological Modelling, Elsevier, vol. 431(C).

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