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Prediction of Pollen-Mediated Gene Flow Between Fields of Red Clover (Trifolium pratense)

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Abstract

Pollen-mediated gene flow between red clover fields by bumblebees is predicted by estimating or simulating the parameters in a gene flow model for insect-pollinated crops. Generally, the predicted level of gene flow was found to depend on the visiting bee species and the spatial arrangement of the red clover fields. When the fields are close to each other, the gene flow depends mainly on the typical foraging distance of the visiting bee species, but when the fields are far apart, the gene flow between red clover fields is more sensitive to the distances between red clover fields than to the actual bumblebee species that pollinates the fields. Using the suggested methodology, the gene flow may be predicted in different agricultural scenarios. For example, if the gene flow between red clover fields is mediated by Bombus terrestris and the red clover fields that were assumed to be quadrates with sides of 100 m are separated by 200 m, then the median gene flow is predicted to be 0.17%.

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Acknowledgement

Thanks to Anne Marie Plejdrup for her dedicated work with the bees and Tommy Silberg for helping with the electrophoresis. J.L.O. at Rothamsted receives grant-aided support from the Biotechnology and Biological Sciences Research Council of the UK. Thanks to Martin Hoyle and an anonymous reviewer for valuable comments on a previous version of the manuscript.

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Authors and Affiliations

  1. Department of Terrestrial Ecology, DMU, Vejlsøvej 25, 8600, Silkeborg, Denmark

    Christian Damgaard & Vibeke Simonsen

  2. Centre for Soils and Ecosystem Function, Department of Plant and Invertebrate Ecology Division, Rothamsted Research, Harpenden, Herts, AL5 2JQ, UK

    Juliet L. Osborne

Authors
  1. Christian Damgaard
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  2. Vibeke Simonsen
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  3. Juliet L. Osborne
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Correspondence to Christian Damgaard.

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Damgaard, C., Simonsen, V. & Osborne, J.L. Prediction of Pollen-Mediated Gene Flow Between Fields of Red Clover (Trifolium pratense). Environ Model Assess 13, 483–490 (2008). https://doi.org/10.1007/s10666-007-9112-8

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  • DOI: https://doi.org/10.1007/s10666-007-9112-8

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