Trees

, Volume 27, Issue 4, pp 865–877

Assessing internal epicormic dynamics in Quercus alba L. using CT scanning: the strong effects of shoot development and tree growth relative to progeny level genetic variation

Original Paper

Abstract

Epicormic branches can be a serious silvicultural problem in many Quercus species because of the potential reduction in log value associated with their occurrence. The phenomenon is also problematic for tree improvement since the genetic component of epicormic branching has not been well quantified. The strong influence of ontogeny on epicormic development in Quercus is well established; however, the long-standing assumption that genetic variation also influences epicormics has not been rigorously tested. With trees from two, 25-year-old Quercus alba L. progeny tests in IN, USA, we used computed tomography scanning to characterize internal epicormic development. We sampled trees from upper and lower crown classes of families that had been classified as having low, medium and high numbers of epicormic sprouts. We also measured an array of variables related to growth and competition with the objective of assessing the relative impacts of genetics and vigor on epicormic development. Using generalized linear and linear mixed models, we found that ontogenetic and vigor variables were strongly associated with epicormic structure and development, and that the genetic effect was negligible. The total number of epicormics was most significantly influenced by the number of sequential branches that bore epicormics (p < 0.001) and the proportion of undeveloped epicormics was most significantly influenced by diameter increment (p < 0.001). We propose that a strong focus on individual tree vigor and form in tree improvement could minimize the impact of epicormic branching in Q. alba trees.

Keywords

White oak Computed tomography scanning Epicormic branches Genetic effects Tree vigor 

