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      Molecular-Level Variation Affects Population Growth in a Butterfly Metapopulation

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      1 , , 2
      PLoS Biology
      Public Library of Science

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          Abstract

          The dynamics of natural populations are thought to be dominated by demographic and environmental processes with little influence of intraspecific genetic variation and natural selection, apart from inbreeding depression possibly reducing population growth in small populations. Here we analyse hundreds of well-characterised local populations in a large metapopulation of the Glanville fritillary butterfly (Melitaea cinxia), which persists in a balance between stochastic local extinctions and recolonisations in a network of 4,000 discrete habitat patches. We show that the allelic composition of the glycolytic enzyme phosphoglucose isomerase (Pgi) has a significant effect on the growth of local populations, consistent with previously reported effects of allelic variation on flight metabolic performance and fecundity in the Glanville fritillary and Colias butterflies. The strength and the sign of the molecular effect on population growth are sensitive to the ecological context (the area and spatial connectivity of the habitat patches), which affects genotype-specific gene flow and the influence of migration on the dynamics of local populations. The biological significance of the results for Pgi is underscored by lack of any association between population growth and allelic variation at six other loci typed in the same material. In demonstrating, to our knowledge for the first time, that molecular variation in a candidate gene affects population growth, this study challenges the perception that differential performance of individual genotypes, leading to differential fitness, is irrelevant to population dynamics. These results also demonstrate that the spatial configuration of habitat and spatial dynamics of populations contribute to maintenance of Pgi polymorphism in this species.

          Abstract

          Researchers observe a link between the genetic composition of the Pgi locus (an enzyme linked with flight metabolic performance) and local population growth within a metapopulation of butterflies.

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          Most cited references58

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          Metapopulation dynamics

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            Influence of gene action across different time scales on behavior.

            Genes can affect natural behavioral variation in different ways. Allelic variation causes alternative behavioral phenotypes, whereas changes in gene expression can influence the initiation of behavior at different ages. We show that the age-related transition by honey bees from hive work to foraging is associated with an increase in the expression of the foraging (for) gene, which encodes a guanosine 3',5'-monophosphate (cGMP)-dependent protein kinase (PKG). cGMP treatment elevated PKG activity and caused foraging behavior. Previous research showed that allelic differences in PKG expression result in two Drosophila foraging variants. The same gene can thus exert different types of influence on a behavior.
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              Density cycles and an offspring quantity and quality game driven by natural selection.

              A long-standing hypothesis posits that natural selection can favour two female strategies when density cycles. At low density, females producing many smaller progeny are favoured when the intrinsic rate of increase, r, governs population growth. At peak density, females producing fewer, high-quality, progeny are favoured when the carrying capacity, K, is exceeded and the population crashes. Here we report on the first example of a genetic r versus K selection game that promotes stable population cycles in lizards. Decade-long fitness studies and game theory demonstrated that two throat-colour morphs were refined by selection in which the strength of natural selection varied with density. Orange-throated females, r strategists, produced many eggs and were favoured at low density. Conversely, yellow-throated females, K strategists, produced large eggs and were favoured at high density. Progeny size should also be under negative frequency-dependent selection in that large progeny will have a survival advantage when rare, but the advantage disappears when they become common. We confirmed this prediction by seeding field plots with rare and common giant hatchlings. Thus, intrinsic causes of frequency- and density-dependent selection promotes an evolutionary game with two-generation oscillations.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Biol
                pbio
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                May 2006
                25 April 2006
                : 4
                : 5
                : e129
                Affiliations
                [1] 1Department of Biological and Environmental Sciences, University of Helsinki, Finland
                [2] 2School of Biological Sciences, University of Liverpool, Liverpool, United Kingdom
                University of Edinburgh United Kingdom
                Article
                10.1371/journal.pbio.0040129
                1440940
                16620151
                f9ed54e4-4a35-4ee5-97fe-0ac9d9e3eb50
                Copyright: © 2006 Hanski and Saccheri. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 10 January 2006
                : 21 February 2006
                Categories
                Research Article
                Ecology
                Evolution
                Genetics/Genomics/Gene Therapy
                Zoology
                Insects
                Arthropods
                Animals
                Eukaryotes

                Life sciences
                Life sciences

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