Wildlife Research Wildlife Research Society
Ecology, management and conservation in natural and modified habitats
REVIEW

Population genetic tools for pest management: a review

Lee Ann Rollins A C , Andrew P. Woolnough B and William B. Sherwin A
+ Author Affiliations
- Author Affiliations

A University of New South Wales, School of Biological, Earth and Environmental Science, Sydney, NSW 2052, Australia.

B Vertebrate Pest Research Section, Department of Agriculture and Food, 100 Bougainvillea Avenue, Forrestfield, WA 6058, Australia.

C Corresponding author. Email: l.rollins@unsw.edu.au

Wildlife Research 33(4) 251-261 https://doi.org/10.1071/WR05106
Submitted: 18 November 2005  Accepted: 4 May 2006   Published: 27 June 2006

Abstract

Population genetic tools have the potential to answer key questions in pest management including quantifying the number of genetically distinct populations represented in an invasion, the number of individuals present, whether populations are expanding or contracting, identifying the origin of invasive individuals, the number of separate introduction events that have occurred and in which order, and the rate that individuals are moving between populations. Genetic methods have only recently gained sufficient resolution to address these questions due to advances in laboratory techniques coupled with an increase in computational power. In combination, these methods may lead to a more comprehensive understanding of the dynamics of invasions. The expansion of the European starling (Sturnus vulgaris) into Western Australia is used as an applied example of how genetic methods can be integrated to provide vital information to improve pest-management strategies. Invasion events also may provide a unique opportunity to test some of these methodologies.


Acknowledgments

We thank Anna Lindholm, Ron Sinclair, Peter Spencer, Peter Thomson, Duncan Sutherland, John Benzie, Merel Dalebout, Clare Holleley and an anonymous reviewer for helpful comments on earlier drafts. We also thank Camilla Myers for inviting this review. This work was funded by an Australian Research Council Linkage Grant number LP0455776 (University of New South Wales, Department of Agriculture and Food Western Australia and the Department of Water, Land & Biodiversity Conservation South Australia).


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Appendix 1.  Associated software
Most of these programs are capable of performing tasks additional to those listed. References listed in the second column refer to theoretical background. Web addresses valid April 2006
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