Tree Genetics & Genomes

, Volume 8, Issue 4, pp 695–708 | Cite as

Estimating population boundaries using regional and local-scale spatial genetic structure: an example in Eucalyptus globulus

  • Suat Hui Yeoh
  • J. Charlie Bell
  • William J. Foley
  • Ian R. Wallis
  • Gavin F. Moran
Original Paper


Eucalyptus globulus Labill is a foundation tree species over its disjunct distribution in southeastern Australia. The quality of its pulp makes it the most important hardwood species in the world. The importance of E. globulus prompted the establishment of common gardens from seed collected across its geographic range. This enabled us to study the genetic structure of the species, its population boundaries, and gene flow using 444 trees from different open-pollinated families that were genotyped at 16 microsatellite loci. A Bayesian clustering method was used to resolve five genetically distinct groups across the geographical range. These groups were identified as regions, which varied in diameter from 38 to 294 km and contain 4 to 16 putative populations. For two of these regional groups, we used spatial autocorrelation analysis based on assignment of trees to their natural stands to examine gene flow within each region. Consistent significant local-scale spatial structure occurred in both regions. Pairs of individuals within a region showed significant genetic similarity that extended beyond 40 km, suggesting distant movement of pollen. This suggests that breeding populations in E. globulus are much bigger than traditionally accepted in eucalypts. Our results are important for the management of genetic diversity and breeding populations in E. globulus. Similar studies of a variety of eucalypts pollinated by insects and birds will determine whether the local-scale genetic structure of E. globulus is unusual.


Microsatellite Simple sequence repeats Genetic structure Population genetics Eucalyptus globulus 

Supplementary material

11295_2011_457_MOESM1_ESM.pdf (167 kb)
ESM 1(PDF 166 kb)
11295_2011_457_MOESM2_ESM.pdf (381 kb)
ESM 2(PDF 381 kb)


