Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-25T23:31:31.176Z Has data issue: false hasContentIssue false

Geographical variation, population structure and gene flow between populations of Chrysophtharta agricola (Coleoptera: Chrysomelidae), a pest of Australian eucalypt plantations

Published online by Cambridge University Press:  09 March 2007

H.F. Nahrung*
Affiliation:
CRC for Sustainable Production Forestry, GPO Box 252-12, Hobart,Tasmania 7001, Australia; and School of Agricultural Science, The University of Tasmania, GPO Box 252-54, Hobart, Tasmania 7001, Tasmania
G.R. Allen
Affiliation:
CRC for Sustainable Production Forestry, GPO Box 252-12, Hobart,Tasmania 7001, Australia; and School of Agricultural Science, The University of Tasmania, GPO Box 252-54, Hobart, Tasmania 7001, Tasmania
*
*Fax: 61 3 6226 7942 E-mail: [email protected]

Abstract

Chrysophtharta agricola (Chapuis) is a pest of commercial eucalypt plantations in Tasmania and Victoria. Vagility of pest populations may result in difficulty predicting temporal and spatial pest outbreaks, and influence genetic resistance to chemical control. Gene flow in this pest species was estimated to assess predicability of attack, the potential efficacy of natural enemies, and the likelihood of resistance build-up. Ten geographic populations of C. agricola (six from Tasmania, one from the Australian Capital Territory, one from New South Wales and two from Victoria) were examined for genetic variation and gene flow using cellulose acetate allozyme electrophoresis. Six enzyme systems (PGI, PGD, PGM, IDH, HEX and MPI) were consistently polymorphic and scorable and were used to quantify estimated gene flow between populations. FST values and analysis of molecular variance indicated that gene flow was restricted between populations. Chrysophtharta agricola exhibited high levels of heterozygosity, probably because of high allelic diversity, and because all loci examined were polymorphic. The southern-most population was the most genetically different to other Tasmanian populations, and may also have been the most recently colonized. Limited gene flow implies that outbreaks of C. agricola should be spatially predictable and populations susceptible to control by natural enemies. Our results also imply that genetic resistance to chemical control may occur under frequent application of insecticide. However, testing population movement between plantations and native forest also needs to be conducted to assess gene flow between forest types.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2003

