Advertisement

Morphological and genetic differentiation of wolf trees in Scots pine stands based on chloroplast microsatellite markers

  • Ekaterina MakrickieneEmail author
  • Darius Danusevičius
  • Gediminas Brazaitis
  • Michael Manton
Original Paper
  • 12 Downloads

Abstract

Genetic variation provides the foundation for species to survive, reproduce and evolve. Wolf trees are an example that may have a difference genetic background; however, research on the genetics of Scots pine (Pinus sylvestris L.) wolf trees is limited. The objectives were to assess (1) the morphological and genetic differentiation of wolf tree morphotypes in artificially established young commercial Scots pine stands using chloroplast microsatellite (cpSSR) DNA markers; and (2) the genetic differentiation based on progeny testing of mature wolf tree and regular tree morphotypes found in natural Scots pine stands. Our material consisted of (a) a 20-year-old artificially established stand in central Lithuania, where we morphotyped all trees and genotyped 59 wolf trees and 50 control trees at 6 cpSSR loci, (b) a nursery test where we assessed the morphology of 2-year-old open pollinated progeny of 8 wolf trees (20 seedlings per tree) in comparison with a control selected in a mature stand in northwestern Lithuania. Results showed a significant genetic differentiation between wolf trees and regular trees in young plantations based on the cpSSR DNA markers. Wolf trees had a higher genetic diversity at the cpSSR loci compared to the regular trees in the young plantations. The progeny test showed wolf trees contained more lateral shoots and possessed larger crown at age 2 in the nursery test. Our study suggests that there is a genetic background for the morphological differentiation between wolf trees and regular commercial Scots pine trees. However, the morphotype structure of wolf trees is complex, thus requiring future replicated studies spread across different regions and age classes.

