Tree Genetics & Genomes

, Volume 7, Issue 2, pp 271–283 | Cite as

Spatial genetic structure in wild cherry (Prunus avium L.): I. variation among natural populations of different density

  • Céline Jolivet
  • Aki M. Höltken
  • Heike Liesebach
  • Wilfried Steiner
  • Bernd Degen
Original Paper


Conservation of forest genetic resources requires intensive knowledge of the spatial arrangement of genetic diversity. In this study, we used four natural Prunus avium stands in Germany with contrasting for densities to understand patterns of spatial genetic structure. To this end, we genotyped adults and saplings at eight microsatellite markers, 54 AFLP loci and at the gametophytic incompatibility locus. We estimated levels of clonal propagation, spatial genetic structure and gene dispersal. High mortality occurred among young clonal individuals, as depicted by the lower clonal diversity in saplings. Contrasting levels of spatial genetic structure were observed among markers, ontogenic stages and populations. AFLP were more efficient for detecting spatial autocorrelation but did not allow us to differentiate low and high density populations, while high density populations showed substantially stronger spatial genetic structure at microsatellite loci. Furthermore, kinship decreased with tree age only in low density stands. We discuss the present results in terms of population history, pollen and seed dispersal and population density. Although conspecific density seems to be an interesting indicator of genetic diversity for conservation programmes, we still need to disentangle the relative influence of clonal propagation and density on the strength of spatial genetic structure. Simulation studies are needed to further address this question.


Spatial genetic structure Microsatellite AFLP Gametophytic incompatibility system Density Clonal propagation 



The project was funded by the German Ministry of Food, Agriculture and Consumer Protection (BMELV) by the grant 05/BE003/2 “Erfassung der genetischen Struktur der Vogelkirsche (Prunus avium) als Grundlage für ein genetisches Monitoring wichtiger Waldbaumarten in Deutschland.” We are thankful for the technical assistance of Alexandra Meier, Volker Schneck and Thomas Stauber; for the constructive comments on the manuscript of Olivier Hardy and two anonymous reviewers and for the language editing of Stephen Carvers.

Supplementary material

11295_2010_330_MOESM1_ESM.doc (62 kb)
Table S1 Genetic diversity and deviation from Hardy–Weinberg equilibrium among adults at eight microsatellites loci and at the gametophytic incompatibility system locus in four Prunus avium populations. A number of alleles, Ae effective number of alleles, H o observed heterozygosity, H e expected heterozygosity, F fixation index (with significance levels). (DOC 61.5 kb)
11295_2010_330_MOESM2_ESM.doc (56 kb)
Table S2 Genetic diversity and deviation from Hardy–Weinberg equilibrium among saplings at eight microsatellites loci in four Prunus avium populations. A number of alleles, Ae effective number of alleles, H o observed heterozygosity, H e expected heterozygosity, F fixation index (with significance levels). (DOC 56.5 kb)
11295_2010_330_MOESM3_ESM.doc (34 kb)
Table S3 Number of loci analysed, degree of polymorphism, effective number of alleles and Shannon’s information index for AFLP data in four Prunus avium populations. (DOC 34 kb)
11295_2010_330_MOESM4_ESM.doc (108 kb)
Table S4 Spatial autocorrelation analysis on a adults (all samples), b adults (subsample) and c saplings in four Prunus avium populations using only one ramet per genotype. F 1 is in the first distance class (0 to 20 m), the Nason kinship coefficient (Loiselle et al. 1995) for microsatellite and S-locus data, the kinship coefficient described in Hardy (2003) for AFLP data, b f is the restricted regression slope between the kinship coefficient and the logarithm of the distance calculated between 0 and 100 m and S p is the statistics defined by Vekemans and Hardy (2004). Significance of the slope was tested with 10,000 permutations. Confidence intervals of S p (b) were estimated as mean ± 2SE and markers were considered as differing significantly when confidence intervals were not overlapping. (DOC 112 kb)


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Céline Jolivet
    • 1
  • Aki M. Höltken
    • 2
    • 5
  • Heike Liesebach
    • 3
  • Wilfried Steiner
    • 4
  • Bernd Degen
    • 1
  1. 1.Institute of Forest GeneticsJohann Heinrich von Thünen Institut (vTI)GrosshansdorfGermany
  2. 2.Department of Wood Science, World ForestryUniversity of HamburgHamburgGermany
  3. 3.Institute of Forest GeneticsJohann Heinrich von Thünen Institut (vTI)WaldsieversdorfGermany
  4. 4.Nordwestdeutsche Forstliche Versuchsanstalt Abteilung WaldgenressourcenHannoversch MündenGermany
  5. 5.Forstliche Versuchs- und Forschungsantalt Baden-WürttembergFreiburgGermany

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