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Avise, J.C. (2000) Phylogeography: the history and formation of species. CambridgeHarvard University Press.CrossRefGoogle Scholar
Brooker, M.I.H. & Kleinig, D.A. (1999) In Field guide to eucalypts. Volume 1: South-eastern Australia. Hawthorn: Bloomings Books.Google Scholar
Clarke, A.R., Zalucki, M.P., Madden, J.L., Patel, V.S. & Paterson, S.C. (1997) Local dispersion of the Eucalyptus leaf-beetle, Chrysophtharta bimaculata (Coleoptera: Chrysomelidae), and implications for forest protection. Journal of Applied Ecology 34, 807817.Google Scholar
Collett, N. (2001) In Insect pests of young eucalypt plantations. Heidelberg: Department of Natural Resources and Environment.Google Scholar
Congdon, B.C., Lange, C.L. & Clarke, A.R. (1997) Geographic variation and gene flow in the eucalyptus defoliating beetle Chrysophtharta bimaculata (Coleoptera: Chrysomelidae). Journal of Applied Ecology 34, 12871292.CrossRefGoogle Scholar
Costa, J.T. (1998) Social behaviour and its effects on colony- and microgeographic genetic structure in phytophagous insect populations. In structure and local adaptation in natural insect populations – effects of ecology, life history and behaviour. pp 204238. [Mopper, S. and Strauss, S.Y., editors]. New York: Chapman and Hall.Google Scholar
Cranston, P.S. & Naumann, I.D. (1991) Biogeography. In The insects of Australia. pp 180197. Canberra: CSIRO Publishing.Google Scholar
Daly, J.C. (1989) The use of electrophoretic data in a study of gene flow in the pest species Heliothis armigera (Hubner) and H. punctigera Wallengren (Lepidoptera: Noctuidae). pp. 115141. in Loxdale, H.D. and Hollander, J.D., (Eds) Electrophoretic studies on agricultural pests. Oxford, Clarendon Press.Google Scholar
de Little, D.W. (1979) Taxonomic and ecological studies of the Tasmanian Eucalyptus-defoliating paropsids. PhD thesis: The University of Tasmania.Google Scholar
de Little, D.W. (1989) Paropsine chrysomelid attack on plantations of Eucalyptus nitens in Tasmania. New Zealand Journal of Forestry Science 19, 223227.Google Scholar
Drake, V.A., Helm, K.F. & Readshaw, J.L. (1981) Insect migration across Bass Strait during spring: a radar study. Bulletin of Entomological Research 71, 449466.Google Scholar
Elliott, H.J., Ohmart, C.P. & Wylie, F R. (1998) In Insect pests of Australian forests: ecology and management. Melbourne: Inkata Press.Google Scholar
Excoffier, L., Smouse, P.E. & Quattro, J.M. (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction sites. Genetics 131, 479491.CrossRefGoogle Scholar
Giles, B.E. & Goudet, J. (1997) Genetic differentiation in Silene dioica metapopulations: estimation of spatiotemporal effects in a successional plant species. American Naturalist 149, 507526.Google Scholar
Haldane, J.B.S. (1930) A mathematical theory of natural and artificial selection. Proceedings of the Cambridge Philosophical Society 26, 220230.Google Scholar
Hebert, P.D.N. & Beaton, M.J. (1989) In Methodologies for allozyme analysis using cellulose acetate electrophoresis: a practical handbook. Windsor, Ontario: Helena Laboratories.Google Scholar
Howlett, B.G. (2000) In Oviposition site selection by the eucalypt herbivore Chrysophtharta bimaculata (Olivier) (Coleoptera: Chrysomelidae) and the implications for larval establishment. PhD thesis: The University of Tasmania.Google Scholar
Howlett, B.G., Clarke, A.R. & Madden, J.L. (2001) The influence of leaf age on the oviposition preference of Chrysophtharta bimaculata (Olivier) and the establishment of neonates. Agricultural and Forest Entomology 3, 121127.CrossRefGoogle Scholar
Hsiao, T.H. (1989) Estimation of genetic variability amongst Coleoptera. In Electrophoretic studies on agricultural pests. pp 143180. [Loxdale, H.D. and Hollander, J.D., editors]. Oxford: Clarendon Press.Google Scholar
Knoll, S., Rowell-Rahier, M., Mardulyn, P. & Pasteels, J.M. (1996) Spatial genetic structure of leaf beetle species with special emphasis on alpine populations. In Chrysomelidae Biology, volume 1: the classification, phylogeny and genetics. pp 379388. [Jolivet, P.H.A. and Cox, M.L., editors]. Amsterdam: SPB Academic Publishers.Google Scholar
Lewis, P.O. & Zaykin, D. (2001) In Genetic Data Analysis: computer program for the analysis of allelic data. Version 1.0 (d16c). Free program distributed by the authors over the internet from http://lewis.eeb.ucom.edu/lewishome/software.html.Google Scholar
McCauley, D.E. (1993) Evolution in metapopulations with frequent local extinction and recolonisation. Oxford Surveys in Evolutionary Biology 9, 109134.Google Scholar
Mopper, S. (1996) Adaptive genetic structure in phytophagous insect populations. Trends in Ecology and Evolution 11, 235238.Google Scholar
Nahrung, H.F. & Allen, G.R. (in press) Intra-plant host selection, oviposition preference and larval survival of Chrysophtharta agricola (Chapuis) (Coleoptera: Chrysomelidae: Paropsini) between foliage types of a heterophyllous host. Agricultural and Forest Entomology.Google Scholar
Nei, M. (1972) Genetic distance between populations. American Naturalist 106, 283292.Google Scholar
Peakall, R. & Smouse, P.E. (2001) In GenAlEx Version 5: genetic analysis in Excel: population genetic software for teaching and research. Australian National University, Canberra: Australia.Google Scholar
Peterson, M.A. & Denno, R.F. (1998) Life history strategies and the genetic structure of phytophagous insect populations. In Genetic structure and local adaptation in natural insect populations: effects of ecology, life history, and behaviour. pp 253322. [Mopper, S. and Strauss, S.Y., editors]. New York: Chapman and Hall.Google Scholar
Rank, N.E. (1992) A hierarchical analysis of genetic differentiation in a montane leaf beetle Chrysomela aeneicollis (Coleoptera: Chrysomelidae). Evolution 46, 10971111.Google Scholar
Richardson, B.J., Baverstock, P.R. & Adams, M. (1986) In Allozyme electrophoresis: a handbook for animal systematics and population studies. Sydney: Academic Press.Google Scholar
Rowell-Rahier, M. (1992) Genetic structure of leaf-beetle populations: microgeographic and sexual differentiation in Oreina cacaliae and O. speciosissima. Entomologia Experimentalis et Applicata 65, 247257.Google Scholar
Wade, M.J. & McCauley, D.E. (1988) Extinction and recolonisation: their effects on the genetic differentiation of local populations. Evolution 42, 9951005.Google Scholar
Wright, S. (1931) Evolution in Mendelian populations. Genetics 16, 97159.Google Scholar