Annals of Forest Science

, Volume 69, Issue 1, pp 93–104 | Cite as

Influence of early re-spacing on Sitka spruce branch structure

  • David AutyEmail author
  • Aaron R. Weiskittel
  • Alexis Achim
  • John R. Moore
  • Barry A. Gardiner
Original Paper



The frequency, size, and insertion angle of primary branches are important determinants of wood quality and can be significantly influenced by silvicultural activities.


This study quantified the long-term influence of early re-spacing on the branching characteristics of mature Sitka spruce [Picea sitchensis (Bong.) Carr.] trees growing in Northern Ireland, UK. The primary aim was to investigate whether any residual effect of stand density on branch attributes remained once the effect of changes in tree size variables had been considered, while a secondary objective was to test the performance of existing Sitka spruce branch models using the current dataset.


Re-spacing treatments had corresponding stand densities of 2,858, 1,452, 725, 477, and 320 stems ha−1. Twenty-four trees were sampled when the stand was 57 years old and branch frequency, size, and insertion angle were recorded for model development.


Maximum branch diameter, insertion angle, and branch frequency were significantly influenced by re-spacing, while no effect was found for relative branch diameter distribution. Residual re-spacing effects were most noticeable on branch size, with only small differences between treatments for branch frequency and insertion angle. Existing models performed well despite the wider range of stand densities examined in the present study.


The results indicate that early re-spacing from 1.9 m2 to wider than 2.6 m2 will result in branch attributes that are detrimental to Sitka spruce sawn timber quality.


Picea sitchensis Wood quality Early re-spacing Maximum branch size Number of branches Branch angle Relative branch size 



We would like to thank Baronscourt Estate and the Northern Ireland Forest Service for allowing access to the trial. Shaun Mochan helped to manage the field project and Elspeth Macdonald, Paul McLean, David Swinson, Floran Pierre, and staff from the Agricultural Food and Bioscience Institute assisted with the field sampling. Drs. Thomas Connolly and Helen McKay provided helpful comments on an earlier version of the manuscript, and we also thank the anonymous reviewers for their valuable comments. The work was funded by the Forestry Commission Corporate and Forestry Services and by a Strategic Research and Development Grant from the Scottish Funding Council.