References

  1. Alden T (1971) Seasonal variations in occurence of indole-3-acetic acid in buds of Pinus silvestris. Physiol Plant 25:54–57CrossRefGoogle Scholar
  2. Aloni R, Schwalm K, Langhans M, Ullrich C (2003) Gradual shifts in sites of free-auxin production during leaf-primordium development and their role in vascular differentiation and leaf morphogenesis in Arabidopsis. Planta 216:841–853PubMedGoogle Scholar
  3. Bates D, Maechler M, Bolker B (2012) Package ‘lme4’: linear mixed-effects models using S4 classes. R package version 0.999999-0. http://cran.r-project.org/web/packages/lme4. Accessed 17 August 2012
  4. Bolker BM (2012) Package ‘bbmle’: tools for general maximum likelihood estimation. R package version 1.0.4.1. http://cran.r-project.org/web/packages/bbmle/index.html. Accessed 17 August 2012
  5. Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens MHH, White JS (2009) Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol Evol 24:127–135PubMedCrossRefGoogle Scholar
  6. Bowersox TW, Ward WW (1968) Auxin inhibition of epicormic shoots in white oak. For Sci 14:192–196Google Scholar
  7. Braham RR, Kellison RC (1987) Suppressed buds in yellow-poplar. J Elisha Mitch Sci S 103:47–55Google Scholar
  8. Browne WJ, Subramanian SV, Jones K, Goldstein H (2005) Variance partitioning in multilevel logistic models that exhibit overdispersion. J R Statist Soc A 168:599–613CrossRefGoogle Scholar
  9. Büsgen M, Münch E (1929) The structure and life of forest trees, 3rd edn. Chapman and Hall Ltd., LondonGoogle Scholar
  10. Carmean WH, Hahn JT, Jacobs RD (1989) Site index curves for forest tree species in the eastern United States. General Technical Report NC, vol 128. USDA Forest Service Google Scholar
  11. Church TW, Godman RM (1966) The formation and development of dormant buds in sugar maple. For Sci 12:301–306Google Scholar
  12. Colin F, Robert N, Druelle JL, Fontaine F (2008) Initial spacing has little influence on transient epicormic shoots in a 20-year-old sessile oak plantation. Ann For Sci 65:508CrossRefGoogle Scholar
  13. Colin F, Ducousso A, Fontaine F (2010a) Epicormics in 13-year-old Quercus petraea: small effect of provenance and large influence of branches and growth unit limits. Ann For Sci 67:312CrossRefGoogle Scholar
  14. Colin F, Mechergui R, Dhote JF, Fontaine F (2010b) Epicormic ontogeny on Quercus petraea trunks and thinning effects quantified with the epicormic composition. Ann For Sci 67:813CrossRefGoogle Scholar
  15. Colin F, Mothe F, Freyburger C, Morisset JB, Leban JM, Fontaine F (2010c) Tracking rameal traces in sessile oak trunks with X-ray computer tomography: biological bases, preliminary results and perspectives. Trees-Struct Funct 24:953–967CrossRefGoogle Scholar
  16. Colin F, Sanjines A, Fortin M, Bontemps JD, Nicolini E (2012) Fagus sylvatica trunk epicormics in relation to primary and secondary growth. Ann Bot 110:995–1005PubMedCrossRefGoogle Scholar
  17. Collet C, Colin F, Bernier F (1997) Height growth, shoot elongation and branch development of young Quercus petraea grown under different levels of resource availability. Ann Sci For 54:65–81CrossRefGoogle Scholar
  18. Dimov LD, Stelzer E, Wharton K, Meadows JS, Chambers JL, Ribbeck K, Moser EB (2006) Effects of thinning intensity and crown class on cherrybark oak epicormic branching five years after treatment. In: Conner KF (ed) Proceedings of the 13th Biennial Southern Silvicultural Research Conference. USDA Forest Serv Gen Tech Rep SRS-92. Asheville, pp 606–610Google Scholar
  19. Fink VS (1980) Anatomische Untersuchungen über das Vorkommen von Sproß- und Wurzelanlagen im Stammbereich von Laub- un Nadelbäumen. I. Proventive Anlagen. Allg Forst Jagdztg 151:160–180Google Scholar
  20. Fink VS (1983) The occurrence of adventitious and preventitious buds within the bark of some temperate and tropical trees. Am J Bot 70:532–542CrossRefGoogle Scholar
  21. Fontaine F, Druelle JL, Clement C, Burrus M, Audran JC (1998) Ontogeny of proventitious epicormic buds in Quercus petraea. I. In the 5 years following initiation. Trees-Struct Funct 13:54–62Google Scholar
  22. Fontaine F, Kiefer E, Clement C, Burrus M, Druelle JL (1999) Ontogeny of the proventitious epicormic buds in Quercus petraea. II. From 6 to 40 years of the tree’s life. Trees-Struct Funct 14:83–90Google Scholar
