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Modeling Wood Characteristics

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Modeling Forest Trees and Stands

Abstract

In addition to affecting tree growth and stand productivity, management treatments also affect characteristics of the wood produced. To fully evaluate the feasibility of various management alternatives, quantitative information on both wood quantity and quality is needed. Wood quality is a term that is commonly used to denote wood characteristics that can be quantified and used to evaluate suitability for specified end uses. This chapter presents information on modeling important wood characteristics, including (i) juvenile-mature wood demarcation, (ii) wood specific gravity, (iii) ring widths, and (iv) number, size, and location of knots. The chapter concludes with a discussion of incorporating wood quality information into growth and yield models and linking growth and yield models with sawing simulators.

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References

  • Abdel-Gadir A, Krahmer RL (1993) Estimating the age of demarcation of juvenile and mature wood in Douglas-fir. Wood Fiber Sci 25:242–249

    Google Scholar 

  • Anthony F, Schimleck LR, Jordan L, Clark A, Daniels RF (2011) Effect of early age woody and herbaceous competition control on wood properties of loblolly pine. For Ecol Manage 262:1639–1647

    Article  Google Scholar 

  • Antony F, Jordan L, Daniels RF, Schimleck LR, Clark A III, Hall DB (2009) Effect of midrotation fertilization on growth and specific gravity of loblolly pine. Can J For Res 39:928–935

    Article  CAS  Google Scholar 

  • Antony F, Schimleck LR, Daniels RF, Clark A III, Hall DB (2010) Modeling the longitudinal variation in wood specific gravity of planted loblolly pine (Pinus taeda) in the United States. Can J For Res 40:2439–2451

    Article  Google Scholar 

  • Antony F, Schimleck LR, Hall DB, Clark A III, Daniels RF (2011) Modeling the effect of midrotation fertilization of specific gravity of loblolly pine (Pinus taeda L.). For Sci 57:145–152

    Google Scholar 

  • Aspinwall MJ, Li B, McKeand SE, Isik F, Gumpertz ML (2010) Prediction of whole-stem α-cellulose yield, lignin content, and wood density in juvenile and mature loblolly pine. South J Appl For 34:84–90

    Google Scholar 

  • Bamber RK, Burley J (1983) The wood properties of radiata pine. Commonwealth Agricultural Bureaux, Slough

    Google Scholar 

  • Barbour JR, Parry DL, Punches J, Forsman J, Ross R (2003) AUTOSAW simulations of lumber recovery for small-diameter Douglas-fir and ponderosa pine from southwestern Oregon. USDA Forest Service, Research Note PNW-RN-543

    Google Scholar 

  • Barnett JR, Jeronimidis G (eds) (2003) Wood quality and its biological basis. Blackwell Publishing/CRC Press, Oxford/Boca Raton

    Google Scholar 

  • Beaulieu E, Schneider R, Berninger F, Ung C-H, Swift DE (2011) Modeling jack pine branch characteristics in Eastern Canada. For Ecol Manage 262:1748–1757

    Article  Google Scholar 

  • Bendtsen BA, Senft J (1986) Mechanical and anatomical properties in individual growth rings of plantation-grown eastern cottonwood and loblolly pine. Wood Fiber Sci 18:23–38

    Google Scholar 

  • Benjamin JG, Chui YH, Kershaw JA Jr (2009a) Circular distribution of branches from plantation grown black spruce in Ontario. North J Appl For 26:15–20

    Google Scholar 

  • Benjamin JG, Kershaw JA Jr, Weiskittel AR, Chui YH, Zhang SY (2009b) External knot size and frequency in black spruce trees from an initial spacing trial in Thunder Bay, Ontario. For Chron 85:618–624

    Google Scholar 

  • Biblis E, Meldahl R, Pitt D, Carino HF (2004) Predicting flexural properties of dimension lumber from 40-year-old loblolly pine plantation stands. For Prod J 54(12):109–113

    Google Scholar 

  • Bowyer JL, Shmulsky R, Haygreen JG (2007) Forest products and wood science: an introduction, 5th edn. Blackwell Publishing, Oxford

    Google Scholar 

  • Burdon RD, Kibblewhite RP, Walker JCF, Megraw RA, Evans R, Cown DJ (2004) Juvenile versus mature wood: a new concept, orthogonal to corewood versus outerwood, with special reference to Pinus radiata and P. taeda. For Sci 50:399–415

