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Modeling the bioenergetics of two herbivorous fish species in the Mediterranean Sea: The native Sarpa salpa and the invasive Siganus rivulatus

Author

Listed:
  • Stavrakidis-Zachou, Orestis
  • Klagkou, Evridiki
  • Livanou, Eleni
  • Lika, Konstadia

Abstract

Global warming has facilitated the invasion of several Red Sea species in the Mediterranean Sea; a phenomenon known as Lessepsian migration. In this work, two key Mediterranean herbivore fish, the native salema (Sarpa salpa) and the invasive marbled spinefoot (Siganus rivulatus) were studied via the lens of bioenergetic modeling based on Dynamic Energy Budget theory. Models for the two species were developed and subsequently used to simulate their performance under gradients of temperature and food as well as explore effects of historical changes in temperature between a past, colder (1982–1997), and a recent, warmer (1998–2022), period for the north and south Eastern Mediterranean Sea. Over this time, our results indicate a progressive benefit in growth for the invasive siganid compared to salema, offering, thus, a competitive advantage for the former, which may contribute to the interpretation of its rapid expansion in the region. In addition, the presented models allow for exploration of other effects such as competition for food resources or differences in reproduction traits, which are discussed in light of existing knowledge. This work contributes towards a better understanding of the complex phenomenon of bioinvasions by offering a mechanistic approach to study the metabolism and performance of invasive and native species under the climate-driven, dynamic environment of the Mediterranean Sea.

Suggested Citation

  • Stavrakidis-Zachou, Orestis & Klagkou, Evridiki & Livanou, Eleni & Lika, Konstadia, 2024. "Modeling the bioenergetics of two herbivorous fish species in the Mediterranean Sea: The native Sarpa salpa and the invasive Siganus rivulatus," Ecological Modelling, Elsevier, vol. 495(C).
  • Handle: RePEc:eee:ecomod:v:495:y:2024:i:c:s0304380024001923
    DOI: 10.1016/j.ecolmodel.2024.110804
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