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European bridgehead effect in the worldwide invasion of the obscure mealybug

  • Margarita C. G. Correa
  • Ferran Palero
  • Thibaut Malausa
  • Didier Crochard
  • Tania Zaviezo
  • Eric Lombaert
Original Paper
  • 55 Downloads

Abstract

Identifying the main routes followed by an invasive species has significant management implications and may help to understand its colonization process. The obscure mealybug, Pseudococcus viburni (Signoret, 1875), is an important agricultural pest native to South America that infests fruit crops worldwide. The genetic diversity and structure of P. viburni samples collected around the globe was investigated here, and the most likely invasion routes were inferred using state-of-the-art population genetics methods. The results obtained include: (1) identification of low intrapopulation genetic diversity (mean number of alleles per locus below 4 and heterozygosity below 50%) and high genetic differentiation among populations (average FST = 0.29); (2) strong evidence of an initial colonization from South America towards Europe and secondary introductions from Europe towards other continents, (3) evidence of population structure within Europe and, (4) support for introductions from North America and Europe to South Africa. These results improve our understanding of the worldwide distribution and invasion pathways of P. viburni and suggest further exploring South America as the best source for potential biological control agents.

Keywords

Biological invasion Agricultural pest Likelihood assignment Microsatellites ABC methods 

Notes

Acknowledgements

Thanks are due to the reviewers for useful suggestions that helped us to improve significantly the manuscript. We would like to thank M. Botton, J. Charles, B. Kaydan, V. Pacheco, M. Sandanayaka and G. Watson for sending us P. viburni samples. We also thank E. Poulin (Universidad de Chile) and E. Fuentes-Contreras (Universidad de Talca) for comments on a previous version of this manuscript. MCG Correa received financial support from Chile CONICYT Doctoral fellowship #21110864 and CONICYT “Tesis en la Industria” #7812110011 and Fondecyt #1170943. This research was also funded by the European Union (FP7 grants KBBE “PURE” #265865, Marie-Curie IRSES “IPRABIO” #269196, and Marie-Curie IAPP “COLBICS” #324475), by the Grant CHALLENGEN (CTM2013-48163) from the Spanish Government and a post-doctoral contract funded by the Beatriu de Pinos Programme of the Generalitat de Catalunya (2014-BPB-00038).

Supplementary material

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Supplementary material 1 (PDF 1119 kb)