    Google Scholar 

  • Burkhart HE, Beckwith JR III (1970) Specific gravity prediction and dry-weight yield estimation. Tappi 53:603–604

    Google Scholar 

  • Clark A III, Saucier JR (1989) Influence of initial planting density, geographic location, and species on juvenile wood formation in southern pine. For Prod J 39(7/8):42–48

    Google Scholar 

  • Clark A III, Saucier JR (1991) Influence of planting density, intensive culture, geographic location, and species on juvenile wood formation in southern pine. Georgia Forest Research Paper 85, Georgia Forestry Commission

    Google Scholar 

  • Clark A III, Daniels RF, Jordan L (2006) Juvenile/mature wood transition in loblolly pine as defined by annual ring specific gravity, proportion of latewood, and microfibril angle. Wood Fiber Sci 38:292–299

    CAS  Google Scholar 

  • Colin F, Houllier F (1991) Branchiness of Norway spruce in north-eastern France: modeling vertical trends in maximum nodal branch size. Ann Sci For 48:679–693

    Article  Google Scholar 

  • Colin F, Houllier F (1992) Branchiness of Norway spruce in northeastern France: predicting the main crown characteristics from usual tree measurements. Ann Sci For 49:511–538

    Article  Google Scholar 

  • Cown DJ, Clement BC (1983) A wood densitometer using direct scanning with X-rays. Wood Sci Technol 17:91–99

    Article  Google Scholar 

  • Di Lucca CM (1999) TASS/SYLVER/TIPSY: systems for predicting the impact of silvicultural practices on yield, lumber value, economic return and other benefits. In: Stand density management conference: using the planning tools. Clear Lake Ltd, Edmonton, pp 7–16

    Google Scholar 

  • Doruska PF, Burkhart HE (1994) Modeling the diameter and locational distribution of branches within the crowns of loblolly pine trees in unthinned plantations. Can J For Res 24:2362–2376

    Article  Google Scholar 

  • Farrar JL (1961) Longitudinal variation in the thickness of the annual ring. For Chron 37:323–330

    Google Scholar 

  • Fayle DCF (1973) Patterns of annual xylem increment integrated by contour presentation. Can J For Res 3:105–111

    Article  Google Scholar 

  • Fayle DCF, MacDonald GB (1977) Growth and development of sugar maple as revealed by stem analysis. Can J For Res 7:526–536

    Article  Google Scholar 

  • Forintek Canada Corp (1994) Optitek: users’s guide. Forintek Canada Corp, Sainte-Foy

    Google Scholar 

  • Fujimoto T, Koga S (2009) An application of mixed-effects model to evaluate the effects of initial spacing on radial variation in wood density in Japanese larch (Larix kaempferi). J Wood Sci 56:7–14

    Article  Google Scholar 

  • Garber SM, Maguire DA (2005) Vertical trends in maximum branch diameter in two mixed-species spacing trials in the central Oregon Cascades. Can J For Res 35:295–307

    Article  Google Scholar 

  • Gardiner B, Leban J-M, Auty D, Simpson H (2011) Models for predicting wood density of British-grown Sitka spruce. Forestry 84:119–132

    Article  Google Scholar 

  • Gartner BL (2005) Assessing wood characteristics and wood quality in intensively managed plantations. J For 103:75–77

    Google Scholar 

  • Grace JC, Pont D, Goulding CJ (1999) Modelling branch development for forest management. N Z J For Sci 29:391–408

    Google Scholar 

  • Harris JM, James RN, Collins MJ (1975) Case for improving wood density in radiata pine. N Z J For Sci 5:347–354

    Google Scholar 

  • Hein S, Mäkinen H, Yue C, Kohnle U (2007) Modelling branch characteristics of Norway spruce from wide spacings in Germany. For Ecol Manage 242:155–164

    Article  Google Scholar 

  • Houllier F, Leban JM, Colin F (1995) Linking growth modelling to timber quality assessment for Norway spruce. For Ecol Manage 74:91–102

    Article  Google Scholar 

  • Ikonen V-P, Kellomäki S, Peltola H (2003) Linking tree stem properties of Scots pine (Pinus sylvestris L.) to sawn timber properties through simulated sawing. For Ecol Manage 174:251–263