  1. Achim A, Gardiner BA, Leban J-M, Daquitane R (2006) Predicting the branching properties of Sitka spruce grown in Great Britain. NZ J For Sci 36:246–264Google Scholar
  2. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723CrossRefGoogle Scholar
  3. Barthélémy D, Caraglio Y (2007) Plant architecture: a dynamic, multilevel and comprehensive approach to plant form, structure and ontogeny. Ann Bot-London 99:375–407CrossRefGoogle Scholar
  4. Brazier JD (1970) Timber improvement II: the effect of vigour on young growth Sitka spruce. Forestry 43:135–150CrossRefGoogle Scholar
  5. Brazier JD (1977) The effect of forest practices on quality of the harvested crop. Forestry 50:49–66CrossRefGoogle Scholar
  6. Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer, New YorkGoogle Scholar
  7. Cannell MGR (1974) Production of branches and foliage by young trees of Pinus contorta and Picea sitchensis: provenance differences and their simulation. J Appl Ecol 11:1091–1115CrossRefGoogle Scholar
  8. CEN (2003) Structural timber—strength classes. EN338:2003, European Committee for Standardization, Brussels, BelgiumGoogle Scholar
  9. Colin F, Houllier F (1991) Branchiness of Norway spruce in north-eastern France: modeling vertical trends in maximum nodal branch size. Ann For Sci 48:679–693CrossRefGoogle Scholar
  10. Colin F, Houllier F (1992) Branchiness of Norway spruce in northeastern France: predicting the main crown characteristics from usual tree measurements. Ann Sci Forest 49:511–538CrossRefGoogle Scholar
  11. Forestry Commission (2010) Forestry facts and figures 2010: a summary of statistics about woodland and forestry. Forestry Commission, EdinburghGoogle Scholar
  12. Deal RL, Barbour RJ, McClellan MH, Parry DL (2003) Development of epicormic sprouts in Sitka spruce following thinning and pruning in south-east Alaska. Forestry 76:401–412CrossRefGoogle Scholar
  13. Fonweban JB, Gardiner BA, Macdonald SE, Auty D (2011) Taper functions for Scots pine (Pinus sylvestris L.) and Sitka spruce (Picea sitchensis (Bong.) Carr.) in northern Britain. Forestry 84:49–60CrossRefGoogle Scholar
  14. Forest Products Laboratory (2010) Wood handbook, wood as an engineering material. General technical report FPL-GTR-190. U.S. Department of Agriculture, Forest Service, Forest Products Laboratory, Madison, 508 pGoogle Scholar
  15. Garber SM, Maguire DA (2003) Modeling stem taper of three central Oregon species using nonlinear mixed-effects models and autoregressive error structures. Forest Ecol Manag 179:507–522CrossRefGoogle Scholar
  16. Garber SM, Maguire DA (2005) Vertical trends in maximum branch diameter in two mixed-species spacing trials in the central Oregon Cascades. Can J Forest Res 35:295–307CrossRefGoogle Scholar
  17. Gardiner BA, Leban J-M, Auty D, Simpson H (2011) Models for predicting wood density of British-grown Sitka spruce. Forestry 84:119–132CrossRefGoogle Scholar
  18. Grace JC, Pont D, Goulding CJ (1999) Modelling branch development for forest management. NZ J For Sci 29:391–408Google Scholar
  19. Guilley E, Hervé JC, Nepveu G (2004) The influence of site quality, silviculture and region on wood density mixed model in Quercus petraea Liebl. Forest Ecol Manag 189:111–121CrossRefGoogle Scholar
  20. Halsall L, Gilbert J, Matthews, R, Fairgrieve, M (2006) United Kingdom: new forecast of softwood availability. Forestry Commission EdinburghGoogle Scholar
  21. Hein S, Weiskittel AR, Kohnle U (2008a) Branch characteristics of widely-spaced Douglas-fir in south-western Germany: comparisons of modelling approaches and geographic regions. Forest Ecol Manag 256:1064–1079CrossRefGoogle Scholar
  22. Hein S, Weiskittel AR, Kohnle U (2008b) Effect of wide spacing on tree growth, branch and sapwood properties of young Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco] in southwestern Germany. Eur J Forest Res 127:481–493CrossRefGoogle Scholar
  23. Heuret P, Meredieu C, Coudurier T, Courdier F, Barthélémy D (2006) Ontogenetic trends in the morphological features of main stem annual shoots of Pinus pinaster (Pinaceae). Am J Bot 93:1577–1587PubMedCrossRefGoogle Scholar
  24. Houllier F, Leban J-M, Colin F (1995) Linking growth modelling to timber quality assessment for Norway spruce. Forest Ecol Manag 74:91–102CrossRefGoogle Scholar
  25. Jack WH (1971) The influence of tree spacing on Sitka spruce growth. Irish Forestry 28:13–33Google Scholar
  26. Joyce PM, OCarroll N (2002) Sitka spruce in Ireland. National Council for Forest Research and Development (COFORD), DublinGoogle Scholar