References

  1. Abd-Rabou S, Shalaby H, Germain J-F et al (2012) Identification of mealybug pest species (Hemiptera: Pseudococcidae) in Egypt and France, using a DNA barcoding approach. Bull Entomol Res 102:1–9.  https://doi.org/10.1017/S0007485312000041 CrossRefGoogle Scholar
  2. Bacon SJ, Aebi A, Calanca P, Bacher S (2014) Quarantine arthropod invasions in Europe: the role of climate, hosts and propagule pressure. Divers Distrib 20:84–94.  https://doi.org/10.1111/ddi.12149 CrossRefGoogle Scholar
  3. Bandelt H, Forster P, Röhl A (1999) Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol 16:37–48CrossRefPubMedGoogle Scholar
  4. Ben-Dov Y, Miller DR, Gibson GAP (2010) Scale net. http://www.sel.barc.usda.gov/scalenet/scalenet.htm. Accessed 30 Sept 2017
  5. Blackburn TM, Lockwood JL, Cassey P (2015) The influence of numbers on invasion success. Mol Ecol 24:1942–1953.  https://doi.org/10.1111/mec.13075 CrossRefPubMedGoogle Scholar
  6. Bock DG, Caseys C, Cousens RD et al (2015) What we still don’t know about invasion genetics. Mol Ecol 24:2277–2297.  https://doi.org/10.1111/mec.13032 CrossRefPubMedGoogle Scholar
  7. Boubou A, Migeon A, Roderick GK et al (2012) Test of colonisation scenarios reveals complex invasion history of the red tomato spider mite Tetranychus evansi. PLoS ONE 7:e35601.  https://doi.org/10.1371/journal.pone.0035601 CrossRefPubMedPubMedCentralGoogle Scholar
  8. Brain CK (1912) Contribution to the knowledge of mealy bugs, genus Pseudococcus in the vicinity of Cape Town, South Africa. Ann Entomol Soc Am 5:177–189CrossRefGoogle Scholar
  9. Carpio C, Curkovic T (2016) Monitoring of population dynamics of Pseudococcus viburni (Signoret)(Hemiptera: Pseudococcidae) during two seasons in a pomegranate (Punica granatum L.) orchard in Central Chile. Chil J Agric Anim Sci 32:117–126CrossRefGoogle Scholar
  10. Cavalli-Sforza L, Edwards A (1967) Phylogenetic analysis. Models and estimation procedures. Am J Hum Genet 19:233–257PubMedPubMedCentralGoogle Scholar
  11. Chapuis M-P, Estoup A (2007) Microsatellite null alleles and estimation of population differentiation. Mol Biol Evol 24:621–631.  https://doi.org/10.1093/molbev/msl191 CrossRefPubMedGoogle Scholar
  12. Charles JG (2011) Using parasitoids to infer a native range for the obscure mealybug, Pseudococcus viburni, in South America. Biocontrol 56:155–161.  https://doi.org/10.1007/s10526-010-9322-x CrossRefGoogle Scholar
  13. Chen Z (2011) Is the weighted z-test the best method for combining probabilities from independent tests? J Evol Biol 24:926–930.  https://doi.org/10.1111/j.1420-9101.2010.02226.x CrossRefPubMedGoogle Scholar
  14. Cornuet J-M, Ravigné V, Estoup A (2010) Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0). BMC Bioinform 11:401.  https://doi.org/10.1186/1471-2105-11-401 CrossRefGoogle Scholar
  15. Correa M, Aguirre C, Germain J et al (2011) A new species of Pseudococcus (Hemiptera: Pseudococcidae) belonging to the “Pseudococcus maritimus” complex from Chile: molecular and morphological description. Zootaxa 2926:46–54Google Scholar
  16. Correa M, Germain J-F, Malausa T, Zaviezo T (2012) Molecular and morphological characterization of mealybugs (Hemiptera: Pseudococcidae) from Chilean vineyards. Bull Entomol Res.  https://doi.org/10.1017/S0007485312000053 PubMedCrossRefGoogle Scholar
  17. Correa MCG, Zaviezo T, Le Maguet J et al (2014) Characterization of microsatellite DNA libraries from three mealybug species and development of microsatellite markers for Pseudococcus viburni (Hemiptera: Pseudococcidae). Bull Entomol Res 104:213–220.  https://doi.org/10.1017/S0007485313000667 CrossRefPubMedGoogle Scholar
  18. Correa MCG, Lombaert E, Malausa T et al (2015) Mealybug species from Chilean agricultural landscapes and main factors influencing the genetic structure of Pseudococcus viburni. Sci Rep 5:16483.  https://doi.org/10.1038/srep16483 CrossRefPubMedPubMedCentralGoogle Scholar
  19. Cristescu ME (2015) Genetic reconstructions of invasion history. Mol Ecol 24:2212–2225CrossRefPubMedGoogle Scholar
  20. Csilléry K, Blum MGB, Gaggiotti OE, François O (2010) Approximate Bayesian Computation (ABC) in practice. Trends Ecol Evol 25:410–418CrossRefPubMedGoogle Scholar
  21. Daane KM, Almeida RPP, Bell VA et al (2012) Biology and management of mealybugs in vineyards. In: Bostanian N, Vincent C, Isaacs R (eds) Arthropod management in vineyards: pests, approaches, and future directions. Springer, DordrechtGoogle Scholar
  22. Daane KM, Middleton MC, Sforza RFH et al (2018) Determining the geographic origin of invasive populations of the mealybug Planococcus ficus based on molecular genetic analysis. PLoS ONE 13:e0193852.  https://doi.org/10.1371/journal.pone.0193852 CrossRefPubMedPubMedCentralGoogle Scholar