Keywords

cpSSR Gene flow Genetic diversity Competition Pinus sylvestris Silviculture 

Notes

References

  1. Beck W (2004) Wirkung der Witterung auf Wachstum und Vitalität von Waldbäumen und Waldbeständen [Effect of weather on growth and vitality of forest trees and forest stands]. In: Anders et al (eds). Auswirkungen der Trockenheitim Jahr 2003 auf Waldzustand und Waldbau. Arbeitsbericht der BFH Nr 2/2004: 36–56 (in German) Google Scholar
  2. Buchovska J, Danusevičius D, Baniulis D, Stanys V, Šikšnianienė JB, Kavaliauskas D (2013) The location of the northern glacial refugium of Scots pine based on mitochondrial DNA markers. Baltic For 19(1):2–12Google Scholar
  3. Cheddadi R, Vendramin GG, Litt T, François L, Kageyama M, Lorentz S, Laurent J-M, De Beaulieu J-L, Sadori L, Jost A, Lunt D (2006) Imprints of glacial refugia in the modern genetic diversity of Pinus sylvestris. Glob Ecol Biogeogr 15:271–282CrossRefGoogle Scholar
  4. Danusevicius D (2008) Hybrid vigour from intra-specific crosses of Scots pine. Baltic For 14(1):2–6Google Scholar
  5. Danusevičius D, Kavaliauskas D, Fussi B (2016) Optimum sample size for SSR-based estimation of representative allele frequencies and genetic diversity in Scots pine populations. Baltic For 22(2):194–202Google Scholar
  6. Dumolin S, Demesure B, Petit RJ (1995) Inheritance of chloroplast and mitochondrial genomes in pedunculated oak investigated with an efficient PCR method. Theor Appl Genet 91:1253–1256CrossRefPubMedGoogle Scholar
  7. Earl DA, von Holdt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361CrossRefGoogle Scholar
  8. Eiche V, Andersson E (1974) Survival and growth in Scots pine (Pinus sylvestris L.). Theor Appl Genet 44:49–57CrossRefPubMedGoogle Scholar
  9. Ekberg I, Eriksson G, Dormling I (1979) Photoperiodic reactions in conifer species. Holarct Ecol 2:255–263Google Scholar
  10. Eliades NG, Eliades DG (2009) Haplotype analysis: software for analysis of haplotypes data. Distributed by the authors. Forest Genetics and Forest Tree Breeding, Georg-Augst University Goettingen, Germany, GöttingenGoogle Scholar
  11. Ennos RA, Sinclair WT, Hu XS, Langdon A (1999) Using organelle markers to elucidate the history, ecology and evolution of plant populations. Syst Assoc Spec 57:1–19Google Scholar
  12. Epperson BK (2004) Multilocus estimation of genetic structure within populations. Theor Popul Biol 65(3):227–237CrossRefPubMedGoogle Scholar
  13. Eriksson G (2008) Pinus sylvestris recent genetic research. Department of Plant Biology and Forest Genetics, Genetic Center, Swedish University of Agricultural Sciences. Uppsala, Sweden, 111 p. ISBN 978-91-85911-90-5Google Scholar
  14. Eriksson G, Ilstedt B, Nilsson C, Ryttman H (1987) Within- and between-population variation of growth and stem quality in a 30-year-old Pinus sylvestris trial. Scand J For Res 2(1–4):301–314CrossRefGoogle Scholar
  15. Erteld W (1960) Untersuchung über Leistung und Entwicklung der Kiefer bei verschiedener Behandlung [Study on performance and development of pine under different treatment]. Arch Forstw 9:326–364 (in German) Google Scholar
  16. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620CrossRefPubMedGoogle Scholar
  17. Faulkner R (1969) Some characters of secondary importance to stem straightness in the breeding of conifers. Second world consultation on forest tree breeding, Washington, DC, USA, 7–16 August 1969. 1970, vol 1, pp 269–283Google Scholar
  18. Felsenstein J (2005) PHYLIP (Phylogeny Inference Package) version 3.6. Distributed by the author. Department of Genome Sciences, University of Washington, SeattleGoogle Scholar
  19. Ferris R, Humphrey JW (1999) A review of potential biodiversity indicators for application in British forests. Forestry 72(4):313–328CrossRefGoogle Scholar
  20. Gedminas A, Ozolinčius R (2006) Medžiai-Vilkai, Medžiai-Avys Ir Sverto Taisyklė [Wolf-trees, sheep-trees and the rule of lever]. Naturales Scientiae Omnibus. http://gamta.vdu.lt/bakalaurai/pop_straipsniai/medziai_vilkai_avys/medziai_vilkai_avys.html. Accessed 15 Oct 2018 (in Lithuanian)
  21. Giertych M (1991) Provenance variation in growth and phenology. In: Giertych M, Mátyás C (eds) Genetics of Scots pine. Akademiai Kiado, Budapest, pp 87–101Google Scholar
  22. Goldstein DB, Linares AR, Cavalli-Sforza LL, Feldman MW (1995) An evaluation of genetic distances for use with microsatellite loci. Genetics 139(1):463–471PubMedPubMedCentralGoogle Scholar
  23. Haapanen M, Veiling P, Annala M-L (1997) Progeny trial estimates of genetic parameters for growth and quality traits in Scots pine. Silva Fennica 31(1):3–12CrossRefGoogle Scholar
