Prediction of Wood Quality in Small-Diameter Douglas-Fir Using Site and Stand Characteristics


  • C. D. Morrow
  • T. M. Gorman
  • J. W. Evans
  • D. E. Kretschmann
  • C. A. Hatfield


Douglas-fir, nondestructive, MOE, prediction, soil, stand, least limiting water range (LLWR)


Standing stress wave measurements were taken on 274 small-diameter Douglas-fir trees in western Montana. Stand, site, and soil measurements collected in the field and remotely through geographical information system (GIS) data layers were used to model dynamic modulus of elasticity (DMOE) in those trees. The best fit linear model developed resulted in an adjusted R2 = 0.52 for predictions of individual tree DMOE and an R2 = 0.85 for predictions averaged on a stand basis. The linear model used was mean annual increment-1, total tree height, and a GIS-based estimate of soil bulk density. Logical models were also developed to predict membership in dichotomous DMOE categories with 71-82% selected trees meeting their respective DMOE criteria. The inverse relationship between soil bulk density and DMOE could be explained by the soil-tree moisture interactions know as least limiting water range.


Adams HD, Kold TE (2004) Drought responses of conifers in ecotone forests of northern Arizona: Tree ring growth and leaf C13. Oecologia 140(2):217-225.nBerg RB, Lonn JD (1996) The preliminary geologic map of the Nez Perce Pass 30' x 60' quadrangle, Montana, revised 1999, Montana Bureau of Mines and Geology: Open-File Report 339.'> H (1972) Nitrogen fertilization and water effects on photosynthesis and earlywood-latewood production in Douglas-fir. Can J For Res 2(4):467-478.nBurns RM, Honkala BH (1990) Douglas-fir in Silvics of North America: 1 Conifers. Vol. 2. Agric Handb 654 USDA For Serv, Washington, DC. 877 pp.nChauhan S, Walker J (2006) Variations in acoustic velocity and density with age, and their interrelationships in radiata pine. For Ecol Mgmt 229(1-3):388-394.nDa Silva AP, Kay BD, Perfect E (1994) Characterization of the least limiting water range of soils. Soil Sci Soc Am J 58(6):1775-1781.nFPL (1965) Western wood density survey. Res Pap FPL-27. USDA For Serv Forest Prod Lab, Madison, WI. 58 pp.nGrabianowski M, Manley B, Walker J (2006) Acoustic measurements on standing trees, logs and green lumber. Wood Sci Technol 40(3):205-216.nGreen DW, Gorman TM, Evans JW, Murphy JF, Hatfield CA (2008) Grading and properties of small-diameter Douglas-fir and ponderosa pine tapered logs. Forest Prod J 58(11):33-41.nGreen DW, Lowell EC, Hernandez R (2005) Structural lumber from dense stands of small-diameter Douglas-fir trees. Forest Prod J 55(7/8):42-50.nJohnson G, Grotta A, Gartner B, Downes G (2005) Impact of the foliar pathogen Swiss needle cast on wood quality of Douglas-fir. Can J For Res 35(2):331-339.nJosza LA, Brix H (1989) The effects of fertilization and thinning on wood quality of a 24-year-old Douglas-fir stand. Can J For Res 19(9):1137-1145.nLei YC, Zhang SY, Jiang Z (2005) Models for predicting lumber bending MOR and MOE based on tree and stand characteristics in black spruce. Wood Sci Technol 39 (1):37-47.nLetey J (1985) Relationship between soil physical properties and crop rotation. Pages 277-294 in BA Stewart, ed. Advances in soil science. Springer-Verlag, New York, NY.nLiu C, Zhang SY, Cloutier A, Rycabel T (2007) Modeling lumber bending stiffness and strength in natural black spruce stands using stand and tree characteristics. For Ecol Mgmt 242(2-3):648-655.nRobertson EO, Jozsa LA, Spittlehouse DL (1990) Estimating Douglas-fir wood production from soil and climate data. Can J For Res 20(3):357-364.nSchoenholtz SH, Van Miegroet H, Burger JA (2000) A review of chemical and physical properties as indicators of forest soil quality: Challenges and opportunities. For Ecol Mgmt 138(1-3):335-356.nUSDA (2004a) Potential vegetation type (PVT) classification of western Montana and northern Idaho (2004). Vector digital data. USDA Forest Service, Northern Region, Missoula, MT. Region 1 Research Station. By permission from Dan Loeffler.nUSDA (2004b) Wetness difference: Region 1 Vegetation mapping project (R1-VMP). Raster digital data. USDA Forest Service, Northern Region, Missoula, MT. Region 1 Research Station. By permission from Dan Loeffler.nUSGS-NRCS (2006) Soil survey database for Bitterroot National Forest area, Montana, 2006. Vector digital data.'>http://soildatamart.nrcs.usda.govnWang X, Carter P, Ross R, Brashaw B (2007) Acoustic assessment of wood quality of raw forest materials—A path to increased profitability. Forest Prod J 57(5):6-14.nWatt MS, Clinton PW, Coker G, Davis MR, Simcock R, Parfitt RL, Dando J (2008)Modeling the influence of environment and stand characteristics on basic density and modulus of elasticity for young Pinus radiata and Cupressus lusitanica. For Ecol Mgmt 255(3):1023-1033.nWolfe R, Murphy J (2005) Strength of small-diameter round and tapered bending members. Forest Prod J 55(3):50-55.nZahner R, Lotan J, Baughman W (1964) Earlywood-latewood features of red pine grown under simulated drought and irrigation. Forest Sci 10(3):361-370.n






Research Contributions