  23. Dent E, VonHoldt B (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361CrossRefGoogle Scholar
  24. Dlugosch KM, Anderson SR, Braasch J et al (2015) The devil is in the details: genetic variation in introduced populations and its contributions to invasion. Mol Ecol 24:2095–2111.  https://doi.org/10.1111/mec.13183 CrossRefPubMedGoogle Scholar
  25. Downie DA (2005) Evidence for multiple origins of grape phylloxera (Daktulosphaira vitifoliae Fitch) (Hemiptera: Phylloxeridae) in South African vineyards. Afr Entomol 13:359–365Google Scholar
  26. Estoup A, Guillemaud T (2010) Reconstructing routes of invasion using genetic data: why, how and so what? Mol Ecol.  https://doi.org/10.1111/j.1365-294X.2010.04773.x PubMedCentralCrossRefPubMedGoogle Scholar
  27. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620.  https://doi.org/10.1111/j.1365-294X.2005.02553.x CrossRefPubMedGoogle Scholar
  28. Facon B, Genton BJ, Shykoff J et al (2006) A general eco-evolutionary framework for understanding bioinvasions. Trends Ecol Evol 21:130–135.  https://doi.org/10.1016/j.tree.2005.10.012 CrossRefPubMedGoogle Scholar
  29. Fraimout A, Debat V, Fellous S et al (2017) Deciphering the routes of invasion of Drosophila suzukii by means of ABC random forest. Mol Biol Evol 34:980–996.  https://doi.org/10.1093/molbev/msx050 PubMedPubMedCentralCrossRefGoogle Scholar
  30. Franco JC, Zada A, Mendel Z (2009) Novel approaches for the management of mealybug pests. In: Ishaaya I, Horowitz AR (eds) Biorational control of arthropod pests. Springer, Netherlands, p 408Google Scholar
  31. Gimpel WF, Miller DR (1996) Systematic analysis of the mealybugs in the Pseudococcus maritimus complex (Homoptera: Pseudococcidae). Contrib Entomol Int 2:1–163Google Scholar
  32. Goudet J (1995) FSTAT (version 1.2): a computer program to calculate F-statistics. J Hered 86:485–486CrossRefGoogle Scholar
  33. Grasswitz TR, James DG (2008) Movement of grape mealybug, Pseudococcus maritimus, on and between host plants. Entomol Exp Appl 129:268–275.  https://doi.org/10.1111/j.1570-7458.2008.00786.x CrossRefGoogle Scholar
  34. Guillemaud T, Beaumont MA, Ciosi M, Cornuet JM, Estoup A (2010) Inferring introduction routes of invasive species using approximate Bayesian computation on microsatellite data. Heredity 104(1):88–99.  https://doi.org/10.1038/hdy.2009.92 CrossRefGoogle Scholar
  35. Guillemaud T, Ciosi M, Lombaert E, Estoup A (2011) Biological invasions in agricultural settings: insights from evolutionary biology and population genetics. C R Biol 334:237–246.  https://doi.org/10.1016/j.crvi.2010.12.008 CrossRefPubMedGoogle Scholar
  36. Hall T (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser 41:95–98Google Scholar
  37. He Y, Liu Y, Zhan R et al (2014) The occurrence of two species of pineapple mealybugs (Dysmicoccus spp.) (Hemiptera: Pseudococcidae) in China and their genetic relationship based on rDNA ITS sequences. Caryologia 67:36–44.  https://doi.org/10.1080/00087114.2014.891698 CrossRefGoogle Scholar
  38. Jakobsson M, Rosenberg NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801–1806.  https://doi.org/10.1093/bioinformatics/btm233 CrossRefPubMedGoogle Scholar
  39. Jost L (2008) GST and its relatives do not measure differentiation. Mol Ecol 17:4015–4026.  https://doi.org/10.1111/j.1365-294X.2008.03887.x CrossRefPubMedGoogle Scholar
  40. Kass RE, Raftery AE (1995) Bayes factors. J Am Stat Assoc 90:773–795CrossRefGoogle Scholar
  41. Kerdelhué C, Boivin T, Burban C (2014) Contrasted invasion processes imprint the genetic structure of an invasive scale insect across southern Europe. Heredity (Edinb).  https://doi.org/10.1038/hdy.2014.39 CrossRefGoogle Scholar
  42. Kirk H, Dorn S, Mazzi D (2013) Worldwide population genetic structure of the oriental fruit moth (Grapholita molesta), a globally invasive pest. BMC Ecol 13:12.  https://doi.org/10.1186/1472-6785-13-12 CrossRefPubMedPubMedCentralGoogle Scholar
  43. Kopelman NM, Mayzel J, Jakobsson M et al (2015) Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resour 15:1179–1191.  https://doi.org/10.1111/1755-0998.12387 CrossRefPubMedPubMedCentralGoogle Scholar
  44. Librado P, Rozas J (2009) DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25:1451–1452.  https://doi.org/10.1093/bioinformatics/btp187 CrossRefPubMedGoogle Scholar
  45. Lombaert E, Guillemaud T, Cornuet J-M et al (2010) Bridgehead effect in the worldwide invasion of the biocontrol harlequin ladybird. PLoS ONE 5:e9743.  https://doi.org/10.1371/journal.pone.0009743 CrossRefPubMedPubMedCentralGoogle Scholar
