Population structure of the beetle pests Phyllodecta vulgatissima and P. vitellinae on UK willow plantations.
ABSTRACT Phyllodecta (= Phratora) vulgatissima and P. vitellinae (Coleoptera: Chrysomelidae) are important pests of willows and poplars. Their differences in host species preference may provide a non-chemical control strategy for pest control. However, little is known about population structure with respect to hosts, regions or seasons. Using five microsatellites, 850 P. vulgatissima and 1100 P. vitellinae individuals, comprising 17 and 22 UK samples, respectively, were genotyped. High diversity was observed at all loci. Migrant numbers exchanged per generation (Nm) were high (2.1-12.6 for P. vulgatissima and 0.9-12.2 for P. vitellinae), suggesting high genetic exchange between samples. Estimates of population differentiation (FST) and analyses of the data using Bayesian methods (Partition and Structure) showed little evidence of subdivision in relation to geography, sampling time or host.
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ABSTRACT: The boll weevil (Anthonomus grandis Boheman) is an insect pest of cotton that underwent a well-documented range expansion across the southeastern U.S. from Mexico beginning about 110 years ago. Eleven microsatellite loci were surveyed to infer the magnitude and pattern of genetic differentiation among boll weevil populations from 18 locations across eight U.S. states and northeast Mexico. Estimates of genetic diversity (allelic diversity and heterozygosity) were greater in Southern than Northern populations, and were greater in the west than the east among Northern populations. Boll weevil populations were genetically structured as a whole across the geographic range sampled, with a global F (ST) of 0.241. South-central populations exhibit classic isolation by distance, but evidence suggests that populations within the Eastern and Western regions have not yet reached genetic equilibrium. Gene flow appears to be relatively high among populations within the Eastern region. Population assignment data and estimates of gene flow indicate that migration between locations separated by < 300 km is frequent. The database of microsatellite genotypes generated in this study now makes it possible, through population assignment techniques, to identify the most likely geographic source of a boll weevil reintroduced to an eradication zone, which will help action agencies decide the most appropriate mitigation response.Genetica 05/2006; 127(1-3):143-61. · 1.68 Impact Factor
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ABSTRACT: The distribution of genetic variation within and among 20 European sites infested by the large pine weevil, Hylobius abietis, was analysed using dominant amplified fragment length polymorphism markers. Analysis of molecular variance was performed at the European, regional and local scales. Most of the genetic variability was found within rather than among populations and the global fixation index averaged over loci was low (0.07). We found no evidence of genetic drift, even in relatively isolated sites. This genetic pattern tends to confirm the high dispersal ability of the weevil and the influence of human-mediated expansion of its range through conifer plantations across Europe since the 19th century. Assignment tests demonstrated that the regional forest is a pertinent geographic scale for defining populations in the large pine weevil. Testing the potential influence of the larval host-plant identity (Scot Pine vs Norway Spruce) on the genetic structure revealed a weak but significant effect in two of the three regions tested (in Ardèche and in Limousin but not in Finland). One locus varied with host-plant use in the two French regions, indicating a potential role in host-plant adaptation. However, host-race formation is not observed in H. abietis; we discuss this result in the light of our current knowledge of this insect's biology. Altogether, this study shows that the use of different host plants for development does not constitute a strong barrier to gene flow for H. abietis and confirms the high dispersal ability of this forest pest.Heredity 08/2006; 97(1):46-55. · 4.11 Impact Factor