  23. Fontaine F, Colin F, Jarret P, Druelle JL (2001) Evolution of the epicormic potential on 17-year-old Quercus petraea trees: first results. Ann For Sci 58:583–592CrossRefGoogle Scholar
  24. Fontaine F, Mothe F, Colin F, Duplat P (2004) Structural relationships between the epicormic formations on the trunk surface and defects induced in the wood of Quercus petraea. Trees-Struct Funct 18:295–306CrossRefGoogle Scholar
  25. Gottschalk KW (1997) Stem quality of oak in 15-year-old stands: influence of species within harvesting treatment and fencing. In: Spiecker H, Rogers R, Somogyi Z (eds) Advances in research in intermediate oak stands. Institute for Forest Growth, Albert-Ludwigs-University of Freiburg, Freiburg, pp 85–97Google Scholar
  26. Hardin JW, Hilbe J (2007) Generalized linear models and extensions, 2nd edn. Stata Press, College StationGoogle Scholar
  27. Harmer R (1992a) Do dominant oaks have few epicormic branches? For Comm Gr Brit Res Div For Auth Res Inf Note 223Google Scholar
  28. Harmer R (1992b) The incidence of recurrent flushing and its effect on branch production in Quercus petraea (Matt) Liebl growing in southern England. Ann Sci For 49:589–597CrossRefGoogle Scholar
  29. Harmer R (2000) Differences in growth and branch production by young plants of two provenances of Quercus robur L. Forestry 73:271–281CrossRefGoogle Scholar
  30. Heuret P, Guédon Y, Guérard N, Barthélémy D (2003) Analysing branching pattern in plantations of young red oak trees (Quercus rubra L., Fagaceae). Ann Bot 91:479–492PubMedCrossRefGoogle Scholar
  31. Jensen JS (2000) Provenance variation in phenotypic traits in Quercus robur and Quercus petraea in Danish provenance trials. Scand J For Res 15:297–308CrossRefGoogle Scholar
  32. Jensen JS, Wellendorf H, Jager K, De Vries SMG, Jensen V (1997) Analysis of a 17-year old Dutch open-pollinated progeny trial with Quercus robur (L.). For Genet 4:139–147Google Scholar
  33. Kerr G, Harmer R (2001) Production of epicormic shoots on oak (Quercus robur): effects of frequency and time of pruning. Forestry 74:467–477CrossRefGoogle Scholar
  34. Kormanik PP, Brown CL (1969) Origin and development of epicormic branches in sweetgum. Research Paper SE, vol 54. USDA Forest ServiceGoogle Scholar
  35. Kuser JE, Knezick DR (1985) Twenty-year observations on a clonal plantation of pitch pine in the New Jersey pinelands. Bull Torrey Bot Club 112:318–323CrossRefGoogle Scholar
  36. Longuetaud F, Mothe F, Leban JM, Mäkelä A (2006) Picea abies sapwood width: variations within and between trees. Scand J Forest Res 21:41–53CrossRefGoogle Scholar
  37. Longuetaud F, Mothe F, Kerautret B, Krähenbühl A, Hory L, Leban JM, Debled-Rennesson I (2012) Automatic knot detection and measurements from X-ray CT images of wood: a review and validation of an improved algorithm on softwood samples. Comput Electron Agric 85:77–89CrossRefGoogle Scholar
  38. Meadows JS (1995) Epicormic branches and lumber grade of bottomland oak. In Lowery G, Meyer D (eds) Proceedings of the 23rd annual hardwood symposium: advances in hardwood utilization: following profitability from the woods through rough dimension. National Hardwood Lumberman’s Association, Cashiers, pp 19–25Google Scholar
  39. Meier AR (2012) Aspects of epicormic development in Quercus alba (L.) and other eastern North American oak species in relation to genetics, tree vigor and silvicultural treatments. MS Thesis, Purdue UniversityGoogle Scholar
  40. Meier AR, Saunders MR, Michler CH (2012) Epicormic buds in trees: a review of bud establishment, development and dormancy release. Tree Physiol 32:565–584PubMedCrossRefGoogle Scholar
  41. Miller GW (1996) Epicormic branching on central Appalachian hardwoods 10 years after deferment cutting. USDA For Serv Res Pap NE-702Google Scholar
  42. Miller GW (2000) Effect of crown growing space on the development of young hardwood crop trees. North J Appl For 17:25–35Google Scholar
  43. Miller GW, Stringer JW (2004) Effect of crown release on tree grade and DBH growth of white oak sawtimber in eastern Kentucky. In: Yaussy DA, Hix DM, Long RP, Goebel PC (eds) Proceedings of the 14th Central Hardwood Forest Conference. USDA For Serv Gen Tech Rep NE-316. Newton Square, pp 37–44Google Scholar
  44. Morisset JB, Mothe F, Bock J, Bréda N, Colin F (2012a) Epicormic ontogeny in Quercus petraea constrains the highly plausible control of epicormic sprouting by water and carbohydrates. Ann Bot 109:365–377PubMedCrossRefGoogle Scholar
