Artificial selection for enhanced flight propensity in an invasive species ( Ceratitis capitata ) reveals minimal trade-offs

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ID: 333635
2026
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Abstract
Abstract Enhanced flight propensity may facilitate range expansions with implications for evolutionary potential, population dynamics, and species invasions. This study investigated artificial selection for flight propensity in a highly invasive agricultural fruit pest, the Mediterranean fruit fly (Medfly), Ceratitis capitata under laboratory conditions. A selection filter was applied for 4–5 generations of C. capitata to select for the fastest (and as a reference group the most lethargic) flyers. Individuals that were able to rapidly overcome a flight barrier were termed “Flyers”, while philopatric individuals were referred to as “Non-flyers.” Flight propensity was quantified using flight performance measurements, whereas walking speed was used as a measurement of locomotor activity. Reproductive traits, thermal performance (i.e., chill coma recovery and heat knockdown time), and desiccation and starvation resistance were assessed for potential physiological trade-offs that may be associated with increased flight propensity. Flight performance trials showed that Flyers performed significantly better than Non-flyers after 4–5 generations of selection, with only female Flyers showing an increased body mass compared to Non-flyers. Cold stress-resistance was the only trait where Non-flyers outperformed Flyers, while thermal tolerance and fecundity traits remained similar between Flyers and Non-flyers. These findings demonstrated that it may be possible to select for enhanced flight propensity without incurring substantial performance or life-history costs. The ability to improve flight performance with minimal costs could be a key factor contributing to the success of invasive species, such as the Mediterranean fruit fly.
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openalex_W7223402038 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal journal of evolutionary biology
Year 2026
DOI
10.1093/jeb/voag114
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