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Analysis of Clines with Variable Selection and Variable Migration.

Thomas Lenormand, Michel Raymond

    The American Naturalist
    |February 5, 2000
    PubMed
    Summary
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    Mosquitoes show extensive, asymmetrical migration and fitness costs for insecticide resistance alleles. This study reveals how population genetics can track ecological and evolutionary changes over time.

    Area of Science:

    • Evolutionary biology
    • Population genetics
    • Ecological dynamics

    Background:

    • Insecticide resistance in Culex pipiens is a significant public health concern.
    • Understanding local adaptation requires analyzing changes in genetic markers over time.
    • Previous migration estimates in mosquitoes were limited to specific seasons.

    Purpose of the Study:

    • To develop a likelihood-based method for estimating dispersal and natural selection.
    • To investigate local adaptation in Culex pipiens to organophosphate insecticides.
    • To analyze clinal pattern modifications at resistance loci during seasonal transitions.

    Main Methods:

    • Developed a novel likelihood-based method to estimate dispersal and selection.
    • Analyzed clinal patterns of two resistance loci in Culex pipiens.
    Keywords:
    asymmetrical gene flowclinefitness costinsecticide resistanceselectionvariable gene flow

    Related Experiment Videos

  • Compared genetic data from breeding to overwintering periods.

    • Main Results:

    • Mosquitoes exhibit extensive and asymmetrical migration between breeding and overwintering sites.
    • Migration rates differ significantly from previous estimates.
    • Resistance alleles incur substantial fitness costs during overwintering.
    • Overwintering initiation varies geographically.

    Conclusions:

    • The developed method effectively tracks demographic and adaptive microevolutionary processes.
    • Seasonal changes in mosquito populations reveal complex ecological and evolutionary dynamics.
    • Population genetics and statistical models offer a powerful framework for studying adaptation.