Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-10T09:14:01.924Z Has data issue: false hasContentIssue false
  • English
  • Français

Landscape composition modulates population genetic structure of Eriosoma lanigerum (Hausmann) on Malus domestica Borkh in central Chile

Published online by Cambridge University Press:  24 October 2008

B. Lavandero ,
M. Miranda ,
C.C. Ramírez  and
E. Fuentes-Contreras
B. Lavandero*
Affiliation:
Instituto de Biología y Biotecnología Vegetal, Universidad de Talca, 2 Norte 685, Casilla 747, Talca, Chile
M. Miranda
Affiliation:
Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Macul, Santiago, Chile
C.C. Ramírez
Affiliation:
Instituto de Biología y Biotecnología Vegetal, Universidad de Talca, 2 Norte 685, Casilla 747, Talca, Chile
E. Fuentes-Contreras
Affiliation:
Departamento de Producción Agrícola, Facultad de Ciencias Agrarias, Universidad de Talca, 2 Norte 685, Casilla 747, Talca, Chile
*
*Author for correspondence Fax: +56-71200276 E-mail: blavandero@utalca.cl
Get access Rights & Permissions [Opens in a new window]

Abstract

Landscape genetics have been particularly relevant when assessing the influence of landscape characteristics on the genetic variability and the identification of barriers to gene flow. Linking current practices of area-wide pest management information on pest population genetics and geographical barriers would increase the efficiency of these programs. The woolly apple aphid, Eriosoma lanigerum (Hausmann), an important pest of apple orchards worldwide, was collected on apple trees (Malus domestica Borkh) from different locations in a 400 km north-south transect trough central Chile. In order to determine if there was population structure, diversity and flow were assessed. A total of 215 individuals from these locations were analysed using Inter Simple Sequence Repeat (ISSR) markers. Four ISSR primers generated a total of 114 polymorphic loci. The percentage of molecular variation among locations was 18%. As the algorithm used by structure may be poorly suited for inferring the number of genetic clusters in a data set that has an IBD relationship, the number of genetic clusters in the samples was also analyzed using a Bayesian clustering method implemented in software Baps version 4.14. We inferred the presence of four genetic clusters in the study region. Clustering of individuals followed a pattern explained by some geographical barriers. Using partial Mantel tests, we detected barriers to gene flow other than distance, created by a combination of main rivers and mountains. Although landscape genetics are rarely used in pest management, our results suggest that these tools may be suitable for the design of area-wide pest management programs.

Keywords

Eriosoma lanigerumgenetic structurebarriers to gene flowpestisolation-by-distance
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 99 , Issue 1 , February 2009 , pp. 97 - 105
Copyright
Copyright © 2008 Cambridge University Press

