Radial variation of wood properties affects product recovery from veneer logs. In Eucalyptus nitens , the radial variation in wood density, microfibril angle and modulus of elasticity was described using non-linear models. The timing of radial change was trait-dependent, and the age at which thresholds for structural products were reached differed between sites.
Eucalyptus nitens is widely planted in cool temperate regions of the world. While mainly grown for pulpwood, rotary-peeled veneer is becoming important. Threshold levels of wood stiffness are required for using this veneer for structural purposes. Stiffness is determined by wood density and microfibril angle, which improve with tree age. The nature of this radial variation affects the recovery of suitable veneer and profitability of the plantation resource.
We model the radial variation of these veneer-critical wood properties and determine whether it varies with growing conditions.
We used logs from three 20–22-year-old Tasmanian plantations. Radial variations in wood density, microfibril angle and modulus of elasticity (measuring stiffness) were assessed using SilviScan. Eight linear and non-linear models were examined using cambial age as the independent variable.
The increases in wood density and modulus of elasticity with age were modelled by sigmoidal functions and the decrease in microfibril angle modelled by an asymptotic function. The timing of radial change was trait-dependent, and the mean ages at which thresholds for structural products were reached between sites.
Radial variation varied among sites and will likely impact the recovery of structural grade veneer from plantations.
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The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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We acknowledge Sustainable Timber Tasmania (former Forestry Tasmania) for assistance in project planning, access to sites, the provision of trees and staff, tree felling and disks preparation. Specifically, we thank: Paul Adams (former FT Senior Research Scientist & Principal Scientist Research); Chris Emmett (IST); Peter Wass, Crispen Marunda, Kristen Dransfield, Matt McCormic, Mitchell Fulford, Rowan Eiszele and Shane Burgess. We also thank CSIRO Land and Water for access to the laboratories and facilities, David Blackburn for field assistance and valued discussion, Chris Harwood for his suggestions and advice in the early stage of this research, and Mark Hunt from the ARC Training Centre for Forest Value for the continuing support of this research.
MV was supported by the Advanced Human Capital Program - CONICYT (Becas Chile) from the Chilean Government and a top-up from the Australian Cooperative Research Centre for Forestry. Research funding for the project was provided by The National Centre for Future Forest Industries (NCFFI) and ARC Training Centre for Forest Value (grant number IC150100004) at the University of Tasmania.
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Contributions of the co-authors
Conceptualisation: MV, MH, and BMP; methodology and data analysis: MV, MH, GD, PAH and BMP; data collection: MV and GD; writing, reviewing, and editing: MV, MH, GD, PAH and BMP.
Responsible editor: Jean-Michel Leban
Appendix 1. Testing the difference between trees within sites
Appendix 2. Analyses based on tree means
Unweighted disk means of wood properties were estimated as the averages of the ring wood property values from disk. Additionally, disk means were estimated by weighting ring means by ring area (weighted disk means), to allow a more accurate representation of the tree-level wood property means (Downes et al. 1997). This methodology assumed that rings were circular and that there was no pith eccentricity. The methodology of Medhurst et al. (2011) was used to quantify eccentricity to test this assumption. Using this measure for each tree, a one-way ANOVA was used to test the differences among the study sites using the anova function of R (R Development Core Team 2018).
Neither the conventional means (unweighted) nor the weighted means significantly differed among sites for wood density, MFA and MOE (Table 6). While the study sites ranked similarly for MFA and MOE based on individual means (unweighted and weighted), wood density did not follow this trend. For example, when differences in wood density were assessed using unweighted means, Strathblane ranked highest for wood density; however, Geeveston ranked above Strathblane when using the weighted disk mean wood density (Table 6).
Disk eccentricity had an average of less than 10% for each site and did not differ among these sites (F2,22 = 1.1, P > 0.05), arguing that the weighted means are a good estimate of the overall difference among sites. With the weighted mean values, wood density was lowest at Florentine but its site mean was not significantly different from Strathblane and Geeveston, according to a Tukey-Kramer multiple comparison test. Unweighted disk means were consistently lower than those based on the area weighted disk means
Appendix 3. Comparisons between inner and outer samples
At a broad scale, the pith-to-cambium change in wood properties was investigated by comparing the inner (adjacent to the pith) and outer (adjacent to the cambium) samples from each tree, with the difference expressed as a percentage of the innermost sample. The samples were chosen as the two innermost and two outermost rings or, following Downes et al. (2014), the innermost and outmost 10% of cross-sectional area. Using this tree-level data, (i) a t test was undertaken separately for each site and wood property to test the statistical significance from zero of the difference between the innermost and outermost samples, and (ii) a one-way ANOVA was undertaken to test for the difference in change among sites, with Tukey-Kramer multiple comparisons applied to compare site means. These analyses were undertaken using cambial age and percentage of area data for each wood property with the t.test and anova functions in R (R Development Core Team 2018).
At each site, all wood properties exhibited a significant difference between innerwood and outerwood (t test from zero; P < 0.05). The wood density and MOE of outerwood were higher than those of innerwood (11.4 to 31.0% and 86.2 to 137.5% higher, respectively, depending upon site), and MFA was lower (− 52.5 to − 60.3% of inner sample), regardless of whether the ring or percentage area data as used (Table 7).
Sites did not differ significantly in the magnitude of the difference in MFA and MOE between innerwood and outerwood, and only when expressed in terms of percentage was there a significant difference for wood density (P < 0.05). Wood density of Geeveston and Strathblane had the greatest and smallest difference between the innermost and outermost wood, respectively.
The rank order of sites and the magnitude of the change in all response variables remained the same, regardless of how the comparison was made and whether sites were significantly different. In wood density, Strathblane showed the least change between pith and cambium, followed by Florentine and Geeveston. On the other hand, Strathblane continued showing the least change, but followed by Geeveston instead of Florentine (Table 7).
Appendix 4. Summary of wood properties by site
Appendix 5. Models selected at site level data
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Vega, M., Hamilton, M., Downes, G. et al. Radial variation in modulus of elasticity, microfibril angle and wood density of veneer logs from plantation-grown Eucalyptus nitens. Annals of Forest Science 77, 65 (2020). https://doi.org/10.1007/s13595-020-00961-1
- Juvenile wood
- Structural plywood