  45. Morisset JB, Mothe F, Chopard B, François D, Fontaine F, Colin F (2012b) Does past emergence of epicormic shoots control current composition of epicormic types? Ann For Sci 69:139–152CrossRefGoogle Scholar
  46. Morisset JB, Mothe F, Colin F (2012c) Observation of Quercus petraea epicormics with X-ray CT reveals strong pith-to-bark correlations: silvicultural and ecological implications. Forest Ecol Manag 278:127–137CrossRefGoogle Scholar
  47. Nicolini E, Chanson B, Bonne F (2001) Stem growth and epicormic branch formation in understorey beech trees (Fagus sylvatica L.). Ann Bot 87:737–750CrossRefGoogle Scholar
  48. Nicolini E, Caraglio Y, Pélissier R, Leroy C, Roggy JC (2003) Epicormic branches: a growth indicator for the tropical forest tree, Dicorynia guianensis Amshoff (Caesalpiniaceae). Ann Bot 92:97–105PubMedCrossRefGoogle Scholar
  49. O’Connor PA, Coggeshall MV (2011) White oak seed source performance across multiple sites in Indiana through age 16. In: Fei S, Lhotka JM, Stringer JW, Gottschalk KW, Miller GW (eds) Proceedings of the 17th Central Hardwood Forest Conference. USDA For Serv Gen Tech Rep P-78. Newton Square, pp 358–363Google Scholar
  50. Okochi T, Hoshino Y, Fujii H, Mitsutani T (2007) Nondestructive tree-ring measurements for Japanese oak and Japanese beech using micro-focus X-ray computed tomography. Dendrochronlogia 24:155–164CrossRefGoogle Scholar
  51. Perkey AW, Wilkins BL (2001) Crop tree field guide: selecting and managing crop trees in the central Appalachians. USDA For Serv NA-TP-10-01Google Scholar
  52. R Development Core Team (2012a) R: a language and environment for statistical computing, version 2.15.0. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
  53. R Development Core Team (2012b) Package ‘stats’: the R stats package. R package version 2.15.0. http://www.r-project.org/. Accessed 17 August 2012
  54. Remphrey WR, Davidson CG (1992) Spatiotemporal distribution of epicormic shoots and their architecture in branches of Fraxinus pennsylvanica. Can J Forest Res 22:336–340CrossRefGoogle Scholar
  55. Rink G, Coggeshall MV (1995) Potential height gain from selection in a five-year-old white oak progeny test. South J Appl For 19:1–4Google Scholar
  56. Ripley B, Hornik K, Gebhardt A, Firth D (2012) Package ‘MASS’: support functions and datasets for venables and Ripley’s MASS. R package version 7.3-17. http://www.stats.ox.ac.uk/pub/MASS4/. Accessed 17 August 2012
  57. Schneider CA, Rasband WS, Eliceiri KW (2012) NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9:671–675PubMedCrossRefGoogle Scholar
  58. Scrucca L (2011) Package ‘qcc’: quality control charts. R package version 2.2. http://cran.r-project.org/web/packages/qcc/index.html. Accessed 17 August 2012
  59. Skaug H, Fournier D, Nielsen A, Magnusson A, Bolker B (2012) Package ‘glmmADMB’: generalized linear mixed models using AD model builder. R package version 0.7.2.12. http://glmmadmb.r-forge.r-project.org/. Accessed 17 August 2012
  60. Spiecker H (1991) Controlling the diameter growth and the natural pruning of sessile and pedunculate oaks. Schriftenreihe der Landesforstverwaltung, Baden-Württemberg Band 72, StuttgartGoogle Scholar
  61. Ward WW (1964) Bud distribution and branching in red oak. Bot Gaz 125:217–220CrossRefGoogle Scholar
  62. Ward WW (1966) Epicormic branching of black and white oaks. For Sci 12:290–296Google Scholar
  63. Wei Q, Leblon B, La Rocque A (2011) On the use of X-ray computed tomography for determining wood properties: a review. Can J Forest Res 41:2120–2140CrossRefGoogle Scholar
  64. Wetherill GB, Brown DW (1991) Statistical process control: theory and practice. Chapman and Hall, LondonGoogle Scholar
  65. Wu R, Zeng ZB, McKeand SE, O’Malley DM (2000) The case for molecular mapping in forest tree breeding. Plant Breed Rev 19:41–68Google Scholar
  66. Zellers CE, Saunders MR, Morrissey RC, Shields JM, Bailey BG, Dyer J, Cook J (2012) Development of allometric leaf area models for intensively managed black walnut (Juglans nigra L.). Ann For Sci 69:907–913Google Scholar
  67. Zuur A, Ieno E, Walker N, Saveliev A, Smith GM (2009) Mixed effects models and extensions in ecology with R. Springer, New YorkCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Forestry and Natural ResourcesPurdue UniversityWest LafayetteUSA

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