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

Abbot, P. (2001) Individual and population variation in invertebrates revealed by Inter-simple Sequence Repeats (ISSRs). Journal of Insect Science 1, 3pp. Available online at http://www.insectscience.org/1.8/.CrossRefGoogle ScholarPubMed
Artigas, J.N. (1994) Entomología Económica. 943 pp. Concepción, Chile, Universidad de Concepción.Google Scholar
Asante, S.K., Danthanarayana, W. & Cairns, S.C. (1993) Spatial and temporal distribution patterns of Eriosoma lanigerum (Homoptera: Aphididae) on apple. Environmental Entomology 22, 1060–1065.CrossRefGoogle Scholar
Beckler, A.A., French, B.W. & Chandler, L.D. (2005) Using GIS in areawide pest management: a case study in South Dakota. Transactions in GIS 9, 109–127.CrossRefGoogle Scholar
Behura, S.K. (2006) Molecular marker systems in insects: current trends and future avenues. Molecular Ecology 15, 3087–3113.CrossRefGoogle ScholarPubMed
Blackman, R.L. & Eastop, V.F. (1994) Aphids on the World's Trees. An Identification and Information Guide. 987 pp. Wallingford, UK, CAB International.CrossRefGoogle Scholar
Blommers, L.H.M. (1994) Integrated pest-management in European apple orchards. Annual Review of Entomology 39, 213–241.CrossRefGoogle Scholar
Bolstad, W.M. (2004) Introduction to Bayesian Statistics. New Jersey, USA, John Wiley & Sons, Inc.CrossRefGoogle Scholar
Bonnet, E. & Van de Peer, Y. (2002) zt: a software tool for simple and partial Mantel tests. Journal of Statistical Software 7, 1–12.CrossRefGoogle Scholar
Bossart, J.L. & Prowell, D.P. (1998) Genetic estimates of population structure and gene flow: limitations, lessons and new directions. Trends in Ecology & Evolution 13, 202–206.CrossRefGoogle ScholarPubMed
Calkins, C.O. & Faust, R.J. (2003) Overview of areawide programs and the program for suppression of codling moth in the western USA directed by the United States Department of Agriculture – Agricultural Research Service. Pest Management Science 59, 601–604.CrossRefGoogle ScholarPubMed
Carrière, Y., Dutilleul, P., Ellers-Kirk, C., Pedersen, B., Haller, S., Antilla, L., Dennehy, T.J. & Tabashnik, B.E. (2004) Sources, sinks, and the zone of influence of refuges for managing insect resistance to Bt crops. Ecological Applications 14, 1615–1623.CrossRefGoogle Scholar
Corander, J., Waldmann, P. & Sillanpaa, M.J. (2003) Bayesian analysis of genetic differentiation between populations. Genetics 163, 367–374.CrossRefGoogle ScholarPubMed
Corander, J., Marttinen, P., Sirén, J. & Tang, J. (2006) BAPS: Bayesian Analysis of Population Structure, manual v. 4.1. Available at http://www.rni.helsinki.fi/~jic/bapspage.html.Google Scholar
Darvill, B., Ellis, J.S., Lye, G.C. & Goulson, D. (2006) Population structure and inbreeding in a rare and declining bumblebee, Bombus muscorum (Hymenoptera: Apidae). Molecular Ecology 15, 601–611.CrossRefGoogle Scholar
DGA (1998) Cuencas hidrográficas en Chile: diagnóstico y proyectos, Santiago, Chile.Google Scholar
Evanno, G., Regnaut, S. & Goudet, J. (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14, 2611–2620.CrossRefGoogle ScholarPubMed
Excoffier, L., Laval, G. & Schneider, S. (2005) Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online 1, 47–50.Google Scholar
Frantz, A.C., Pourtois, J.T., Heuertz, M., Schley, L., Flamand, M.C., Krier, A., Bertouille, S., Chaumont, F. & Burke, T. (2006) Genetic structure and assignment tests demonstrate illegal translocation of red deer (Cervus elaphus) into a continuous population. Molecular Ecology 15, 3191–3203.CrossRefGoogle Scholar
Gao, J.M., Zhang, S.G., Qi, L.W., Zhang, Y., Wang, C.G. & Song, W.Q. (2006) ISSR and AFLP identification and genetic relationships of Chinese elite accessions from the genus Populus. Annals of Forest Science 63, 499–506.Google Scholar
Gwynne, R.N. (1999) Globalisation, commodity chains and fruit exporting regions in Chile. Tijdschrift Voor Economische en Sociale Geografie 90, 211–225.CrossRefGoogle Scholar
Hales, D.F., Tomiuk, J., Wohrmann, K. & Sunnucks, P. (1997) Evolutionary and genetic aspects of aphid biology: a review. European Journal of Entomology 94, 1–55.Google Scholar
Halkett, F., Simon, J.C. & Balloux, F. (2005) Tackling the population genetics of clonal and partially clonal organisms. Trends in Ecology & Evolution 20, 194–201.CrossRefGoogle ScholarPubMed
Herrmann, F., Westphal, C., Moritz, R.F.A. & Steffan-Dewenter, I. (2007) Genetic diversity and mass resources promote colony size and forager densities of a social bee (Bombus pascuorum) in agricultural landscapes. Molecular Ecology 16, 1167–1178.CrossRefGoogle ScholarPubMed
Insightful, C. (2001) S-PLUS 6 for Windows Guide to Statistics, Seattle, WA, USA.Google Scholar
Loxdale, H.D. & Lushai, G. (1999) Slaves of the environment: the movement of herbivorous insects in relation to their ecology and genotype. Philosophical Transactions of the Royal Society of London Series B: Biological Sciences 354, 1479–1495.CrossRefGoogle Scholar
Maguire, T.L., Peakall, R. & Saenger, P. (2002) Comparative analysis of genetic diversity in the mangrove species Avicennia marina (Forsk.) Vierh. (Avicenniaceae) detected by AFLPs and SSRs. Theoretical and Applied Genetics 104, 388–398.CrossRefGoogle ScholarPubMed