  27. Kampstra P (2008) Beanplot: a boxplot alternative for visual comparison of distributions. J Stat Software 28:1–9Google Scholar
  28. Kilpatrick DJ, Sanderson JM, Savill JS (1981) The influence of five early respacing treatments on the growth of Sitka spruce. Forestry 54:17–29CrossRefGoogle Scholar
  29. Littel RC, Milliken GA, Stroup WW, Wolfinger RD (2002) SAS system for mixed models. SAS Institute Inc., CaryGoogle Scholar
  30. Macdonald SE, Hubert J (2002) A review of the effects of silviculture on timber quality of Sitka spruce. Forestry 75:107–138CrossRefGoogle Scholar
  31. Macdonald SE, Gardiner BA, Mason WL (2010) The effects of transformation of even-aged stands to continuous cover forestry on conifer log quality and wood properties in the UK. Forestry 83:1–16CrossRefGoogle Scholar
  32. Maguire DA, Kershaw JA, Hann DW (1991) Predicting the effects of silvicultural regime on branch size and crown wood core in Douglas-fir. Forest Sci 37:1409–1428Google Scholar
  33. Mäkinen H, Colin F (1999a) Predicting the number, death, and self-pruning of branches in Scots pine. Can J Forest Res 29:1225–1236CrossRefGoogle Scholar
  34. Mäkinen H, Colin F (1999b) Predicting branch angle and branch diameter of Scots pine from usual tree measurements and stand structural information. Can J Forest Res 28:1686–1696CrossRefGoogle Scholar
  35. Mäkinen H, Hein S (2006) Effect of wide spacing on increment and branch properties of young Norway spruce. Eur J Forest Res 125:239–248CrossRefGoogle Scholar
  36. Maun KW (1992) Sitka spruce for construction timber: The relationship between wood growth characteristics and machine grade yields of Sitka spruce. Research information note 212. Forestry Commission: Edinburgh, UK.Google Scholar
  37. McCullagh P, Nelder JA (1989) Generalized linear models. Chapman & Hall, LondonGoogle Scholar
  38. Moore JR, Achim A, Lyon A, Mochan S, Gardiner BA (2009) Effects of early re-spacing on the physical and mechanical properties of Sitka spruce structural timber. Forest Ecol Manag 258:1174–1180CrossRefGoogle Scholar
  39. Parresol BR (1999) Assessing tree and stand biomass: a review with examples and critical comparisons. Forest Sci 45:573–593Google Scholar
  40. Pinheiro JC, Bates DM (2009) Mixed-effects models in S and S-PLUS. Springer, New YorkGoogle Scholar
  41. Quine CP (2004) Development of epicormic sprouts on Sitka spruce stems in response to windthrown gap formation. Forestry 77:225–233CrossRefGoogle Scholar
  42. R Development Core Team (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  43. Schneider R, Zhang SY, Swift DE, Bégin J, Lussier J-M (2008) Predicting selected wood properties of jack pine following commercial thinning. Can J Forest Res 38:2030–2043CrossRefGoogle Scholar
  44. Tasissa G, Burkhart HE (1998) An application of mixed effects analysis to modeling thinning effects on stem profile of loblolly pine. Forest Ecol Manag 103:87–101CrossRefGoogle Scholar
  45. Wardle PA (1967) Spacing in plantations: a management review. Forestry 40:47–69CrossRefGoogle Scholar
  46. Weiskittel AR, Maguire DA, Monserud RA (2007) Modeling crown structural responses to competing vegetation control, thinning, fertilization, and Swiss needle cast in coastal Douglas-fir of the Pacific Northwest, USA. Forest Ecol Manag 245:96–109CrossRefGoogle Scholar
  47. Weiskittel AR, Seymour RS, Hofmeyer PV, Kershaw JA (2010) Modelling primary branch frequency and size for five conifer species in Maine, USA. Forest Ecol Manag 259:1912–1921CrossRefGoogle Scholar
  48. Worrell R (1987) Geographical variation in Sitka spruce productivity and its dependence on environmental factors. PhD dissertation. University of Edinburgh, Edinburgh, UKGoogle Scholar
  49. Zhang S, Chauret G, Ren HQ, Desjardins R (2002) Impact of initial spacing on plantation black spruce lumber grade yield, bending properties, and MSR yield. Wood Fiber Sci 34:460–475Google Scholar

Copyright information

© INRA and Springer-Verlag, France 2011

Authors and Affiliations

  • David Auty
    • 1
    • 4
    Email author
  • Aaron R. Weiskittel
    • 2
  • Alexis Achim
    • 1
    • 4
  • John R. Moore
    • 3
    • 5
  • Barry A. Gardiner
    • 1
  1. 1.Forest ResearchRoslinUK
  2. 2.School of Forest ResourcesUniversity of MaineOronoUK
  3. 3.Forest Products Research InstituteEdinburgh Napier UniversityEdinburghUK
  4. 4.Département des Sciences du bois et de la ForêtUniversité LavalQuébecCanada
  5. 5.Scion (New Zealand Forest Research Institute Limited)RotoruaNew Zealand

Personalised recommendations