  24. Hale ML, Burg TM, Steeves TE (2012) Sampling for microsatellite-based population genetic studies: 25–30 individuals per population is enough to accurately estimate allele frequencies. PLoS ONE 7(9):e45170CrossRefPubMedPubMedCentralGoogle Scholar
  25. Hannerz M (1998) Genetic and seasonal variation in hardiness and growth rhythm in boreal and temperate conifers—a review and annotated bibliography. The Forestry Research Institute of Sweden, Report 2, p 140Google Scholar
  26. Hertel H, Kohlstock N (1994) Different genetic structures of two morphological types of Scots pine (Pinus sylvestris L.). Silvea Genetica 43(5):268–272Google Scholar
  27. Karazija S (1988) Lietuvos miska tipai. [Forest types of Lithuania]. Mokslas, Vilnius (in Lithuanian) Google Scholar
  28. Kavaliauskas D (2015) Genetic structure and genetic diversity of Scots pine (Pinus sylvestris L.) populations in Lithuania. Ph.D. thesis, Aleksandras Stulginskis University, p 139 (in English) Google Scholar
  29. Kerpauskaite V (2017) Effect of forest management on genetic diversity and spatial genetic structure of Scots pine. Ph.D. thesis, Aleksandras Stulginskis university, Akademija 2017, p 95Google Scholar
  30. Kerr G, Haufe J (2011) Thinning practice. A silvicultural guide. Forestry commission. http://www.forestry.gov.uk/pdf/Silviculture_Thinning_Guide_v1_Jan2011.pdf/$FILE/Silviculture_Thinning_Guide_v1_Jan2011.pdf. Accessed 05 June 2018
  31. Kohlstock N (1982) Neue Erkenntnisse in der Kiefern-Jungwuchpflege [New insights into the management of young pine stands]. Beiträge fur die Forstwirtschaft 4:155–159 (in German) Google Scholar
  32. Kräuter G (1965) Die Behandlung von Kiefernjungbeständen auf der Grundlage von biologischen und dynamischen Merkmalen der Einzelstämme. Conference report. AdL Berlin 75:337–342 (in German) Google Scholar
  33. Lindgren D, Paule L, Xihuan S, Yadzani R, Segerström U, Tallin J-E, Lejdebro ML (1995) Can viable pollen carry Scots pine genes over long distances? Grana 34:64–69CrossRefGoogle Scholar
  34. Liu K, Muse SV (2005) PowerMarker: integrated analysis environment for genetic marker data. Bioinformatics 21:2128–2129CrossRefPubMedGoogle Scholar
  35. Liziniewicz M (2014) Influence of spacing and thinning on wood properties in conifer plantations. Doctoral dissertation. Acta Universitatis agriculturae Sueciae. p 96Google Scholar
  36. Lockow K-W (1992) Kieferntypen und Bestandesbehandlung. Zum Wachstumsablauf und zur Wuchsdynamik der Kiefer miteinigen Schlussfolgerungenfür die Bestandesbehandlung [Pine types and stand treatment. On the growth process and the growth dynamics of pine with some conclusions for the stand treatment]. Der Wald 42(5):170–173 (in German) Google Scholar
  37. Lönnroth E (1925) Untersuchungen über die innere Struktur und Entwicklung gleichaltriger naturnormaler Kiefernbestände, basiert auf Material aus der Südhälfte Finnlands [Research into the internal structure and evolution of the same age normal natural pine stands, based on the materials from the southern half of Finland]. Acta Forestalia Fennica Nr 30:1–269 (in German) Google Scholar
  38. Makarov V, Iozus A, Morozova E (2014) Estimation of the heritability of selected breeding material by speed of growth of the seed progeny in the conditions of dry steppe in lower Volga region. Mod Prob Sci Educ No 4. http://science-education.ru/ru/article/view?id=14317. Accessed 14 Mar 2019 (in Russian)
  39. Makrickiene E (2017) Environmental and genetic attributes of wolf trees’ morphological types in scots pine (Pinus sylvestris L.). ASU, Kaunas, p 130Google Scholar
  40. Makrickiene E, Drössler L, Brazaitis G (2016) Development and traits of wolf trees in Scots pine (Pinus sylvestris L.): a literature review. Baltic For 22(1):181–188Google Scholar
  41. Mason WL, Alia R (2000) Current and future status of Scots pine (Pinus sylvestris L.) forests in Europe. Investigacion Agraria: Sistemos y Recursos Forestales Fuera de Serie 1–2000:317–333Google Scholar
  42. Namkoong G, Boyle TJB, Gregorius H-R, Joly H, Savolainen O, Ratnam W, Young A (1996) Testing criteria and indicators for assessing the sustainability of forest management: genetic criteria and indicators. CIFOR working paper No. 10. CIFOR, Bogor, Indonesia, 15 ppGoogle Scholar
  43. Naydenov K, Senneville S, Beaulieu J, Tremblay F, Bousquet J (2007) Glacial vicariance in Eurasia: mitochondrial DNA evidence from Scots pine for a complex heritage involving genetically distinct refugia at mid-northern latitudes and in Asia Minor. BMC Evol Biol 7(1):233CrossRefPubMedPubMedCentralGoogle Scholar
