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Plant-host shift, spatial persistence, and the viability of an invasive insect population

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  • de Godoy, Isabelle Bueno Silva
  • McGrane-Corrigan, Blake
  • Mason, Oliver
  • Moral, Rafael de Andrade
  • Godoy, Wesley Augusto Conde

Abstract

Assessing the effects of a plant-host shift is important for monitoring insect populations over long time periods and for interventions in a conservation or pest management framework. In a heterogeneous environment, individuals may disperse between sources and sinks in order to persist. Here we propose a single-species two-patch model that aims to capture the generational movement of an insect that exhibits density-dependent dispersal, to see how shifting between hosts could alter its viability and asymptotic dynamics. We then analyse the stability and persistence properties of the model and further validate it using parameter estimates derived from laboratory experiments. In order to evaluate the potential of this model, we applied it to Drosophila suzukii (Diptera: Drosophilidae), which has become a harmful pest in several countries around the world. Although many studies have investigated the preference and attractiveness of potential hosts on this invasive drosophilid, no studies thus far have investigated whether a shift of fruit host could affect such a species’ ecological viability or spatiotemporal persistence. The model results show that a shift in host choice can significantly affect the growth potential and fecundity of a species such as D. suzukii, which ultimately could aid such invasive populations in their ability to persist within a changing environment.

Suggested Citation

  • de Godoy, Isabelle Bueno Silva & McGrane-Corrigan, Blake & Mason, Oliver & Moral, Rafael de Andrade & Godoy, Wesley Augusto Conde, 2023. "Plant-host shift, spatial persistence, and the viability of an invasive insect population," Ecological Modelling, Elsevier, vol. 475(C).
  • Handle: RePEc:eee:ecomod:v:475:y:2023:i:c:s0304380022002733
    DOI: 10.1016/j.ecolmodel.2022.110172
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    References listed on IDEAS

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    1. Iskin da S. Costa, Michel & dos Anjos, Lucas, 2018. "Multiple hydra effect in a predator–prey model with Allee effect and mutual interference in the predator," Ecological Modelling, Elsevier, vol. 373(C), pages 22-24.
    2. V.A.A. Jansen & K. Sigmund, 1998. "Shaken Not Stirred: On Permanence in Ecological Communities," Working Papers ir98101, International Institute for Applied Systems Analysis.
    3. Bartolo Luque & Lucas Lacasa & Fernando J Ballesteros & Alberto Robledo, 2011. "Feigenbaum Graphs: A Complex Network Perspective of Chaos," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-8, September.
    4. Langille, Aaron B. & Arteca, Ellen M. & Ryan, Geraldine D. & Emiljanowicz, Lisa M. & Newman, Jonathan A., 2016. "North American invasion of Spotted-Wing Drosophila (Drosophila suzukii): A mechanistic model of population dynamics," Ecological Modelling, Elsevier, vol. 336(C), pages 70-81.
    5. Nikhil Pal & Sudip Samanta & Maia Martcheva & Joydev Chattopadhyay, 2018. "Role of Bi-Directional Migration in Two Similar Types of Ecosystems," Mathematics, MDPI, vol. 6(3), pages 1-16, March.
    6. Powell, James A. & Bentz, Barbara J., 2014. "Phenology and density-dependent dispersal predict patterns of mountain pine beetle (Dendroctonus ponderosae) impact," Ecological Modelling, Elsevier, vol. 273(C), pages 173-185.
    7. Rizopoulos, Dimitris, 2010. "JM: An R Package for the Joint Modelling of Longitudinal and Time-to-Event Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 35(i09).
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