    Article  Google Scholar 

  • Ikonen V-P, Peltola H, Wilhelmsson L, Kilpeläinen A, Väisänen H, Nuutinen T, Kellomäki S (2008) Modelling the distribution of wood properties along the stems of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) as affected by silvicultural management. For Ecol Manage 256:1356–1371

    Article  Google Scholar 

  • Jordan L, Clark A III, Schimleck LR, Hall DB, Daniels RF (2008) Regional variation in wood specific gravity of planted loblolly pine in the United States. Can J For Res 38:698–710

    Article  Google Scholar 

  • Kellomäki S, Ikonen V-P, Peltola H, Kolström T (1999) Modelling the structural growth of Scots pine with implications for wood quality. Ecol Mod 122:117–134

    Article  Google Scholar 

  • Kershaw JA Jr, Benjamin JG, Weiskittel AR (2009) Approaches for modeling vertical distribution of maximum knot size in black spruce: a comparison of fixed- and mixed- effects nonlinear models. For Sci 55:230–237

    Google Scholar 

  • Knapic S, Seppä IP, Usenius A, Pereira H (2011) Stem modeling and simulation of conversion of cork oak stems for quality wood products. Eur J For Res 130:745–751

    Article  Google Scholar 

  • Koubaa A, Isabel N, Zhang SY, Beaulieu J, Bousquet J (2005) Transition from juvenile to mature wood in black spruce (Picea mariana (Mill.) B.S.P.). Wood Fiber Sci 37:445–455

    CAS  Google Scholar 

  • Larocque GR, Marshall PL (1995) Wood relative density development in red pine (Pinus resinosa Ait.) stands as affected by different initial spacings. For Sci 41:709–728

    Google Scholar 

  • Larson PR (1963) Stem form development of forest trees. Forest Science Monograph No. 5

    Google Scholar 

  • Larson PR, Kretschmann DE, Clark A III, Isebrands JG (2001) Formation and properties of juvenile wood in southern pines: a synopsis. USDA Forest Service, General Technical Report FPL-GTR-129

    Google Scholar 

  • Lasserre JP, Mason EG, Watt MS, Moore JR (2009) Influence of initial planting spacing and genotype on microfibril angle, wood density fibre properties and modulus of elasticity in Pinus radiata D. Don corewood. For Ecol Manage 258:1924–1931

    Article  Google Scholar 

  • Liu C, Zhang SY (2005) Models for predicting product recovery using selected tree characteristics of black spruce. Can J For Res 35:930–937

    Article  Google Scholar 

  • Liu J, Burkhart HE, Amateis RL (1995) Projecting crown measurements for loblolly pine trees using a generalized thinning response function. For Sci 41:43–53

    Google Scholar 

  • Love-Myers KR, Clark A III, Schimleck LR, Jokela EJ, Daniels RF (2009) Specific gravity responses of slash and loblolly pine following mid-rotation fertilization. For Ecol Manage 257:2342–2349

    Article  Google Scholar 

  • Maguire DA, Hann DW (1987) A stem dissection technique for dating branch mortality and reconstructing past crown recession. For Sci 33:858–871

    Google Scholar 

  • Maguire DA, Kershaw JA Jr, Hann DW (1991) Predicting the effects of silvicultural regime on branch size and crown wood core in Douglas-fir. For Sci 37:1409–1428

    Google Scholar 

  • Mäkelä A, Mäkinen H (2003) Generating 3D sawlogs with a process-based growth model. For Ecol Manage 184:337–354

    Article  Google Scholar 

  • Mäkela A, Grace JC, Deckmyn G, Kantola A, Campioli M (2010) Simulating wood quality in forest management models. For Syst 19(SI):48–68

    Google Scholar 

  • Mäkinen H, Colin F (1998) Predicting branch angle and branch diameter of Scots pine from usual tree measurements and stand structural information. Can J For Res 28:1686–1696

    Article  Google Scholar 

  • Mäkinen H, Colin F (1999) Predicting the number, death, and self-pruning of branches in Scots pine. Can J For Res 29:1225–1236

    Article  Google Scholar 

  • Mäkinen H, Hein S (2006) Effect of wide spacing on increment and branch properties of young Norway Spruce. Eur J For Res 125:239–248

    Article  Google Scholar 

  • Mäkinen H, Mäkelä A (2003) Predicting basal area of Scots pine branches. For Ecol Manage 179:351–362