  44. Neale DB, Sederoff RR (1989) Paternal inheritance of chloroplast DNA and maternal inheritance of mitochondrial DNA in loblolly pine. Theor Appl Genet 77(2):212–216CrossRefPubMedGoogle Scholar
  45. Nei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. J Mol Evol 19:153–170CrossRefPubMedGoogle Scholar
  46. Nilsson J-E (1991) The value of early testing. In: Giertych M, Mįtyįs CS (eds) Genetics of Scots pine. Elsevier, Amsterdam, pp 255–263Google Scholar
  47. Nilsson U, Albrektsson A (1993) Productivity of needles and allocation of growth in young Scots pine trees of different competitive status. For Ecol Manag 62(1–4):173–187CrossRefGoogle Scholar
  48. Nilsson U, Agestam E, Eko P-M, Elfving B, Fahlvik N, Johansson U, Karlsson K, Lundmark T, Wallentin C (2010) Thinning of Scots pine and Norway spruce monocultures in Sweden—effects of different thinning programmes on stand level gross- and net stem volume production. Technical report. Studia Forestalia Suecica No 219, 47 ppGoogle Scholar
  49. Page RD (2001) TreeView. Glasgow University, GlasgowGoogle Scholar
  50. 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
  51. Persson A, Persson B (1992) Survival, growth and quality of Norway spruce (Picea abies (L.) Karst.) provenances at the three Swcdish sites of the IUFRO 1964/68 provenance experiment. Sweden University of Agricultural Sciences Department Forest Yield Research Report 29Google Scholar
  52. Pofahl U, Lockow K-W, Läuter H (1979) Zur Lösung von Klassifizierungsproblemen mit Hilfe der mehrdimensionalen Varianzanalyse [Solution of classification problems using the multidimensional analysis of variance]. Beiträge für die Forstwirtschaft 13(2):41–48 (in German) Google Scholar
  53. Powell W, Morgante M, Andre C, McNicol JW, Machray GC, Doyle JJ, Tingey SV, Rafalski JA (1995) Hypervariable microsatellites provide a general source of polymorphic DNA markers for the chloroplast genome. Curr Biol 5(9):1023–1029CrossRefPubMedGoogle Scholar
  54. Prescher F (1985) Framtida förädlingsstrategi for tall [Future breeding strategy for Scots pine]. Slutredogörelse till Skogs-och Jordbrukets Forskningsrâd. Swedish University of Agricultural Sciences, Department of Forestry Yielding Research, Department Note (in Swedish) Google Scholar
  55. Preuhsler T (1979) Ertragskundliche Merkmale oberbayerischer Bergmischwald-Verjüngungsbestände auf kalkalpinen Standorten im Forstamt Kreuth. Forstl Forschungsber München 45:312–345 (in German) Google Scholar
  56. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  57. Provan J, Soranzo N, Wilson NJ, McNicol JW, Forrest GI, Cottrell J, Powell W (1998) Gene-pool variation in Caledonian and European Scots pine (Pinus sylvestris L.) revealed by chloroplast simple-sequence repeats. Proc R Soc Lond 265:1697–1705CrossRefGoogle Scholar
  58. Schötte G (1917) Om snöskadorna i södra och mellersta Sveriges skogar åren 1915–1916. Meddelanden från statens skogs-försöksanstalt 13–14(1):111–175 (In Swedish) Google Scholar
  59. Selkoe KA, Toonen RJ (2006) Microsatellites for ecologists: a practical guide to using and evaluating microsatellite markers. Ecol Lett 9(5):615–629CrossRefPubMedGoogle Scholar
  60. Sinclair WT, Morman JD, Ennos RA (1999) The postglacial history of Scots pine (Pinus sylvestris L.) in Western Europe: evidence from mitochondrial DNA variation. Mol Ecol 8:83–88CrossRefGoogle Scholar
  61. Uusvaara O (1991) Havaintoja nuorten istutusmänniköiden oksikkuudesta ja puuaineen laadusta. [Observations about the branchiness and the wood quality of young plantation-grown Scots pine.] Metsäntutkimuslaitoksen tiedonantoja 377, 56 p (In Finnish with English summary)Google Scholar
  62. Vanninen P, Mäkelä A (2005) Carbon budget for Scots pine trees: effects of size, competition and site fertility on growth allocation and production. Tree Physiol 25:17–30CrossRefPubMedGoogle Scholar
  63. Vendramin GG, Lelli L, Rossi P, Morgante M (1996) A set of primers for the amplification of 20 chloroplast microsatellites in Pinaceae. Mol Ecol 5:595–598CrossRefPubMedGoogle Scholar
  64. Wiedemann E (1943) Kiefern-Ertragstafel für mäßige Durchforstung, starke Durchforstung und Lichtung [A yield table for moderate thinning, heavy thinning and light-enchancing thinning in pine]. In: Schober R (ed) Ertragstafeln wichtiger Holzarten bei verschiedener Durchforstung, 4th edn. Sauerländer, Frankfurt am Main, pp 98–115 (in German) Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Vytautas Magnus UniversityAkademijaLithuania
  2. 2.LAMMC Forest Research Institute of Lithuanian Research Centre for Agriculture and ForestryGirionysLithuania

Personalised recommendations