  1. Andrew RL, Peakall R, Wallis IR, Foley WJ (2007a) Spatial distribution of defense chemicals and markers and the maintenance of chemical variation. Ecology 88:716–728PubMedCrossRefGoogle Scholar
  2. Andrew RL, Wallis IR, Harwood CE, Henson M, Foley WJ (2007b) Heritable variation in the foliar secondary metabolite sideroxylonal in Eucalyptus confers cross-resistance to herbivores. Oecologia 153:891–901PubMedCrossRefGoogle Scholar
  3. Barbour RC, O’Reilly-Wapstra JM, De Little DW, Jordan GJ, Steane DA, Humphreys JR, Bailey JK, Whitham TG, Potts BM (2009) A geographic mosaic of genetic variation within a foundation tree species and its community-level consequences. Ecology 90:1762–1772PubMedCrossRefGoogle Scholar
  4. Beck NR, Peakall R, Heinsohn R (2008) Social constraint and an absence of sex-biased dispersal drive fine-scale genetic structure in white-winged choughs. Mol Ecol 17:4346–4358PubMedCrossRefGoogle Scholar
  5. Brondani RPV, Brondani C, Tarchini R, Grattapaglia D (1998) Development, characterization and mapping of microsatellite markers in Eucalyptus grandis and E. urophylla. Theor Appl Genet 97:816–827CrossRefGoogle Scholar
  6. Butcher PA, Skinner AK, Gardiner CA (2005) Increased inbreeding and inter-species gene flow in remnant populations of the rare Eucalyptus benthamii. Conserv Genet 6:213–226CrossRefGoogle Scholar
  7. Butcher PA, McDonald MW, Bell JC (2009) Congruence between environmental parameters, morphology and genetic structure in Australia’s most widely distributed eucalypt, Eucalyptus camaldulensis. Tree Genet Genomes 5:189–210CrossRefGoogle Scholar
  8. Cann JH, Belperio AP, Gostin VA, Murraywallace CV (1988) Sea-level history, 45 000 to 30 000 yr BP inferred from benthic foraminifera, Gulf St Vincent, South Australia. Quat Res 29:153–175CrossRefGoogle Scholar
  9. Dutkowski GW, Potts BM (1999) Geographic patterns of genetic variation in Eucalyptus globulus ssp globulus and a revised racial classification. Aust J Bot 47:237–263CrossRefGoogle Scholar
  10. Earl DA (2011) Structure harvester v0.6.1 Available at
  11. Epperson BK (2005) Estimating dispersal from short distance spatial autocorrelation. Heredity 95:7–15PubMedCrossRefGoogle Scholar
  12. Epperson BK (2007) Plant dispersal, neighbourhood size and isolation by distance. Mol Ecol 16:3854–3865PubMedCrossRefGoogle Scholar
  13. Escudero A, Iriondo JM, Torres ME (2003) Spatial analysis of genetic diversity as a tool for plant conservation. Biol Conserv 113:351–365CrossRefGoogle Scholar
  14. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620PubMedCrossRefGoogle Scholar
  15. Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587PubMedGoogle Scholar
  16. Ford J (1987) Minor isolates and minor geographical barriers in avian speciation in continental Australia. Emu 87:90–102CrossRefGoogle Scholar
  17. Frantz AC, Cellina S, Krier A, Schley L, Burke T (2009) Using spatial Bayesian methods to determine the genetic structure of a continuously distributed population: clusters or isolation by distance? J Appl Ecol 46:493–505CrossRefGoogle Scholar
  18. Freeman JS, Jackson HD, Steane DA, McKinnon GE, Dutkowski GW, Potts BM, Vaillancourt RE (2001) Chloroplast DNA phylogeography of Eucalyptus globulus. Aust J Bot 49:585–596CrossRefGoogle Scholar
  19. Gardiner C, Crawford D (1987, 1988) Seed collections of Eucalyptus globulus subsp. globulus for tree improvement purposes. Tree Seed Centre, CSIRO Division of Forest Research report, CanberraGoogle Scholar
  20. Glaubitz JC (2004) CONVERT: a user-friendly program to reformat diploid genotypic data for commonly used population genetic software packages. Mol Ecol Notes 4:309–310CrossRefGoogle Scholar
  21. Glaubitz JC, Emebiri LC, Moran GF (2001) Dinucleotide microsatellites from Eucalyptus sieberi: inheritance, diversity, and improved scoring of single-base differences. Genome 44:1041–1045PubMedGoogle Scholar
  22. Grattapaglia D, Kirst M (2008) Eucalyptus applied genomics: from gene sequences to breeding tools. New Phytol 179:911–929PubMedCrossRefGoogle Scholar
  23. Guillot G, Estoup A, Mortier F, Cosson JF (2005) A spatial statistical model for landscape genetics. Genetics 170:1261–1280PubMedCrossRefGoogle Scholar
  24. Hingston AB, Gartrell BD, Pinchbeck G (2004) How specialized is the plant–pollinator association between Eucalyptus globulus ssp globulus and the swift parrot Lathamus discolor? Austral Ecol 29:624–630CrossRefGoogle Scholar
  25. Jackson HD, Steane DA, Potts BM, Vaillancourt RE (1999) Chloroplast DNA evidence for reticulate evolution in Eucalyptus (Myrtaceae). Mol Ecol 8:739–751CrossRefGoogle Scholar
  26. Jones TH, Vaillancourt RE, Potts BM (2007) Detection and visualization of spatial genetic structure in continuous Eucalyptus globulus forest. Mol Ecol 16:697–707PubMedCrossRefGoogle Scholar
  27. Jordan GJ, Potts BM, Kirkpatrick JB, Gardiner C (1993) Variation in the Eucalyptus globulus complex revisited. Aust J Bot 41:763–785CrossRefGoogle Scholar
  28. Krauss SL, Koch JM (2004) Rapid genetic delineation of provenance for plant community restoration. J Appl Ecol 41:1162–1173CrossRefGoogle Scholar
  29. Krauss SL, Hermanutz L, Hopper SD, Coates DJ (2007) Population-size effects on seeds and seedlings from fragmented eucalypt populations: implications for seed sourcing for ecological restoration. Aust J Bot 55:390–399CrossRefGoogle Scholar