    Article  Google Scholar 

  • Mäkinen H, Ojansuu R, Niemistö P (2003a) Predicting external branch characteristics of planted silver birch (Betula pendula Roth.) on the basis of routine stand and tree measurements. For Sci 49:301–317

    Google Scholar 

  • Mäkinen H, Ojansuu S, Sairanen P, Yli-Kojola H (2003b) Predicting branch characteristics of Norway spruce (Picea abies (L.) Karst.) from simple stand and tree measurements. Forestry 76:525–546

    Article  Google Scholar 

  • McAlister RH, Powers HR, Pepper WD (2000) Mechanical properties of stemwood and limbwood of seed orchard loblolly pine. For Prod J 50(10):91–94

    Google Scholar 

  • Megraw RA (1985) Wood quality factors in loblolly pine. Tappi Press, Atlanta, 88 pp

    Google Scholar 

  • Meredieu C, Colin F, Hervé J-C (1998) Modelling branchiness of Corsican pine with mixed-effect models (Pinus nigra Arnold spp. laricio (Poiret) Maire). Ann Sci For 55:359–374

    Article  Google Scholar 

  • Miles PD, Smith WB (2009) Specific gravity and other properties of wood and bark for 156 tree species found in North America. USDA Forest Service, Research Note NRS-38

    Google Scholar 

  • Mitchell KJ (1988) SYLVER: modelling the impact of silviculture on yield, lumber value, and economic return. For Chron 64:127–131

    Google Scholar 

  • Moberg L (1999) Variation in knot size of Pinus sylvestris in two initial spacing trials. Silva Fenn 33:131–144

    Google Scholar 

  • Moberg L (2000) Models of internal knot diameter for Pinus sylvestris. Scand J For Res 15:177–187

    Article  Google Scholar 

  • Moberg L (2001) Models of internal knot properties for Picea abies. For Ecol Manage 147:123–138

    Article  Google Scholar 

  • Moberg L (2006) Predicting knot properties of Picea abies and Pinus sylvestris from generic tree descriptors. Scand J For Res 21:48–61

    Article  Google Scholar 

  • Mora CR, Allen HL, Daniels RF, Clark A III (2007) Modeling corewood-outerwood transition in loblolly pine using wood specific gravity. Can J For Res 37:999–1011

    Article  Google Scholar 

  • Mörling T (2002) Evaluation of annual ring width and ring density development following fertilisation and thinning of Scots pine. Ann For Sci 59:29–40

    Article  Google Scholar 

  • Mutz R, Guilley E, Sauter UH, Nepveu G (2004) Modelling juvenile-mature wood transition in Scots pine (Pinus sylvestris L.) using nonlinear mixed-effects models. Ann For Sci 61:831–841

    Article  Google Scholar 

  • Nyakuengama JG, Downes GM, Ng J (2002) Growth and wood density responses to later-age fertilizer application in Pinus radiata. IAWA J 23:431–448

    Google Scholar 

  • Øvrum A, Vestøl GI, Høibø OA (2011) Modelling the effects of timber length, stand- and tree properties on grade yield of Picea abies timber. Scand J For Res 26:99–109

    Article  Google Scholar 

  • Pearson RG, Gilmore RC (1971) Characterization of the strength of juvenile wood of loblolly pine (Pinus taeda L.). For Prod J 21(1):23–31

    Google Scholar 

  • Pearson RG, Gilmore RC (1980) Effect of fast growth rate on the mechanical properties of loblolly pine. For Prod J 30(5):47–54

    Google Scholar 

  • Pinto I, Pereira H, Usenius A (2003) Analysis of log shape and internal knots in twenty Maritime pine (Pinus pinaster Ait.) stems based on visual scanning and computer aided reconstruction. Ann For Sci 60:137–144

    Article  Google Scholar 

  • Raymond CA, Joe B, Anderson DW, Watt DJ (2008) Effect of thinning on relationships between three measures of wood stiffness in Pinus radiata: standing trees vs. logs vs. short clear specimens. Can J For Res 38:2870–2879

    Article  Google Scholar 

  • Repola J (2006) Models for vertical wood density of Scots pine, Norway spruce and birch stems, and their application to determine average wood density. Silva Fenn 40:673–685

