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      Genes in new environments: genetics and evolution in biological control.

      Nature reviews. Genetics
      Animals, Biological Evolution, Environment, Insect Control, Pest Control, Biological

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          Abstract

          The availability of new genetic technologies has positioned the field of biological control as a test bed for theories in evolutionary biology and for understanding practical aspects of the release of genetically manipulated material. Purposeful introductions of pathogens, parasites, predators and herbivores, when considered as replicated semi-natural field experiments, show the unpredictable nature of biological colonization. The characteristics of organisms and their environments that determine this variation in the establishment and success of biological control can now be explored using genetic tools. Lessons from studies of classical biological control can help inform researchers and policy makers about the risks that are associated with the release of genetically modified organisms, particularly with respect to long-term evolutionary changes.

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          Most cited references66

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          Environmental and Economic Costs of Nonindigenous Species in the United States

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            Gene flow and the geographic structure of natural populations.

            M Slatkin (1987)
            There is abundant geographic variation in both morphology and gene frequency in most species. The extent of geographic variation results from a balance of forces tending to produce local genetic differentiation and forces tending to produce genetic homogeneity. Mutation, genetic drift due to finite population size, and natural selection favoring adaptations to local environmental conditions will all lead to the genetic differentiation of local populations, and the movement of gametes, individuals, and even entire populations--collectively called gene flow--will oppose that differentiation. Gene flow may either constrain evolution by preventing adaptation to local conditions or promote evolution by spreading new genes and combinations of genes throughout a species' range. Several methods are available for estimating the amount of gene flow. Direct methods monitor ongoing gene flow, and indirect methods use spatial distributions of gene frequencies to infer past gene flow. Applications of these methods show that species differ widely in the gene flow that they experience. Of particular interest are those species for which direct methods indicate little current gene flow but indirect methods indicate much higher levels of gene flow in the recent past. Such species probably have undergone large-scale demographic changes relatively frequently.
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              Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach.

              A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source-sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.
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                Author and article information

                Journal
                14634636
                10.1038/nrg1201

                Chemistry
                Animals,Biological Evolution,Environment,Insect Control,Pest Control, Biological
                Chemistry
                Animals, Biological Evolution, Environment, Insect Control, Pest Control, Biological

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