  30. Külheim C, Yeoh SH, Maintz J, Foley WJ, Moran GF (2009) Comparative SNP diversity among four Eucalyptus species for genes from secondary metabolite biosynthetic pathways. BMC Genomics 10:452PubMedCrossRefGoogle Scholar
  31. Külheim C, Yeoh SH, Wallis IR, Laffan S, Moran GF, Foley WJ (2011) The molecular basis of quantitative variation in foliar secondary metabolites in Eucalyptus globulus. New Phytol 191:1041–1053PubMedCrossRefGoogle Scholar
  32. Lewis PO, Zaykin D (2001) 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 Scholar
  33. Liu KJ, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129PubMedCrossRefGoogle Scholar
  34. Mac Nally R, Horrocks G (2000) Landscape-scale conservation of an endangered migrant: the swift parrot (Lathamus discolor) in its winter range. Biol Conserv 92:335–343CrossRefGoogle Scholar
  35. Marquardt PE, Epperson BK (2004) Spatial and population genetic structure of microsatellites in white pine. Mol Ecol 13:3305–3315PubMedCrossRefGoogle Scholar
  36. McKinnon GE, Potts BM, Steane DA, Vaillancourt RE (2005) Population and phylogenetic analysis of the cinnamoyl coA reductase gene in Eucalyptus globulus (Myrtaceae). Aust J Bot 53:827–838CrossRefGoogle Scholar
  37. McKinnon GE, Smith JJ, Potts BM (2010) Recurrent nuclear DNA introgression accompanies chloroplast DNA exchange between two eucalypt species. Mol Ecol 19:1367–1380PubMedCrossRefGoogle Scholar
  38. Nei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. J Mol Evol 19:153–170PubMedCrossRefGoogle Scholar
  39. Oosterhout CV, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4:535–538CrossRefGoogle Scholar
  40. Ottewell KM, Donnellan SC, Moran GF, Paton DC (2005) Multiplexed microsatellite markers for the genetic analysis of Eucalyptus leucoxylon (Myrtaceae) and their utility for ecological and breeding studies in other Eucalyptus species. J Hered 96:445–451PubMedCrossRefGoogle Scholar
  41. Peakall R, Smouse PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6:288–295CrossRefGoogle Scholar
  42. Peakall R, Smouse PE, Huff DR (1995) Evolutionary implications of allozyme and RAPD variation in diploid populations of dioecious buffalo grass Buchloe dactyloides. Mol Ecol 4:135–147CrossRefGoogle Scholar
  43. Peakall R, Ruibal M, Lindenmayer DB (2003) Spatial autocorrelation analysis offers new insights into gene flow in the Australian bush rat, Rattus fuscipes. Evolution 57:1182–1195PubMedGoogle Scholar
  44. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedGoogle Scholar
  45. Rambaut A (2008) FigTree v1.1.1. University of Edinburgh, EdinburghGoogle Scholar
  46. Slatkin M (1987) Gene flow and the geographic structure of natural populations. Science 236:787–792PubMedCrossRefGoogle Scholar
  47. Smouse PE, Peakall R (1999) Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity 82:561–573PubMedCrossRefGoogle Scholar
  48. Smouse PE, Peakall R, Gonzales E (2008) A heterogeneity test for fine-scale genetic structure. Mol Ecol 17:3389–3400PubMedCrossRefGoogle Scholar
  49. Steane DA, Conod N, Jones RC, Vaillancourt RE, Potts BM (2006) A comparative analysis of population structure of a forest tree, Eucalyptus globulus (Myrtaceae), using microsatellite markers and quantitative traits. Tree Genet Genomes 2:30–38CrossRefGoogle Scholar
  50. Steane DA, Nicolle D, Sansaloni CP, Petroli CD, Carling J, Kilian A, Myburg AA, Grattapaglia D, Vaillancourt RE (2011) Population genetic analysis and phylogeny reconstruction in Eucalyptus (Myrtaceae) using high-throughput, genome-wide genotyping. Mol Phylogenet Evol 59:206–224PubMedCrossRefGoogle Scholar
  51. Streiff R, Labbe T, Bacilieri R, Steinkellner H, Glossl J, Kremer A (1998) Within-population genetic structure in Quercus robur L. and Quercus petraea (Matt.) Liebl. assessed with isozymes and microsatellites. Mol Ecol 7:317–328CrossRefGoogle Scholar
  52. Thamarus KA, Groom K, Murrell J, Byrne M, Moran GF (2002) A genetic linkage map for Eucalyptus globulus with candidate loci for wood, fibre, and floral traits. Theor Appl Genet 104:379–387PubMedCrossRefGoogle Scholar
  53. Thumma BR, Southerton SG, Bell JC, Owen JV, Henery ML, Moran GF (2010) Quantitative trait locus (QTL) analysis of wood quality traits in Eucalyptus nitens. Tree Genet Genomes 6:305–317CrossRefGoogle Scholar
  54. Vekemans X, Hardy OJ (2004) New insights from fine-scale spatial genetic structure analyses in plant populations. Mol Ecol 13:921–935PubMedCrossRefGoogle Scholar
  55. Wallis IR, Keszei A, Henery ML, Moran GF, Forrester R, Maintz J, Marsh KJ, Andrew RL, Foley WJ (2011) A chemical perspective on the evolution of variation in Eucalyptus globulus. Perspect Plant Ecol, Evol Syst 13:305–318CrossRefGoogle Scholar
  56. Waples RS, Gaggiotti O (2006) What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Mol Ecol 15:1419–1439PubMedCrossRefGoogle Scholar
  57. Yeh F, Yang R-C, TBJ B, Z-H Y, JX M (1997) POPGENE, the user-friendly shareware for population genetic analysis. Molecular Biology and Biotechnology Centre, University of Alberta, Canada.
  58. Yu JM, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Suat Hui Yeoh
    • 1
    • 2
  • J. Charlie Bell
    • 3
  • William J. Foley
    • 1
  • Ian R. Wallis
    • 1
  • Gavin F. Moran
    • 1
  1. 1.Evolution, Ecology and Genetics, Research School of Biology, ANU College of Medicine, Biology and EnvironmentThe Australian National UniversityCanberraAustralia
  2. 2.Institute of Biological Sciences, Faculty of ScienceUniversity of MalayaKuala LumpurMalaysia
  3. 3.CSIRO Plant IndustryCanberraAustralia

Personalised recommendations