  46. Lombaert E, Guillemaud T, Thomas CE et al (2011) Inferring the origin of populations introduced from a genetically structured native range by approximate Bayesian computation: case study of the invasive ladybird Harmonia axyridis. Mol Ecol 20:4654–4670.  https://doi.org/10.1111/j.1365-294X.2011.05322.x CrossRefPubMedGoogle Scholar
  47. Malausa T, Fenis A, Warot S et al (2011) DNA markers to disentangle complexes of cryptic taxa in mealybugs (Hemiptera: Pseudococcidae). J Appl Entomol 135:142–155.  https://doi.org/10.1111/j.1439-0418.2009.01495.x CrossRefGoogle Scholar
  48. Pacheco da Silva VC, Bertin A, Blin A, Germain J-F, Bernardi D, Rignol G, et al (2014) Molecular and morphological identification of mealybug species (Hemiptera: Pseudococcidae) in Brazilian vineyards. PLoS ONE 9(7):e103267.  https://doi.org/10.1371/journal.pone.0103267 CrossRefGoogle Scholar
  49. Palero F, Lopes J, Abellaó P et al (2009) Rapid radiation in spiny lobsters (Palinurus spp) as revealed by classic and ABC methods using mtDNA and microsatellite data. BMC Evol Biol.  https://doi.org/10.1186/1471-2148-9-263 PubMedPubMedCentralCrossRefGoogle Scholar
  50. Park D-S, Suh S-J, Hebert PDN et al (2011) DNA barcodes for two scale insect families, mealybugs (Hemiptera: Pseudococcidae) and armored scales (Hemiptera: Diaspididae). Bull Entomol Res 101:429–434.  https://doi.org/10.1017/S0007485310000714 CrossRefPubMedGoogle Scholar
  51. Pascual M, Chapuis MP, Mestres F et al (2007) Introduction history of Drosophila subobscura in the New World: a microsatellite-based survey using ABC methods. Mol Ecol 16:3069–3083.  https://doi.org/10.1111/j.1365-294X.2007.03336.x CrossRefPubMedGoogle Scholar
  52. Pastor-Satorras R, Vespignani A (2001) Epidemic spreading in scale-free networks. Phys Rev Lett 86:3200–3203CrossRefPubMedGoogle Scholar
  53. Piry S, Alapetite A, Cornuet J-M et al (2004) GENECLASS2: a software for genetic assignment and first-generation migrant detection. J Hered 95:536–539.  https://doi.org/10.1093/jhered/esh074 CrossRefPubMedGoogle Scholar
  54. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  55. Rannala B, Mountain JL (1997) Detecting immigration by using multilocus genotypes. Proc Natl Acad Sci 94:9197–9201.  https://doi.org/10.1073/pnas.94.17.9197 CrossRefPubMedGoogle Scholar
  56. Robert CP, Cornuet JM, Marin JM, Pillai NS (2011) Lack of confidence in approximate Bayesian computation model choice. Proc Natl Acad Sci 108:15112–15117CrossRefPubMedGoogle Scholar
  57. Rosenberg NA (2004) DISTRUCT: a program for the graphical display of population structure. Mol Ecol Notes 4:137–138.  https://doi.org/10.1046/j.1471-8286.2003.00566.x CrossRefGoogle Scholar
  58. Rousset F (2008) Genepop’007: a complete re-implementation of the genepop software for Windows and Linux. Mol Ecol Resour 8:103–106.  https://doi.org/10.1111/j.1471-8286.2007.01931.x CrossRefPubMedGoogle Scholar
  59. Rung A, Scheffer S, Evans G, Miller D (2008) Molecular identification of two closely related species of mealybugs of the genus Planococcus (Homoptera: Pseudococcidae). Ann Entomol Soc Am 101:525–532CrossRefGoogle Scholar
  60. Sax D, Stachowicz JJ, Gaines SD (2005) Species invasions: insights into ecology, evolution, and biogeography. Sinauer Associates, SunderlandGoogle Scholar
  61. Simberloff D (2009) The role of propagule pressure in biological invasions. Annu Rev Ecol Evol Syst 40:81–102.  https://doi.org/10.1146/annurev.ecolsys.110308.120304 CrossRefGoogle Scholar
  62. Sokal RR, Rohlf FJ (1995) Biometry: the principles and practice of statistics in biological research, 3rd edn. Freeman and Company, New YorkGoogle Scholar
  63. Tamura K, Stecher G, Peterson D et al (2013) MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol 30:2725–2729.  https://doi.org/10.1093/molbev/mst197 CrossRefPubMedPubMedCentralGoogle Scholar
  64. Unwin T (2005) Wine and the vine: an historical geography of viticulture and the wine trade. Taylor & Francis, New YorkGoogle Scholar
  65. Walton VM, Daane KM, Pringle KL (2004) Monitoring Planococcus ficus in South African vineyards with sex pheromone-baited traps. Crop Prot 23:1089–1096.  https://doi.org/10.1016/j.cropro.2004.03.016 CrossRefGoogle Scholar
  66. Weir BS, Cockerham C (1984) Estimating F-statistics for the analysis of population structure. Evolution (N Y) 38:1358–1370Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Facultad de Agronomía e Ingeniería ForestalPontificia Universidad Católica de ChileSantiagoChile
  2. 2.INRA, CNRS, ISAUniversité Côte d’AzurSophia AntipolisFrance
  3. 3.Centre for Molecular and Functional Ecology in AgroecosystemsUniversidad de TalcaTalcaChile
  4. 4.Centre d’Estudis Avançats de Blanes (CEAB-CSIC)BlanesSpain

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