Nei, M. (1973) Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences of the United States of America 70, 3321–3323.CrossRefGoogle ScholarPubMed
Nei, M. & Li, W.H. (1979) Mathematical model for studying genetic variation in term of restriction endonuclease. Proceedings of the National Academy of Sciences of the United States of America 76, 5269–5273.CrossRefGoogle Scholar
Nybom, H. (2004) Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Molecular Ecology 13, 1143–1155.CrossRefGoogle ScholarPubMed
Park, Y.L., Perring, T.M., Farrar, C.A. & Gispert, C. (2006) Spatial and temporal distributions of two sympatric Homalodisca spp. (Hemiptera: Cicadellidae): Implications for areawide pest management. Agriculture Ecosystems & Environment 113, 168–174.CrossRefGoogle Scholar
Parry, H.R., Evans, A.J. & Morgan, D. (2006) Aphid population response to agricultural landscape change: A spatially explicit, indlividual-based model. Ecological Modelling 199, 451–463.CrossRefGoogle Scholar
Peakall, R. & Smouse, P.E. (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6, 288–295.CrossRefGoogle Scholar
Pearse, D.E. & Crandall, K.A. (2005) Beyond F ST: Analysis of population genetic data for conservation. Conservation Genetics 5, 585–602.CrossRefGoogle Scholar
Pritchard, J. & Wen, W. (2003) Documentation for STRUCTURE software: version 2. Available at http://pritch.bsd.uchicago.edu.Google Scholar
Pritchard, J.K., Stephens, M. & Donnelly, P. (2000) Inference of population structure using multilocus genotype data. Genetics 155, 945–959.CrossRefGoogle ScholarPubMed
Sandanayaka, W.R.M. & Bus, V.G.M. (2005) Evidence of sexual reproduction of woolly apple aphid, Eriosoma lanigerum, in New Zealand. Journal of Insect Science 5, 7pp. Available online at http://www.insectscience.org/5.27/.CrossRefGoogle ScholarPubMed
Sander, A.C., Purtauf, T., Holzhauer, S.I.J. & Wolters, V. (2006a) Landscape effects on the genetic structure of the ground beetle Poecilus versicolor Sturm 1824. Biodiversity and Conservation 15, 245–259.CrossRefGoogle Scholar
Sander, A.C., Purtauf, T., Wolters, V. & Dauber, J. (2006b) Landscape genetics of the widespread ground-beetle Carabus auratus in an agricultural region. Basic and Applied Ecology 7, 555–564.CrossRefGoogle Scholar
Santibáñez, F. (1993) Atlas agroclimático de Chile: regiones sexta, séptima, octava y novena. Santiago, Chile, Ministerio de Agricultura, Fondo de Investigación Agropecuaria.Google Scholar
Solervicens, J. (1995) Consideraciones generales sobre los insectos, el estado de su conocimiento y las colecciones. pp. 198–210in Simonetti, J., Arroyo, M., Spotorno, A. & Lozada, E. (Eds) Diversidad Biológica de Chile. Santiago, Chile, Comisión Nacional de Ciencia y Tecnología.Google Scholar
Storfer, A., Murphy, M.A., Evans, J.S., Goldberg, C.S., Robinson, S., Spear, S.F., Dezzani, R., Delmelle, E., Vierling, L. & Waits, L.P. (2007) Putting the ‘landscape’ in landscape genetics. Heredity 98, 128–142.CrossRefGoogle ScholarPubMed
Sunnucks, P. & Hales, D. (1996) Numerous transposed sequences of mitochondrial cytochrome oxidase I–II in aphids of the genus Sitobion (Hemiptera: Aphididae). Molecular Biology and Evolution 13, 510–524.CrossRefGoogle ScholarPubMed
Timm, A.E., Pringle, K.L. & Warnich, L. (2005) Genetic diversity of woolly apple aphid Eriosoma lanigerum (Hemiptera: Aphididae) populations in the Western Cape, South Africa. Bulletin of Entomological Research 95, 187–191.CrossRefGoogle ScholarPubMed
Vandergast, A.G., Bohonak, A.J., Weissman, D.B. & Fisher, R.N. (2007) Understanding the genetic effects of recent habitat fragmentation in the context of evolutionary history: phylogeography and landscape genetics of a southern California endemic Jerusalem cricket (Orthoptera: Stenopelmatidae: Stenopelmatus). Molecular Ecology 16, 977–992.CrossRefGoogle ScholarPubMed
Vialatte, A., Dedryver, C.A., Simon, J.C., Galman, M. & Plantegenest, M. (2005) Limited genetic exchanges between populations of an insect pest living on uncultivated and related cultivated host plants. Proceedings of the Royal Society B: Biological Sciences 272, 1075–1082.CrossRefGoogle ScholarPubMed
Westbrook, J.K. & Isard, S.A. (1999) Atmospheric scales of biotic dispersal. Agricultural and Forest Meteorology 97, 263–274.CrossRefGoogle Scholar
Wolfe, A.D., Xiang, Q.Y. & Kephart, S.R. (1998) Assessing hybridization in natural populations of Penstemon (Scrophulariaceae) using hypervariable intersimple sequence repeat (ISSR) bands. Molecular Ecology 7, 1107–1125.CrossRefGoogle ScholarPubMed
Zhu, M., Radcliffe, E.B., Ragsdale, D.W., MacRae, I.V. & Seeley, M.W. (2006) Low-level jet streams associated with spring aphid migration and current season spread of potato viruses in the US northern Great Plains. Agricultural and Forest Meteorology 138, 192–202.CrossRefGoogle Scholar
Zietkiewicz, E., Rafalski, A. & Labuda, D. (1994) Genome fingerprinting by simple sequence repeat (Ssr)-anchored polymerase chain-reaction amplification. Genomics 20, 176–183.CrossRefGoogle ScholarPubMed