    Google Scholar 

  • Sauter UH, Mutz R, Munro BD (1999) Determining juvenile-mature wood transition in Scots pine using latewood density. Wood Fiber Sci 31:416–425

    CAS  Google Scholar 

  • Schneider R, Zhang SY, Swift DE, Bégin J, Lussier J-M (2008) Predicting selected wood properties of jack pine following commercial thinning. Can J For Res 38:2030–2043

    Article  Google Scholar 

  • Schultz EB, Matney TG (2006) An integrated growth and yield simulator for predicting loblolly pine dry weight pulp yields. Wood Fiber Sci 38:672–681

    CAS  Google Scholar 

  • Tasissa G, Burkhart HE (1997) Modeling thinning effects on ring width distribution in loblolly pine (Pinus taeda). Can J For Res 27:1291–1301

    Article  Google Scholar 

  • Tasissa G, Burkhart HE (1998a) Juvenile-mature wood demarcation in loblolly pine trees. Wood Fiber Sci 30:119–127

    CAS  Google Scholar 

  • Tasissa G, Burkhart HE (1998b) Modeling thinning effect on ring specific gravity of loblolly pine (Pinus taeda L.). For Sci 44:212–223

    Google Scholar 

  • Thörnqvist T (1993) Juvenile wood in coniferous trees. Document D13:1993. Swedish Council for Building Research, Stockholm

    Google Scholar 

  • Todaro L, Macchioni N (2011) Wood properties of young Douglas-fir in Southern Italy: results over a 12-year post-thinning period. Eur J For Res 130:251–261

    Article  Google Scholar 

  • Todoroki CL (1990) AUTOSAW system for sawing simulation. N Z J For Sci 20:332–348

    Google Scholar 

  • Tong QJ, Zhang SY (2006) Modelling jack pine lumber value recovery in relation to tree characteristics using Optitek simulation. For Prod J 56(1):66–72

    Google Scholar 

  • Trincado G, Burkhart HE (2008) A model of knot shape and volume in loblolly pine trees. Wood Fiber Sci 40:634–646

    CAS  Google Scholar 

  • Trincado G, Burkhart HE (2009) A framework for modeling the dynamics of first-order branches and spatial distribution of knots in loblolly pine trees. Can J For Res 39:566–579

    Article  Google Scholar 

  • Watt MS, Zoric B (2010) Development of a model describing modulus of elasticity across environmental and stand density gradients in plantation-grown Pinus radiata within New Zealand. Can J For Res 40:1558–1566

    Article  Google Scholar 

  • Weiskittel AR, Maguire DA, Monserud RA, Rose R, Turnblom EC (2006) Intensive management influence on Douglas-fir stem form, branch characteristics, and simulated product recovery. N Z J For Sci 36:293–312

    Google Scholar 

  • 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. For Ecol Manage 245:96–109

    Article  Google Scholar 

  • Yang K-C (1994) Impact of spacing on width and basal area of juvenile and mature wood in Picea mariana and Picea glauca. Wood Fiber Sci 26:479–488

    CAS  Google Scholar 

  • Zhang SY (1994) Mechanical properties in relation to specific gravity in 342 Chinese woods. Wood Fiber Sci 26:512–526

    CAS  Google Scholar 

  • Zhang SY (1997) Wood specific gravity-mechanical property relationship at species level. Wood Sci Technol 31:181–191

    Article  CAS  Google Scholar 

  • Zhang SY, Tong QJ (2005) Modeling lumber recovery in relation to selected tree characteristics in jack pine using sawing simulator Optitek. Ann For Sci 62:219–228

    Article  Google Scholar 

  • Zobel BJ, Sprague JR (1998) Juvenile wood in forest trees. Springer, Berlin

    Book  Google Scholar 

  • Zobel BJ, van Buijtenen JP (1989) Wood variation its causes and control. Springer, Berlin

    Book  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Forestry, Virginia Tech, Cheatham Hall 319, Blacksburg, VA, 24061, USA

    Harold E. Burkhart

  2. Instituto Superior de Agronomia DRAT, Universidade Técnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal

    Margarida Tomé

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  1. Harold E. Burkhart
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  2. Margarida Tomé
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Burkhart, H.E., Tomé, M. (2012). Modeling Wood Characteristics. In: Modeling Forest Trees and Stands. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3170-9_17

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