Effects of Growth and Treatment Conditions on the Quality of Norway Spruce (Picea abies L.) Sawn Timber
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sample Materials
2.2. Visual Grading and Mechanical Testing
2.3. Description of Data Analysis
3. Results
3.1. Visual Grading of Spruce Sawn Timber
3.2. Mechanical Properties of Sawn Timber in Dependence of the Study Site
3.3. Relationships of Tree Anatomy and Visual Board Properties
3.4. Ordinal Models for Board Quality in Dependence of Visual Properties
3.5. Ordinal Model for Board Quality Based on Tree Architecture and Forest Parameters
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Puettmann, K.J. Silvicultural Challenges and options in the Context of Global Change: “Simple” Fixes and Opportunities for New Management Approaches. J. For. 2011, 109, 321–331. [Google Scholar]
- Temperli, C.; Bugmann, H.; Elkin, C. Adaptive management for competing forest goods and services under climate change. Ecol. Appl. 2012, 22, 2065–2077. [Google Scholar] [CrossRef] [PubMed]
- D’Amato, A.W.; Bradford, J.B.; Fraver Sand Palik, B.J. Effects of thinning on drought vulnerability and climate response in north temperate forest ecosystems. Ecol. Appl. 2013, 23, 1735–1742. [Google Scholar] [CrossRef]
- Müller, F.; Augustynczik AL, D.; Hanewinkel, M. Quantifying the risk mitigation efficiency of changing silvicultural systems under storm risk throughout history. Ann. For. Sci. 2019, 76, 116. [Google Scholar] [CrossRef]
- Yousefpour, R.; Gray, D.R. Managing forest risks in uncertain times of climate change. Ann. For. Sci. 2022, 79, 16. [Google Scholar] [CrossRef]
- Sharma, R.P.; Vacek, Z.; Vacek, S. Modeling individual tree height to diameter ratio for Norway spruce and European beech in Czech Republic. Trees 2016, 30, 1969–1982. [Google Scholar] [CrossRef]
- Šilinskas, B.; Varnagirytè-Kabašinskiene, I.; Aleinikovas, M.; Benušiene, L.; Aleinikovienè, J.; Škėma, M. Scots Pine and Norway Spruce Wood Properties at Sites with Different Stand Densities. Forests 2020, 11, 587. [Google Scholar] [CrossRef]
- Pretzsch, H. Density and growth of forest stands revisited. Effect of the temporal scale of observation, site quality, and thinning. For. Ecol. Manag. 2020, 460, 117879. [Google Scholar] [CrossRef]
- Valentine, H.T.; Mäkelä, A.; Green, E.J.; Amateis, R.L.; Mäkinen, H.; Ducey, M.J. Models relating stem growth to crown length dynamics: Application to Loblolly pine and Norway spruce. Trees 2012, 26, 469–478. [Google Scholar] [CrossRef]
- Bianchi, S.; Huuskonen, S.; Hynynen, J.; Siipilehto, J.; Niemistö, P. Tree-level differences in Norway spruce and Scots pine growth after extreme thinning treatments. Scand. J. For. Res. 2022, 37, 109–118. [Google Scholar] [CrossRef]
- Jaakkola, T.; Mäkinen, H.; Saranpää, P. Wood density of Norway spruce: Responses to timing and intensity of first commercial thinning and fertilization. For. Ecol. Manag. 2006, 237, 513–521. [Google Scholar] [CrossRef]
- Bobinac, M.; Andrasev, S.; Bauer-Zivkovic, A.; Susic, N. Effects of Heavy Thinnings on the increment and stability of a Norway spruce stand and its trees between the ages of 32 and 50. Sumar. List 2018, 142, 33–46. [Google Scholar]
- Kolář, T.; Dobrovolný, P.; Szabó, P.; Mikita, T.; Kyncl, J.; Sochova, I.; Rybníček, M. Wood species utilization for timber constructions in the Czech lands over the period 1400–1900. Dendrochronologia 2021, 70, 125900. [Google Scholar] [CrossRef]
- Høibø, O.; Vestøl, G.I.; Fischer, C.; Fjeld, L.; Øvrum, A. Bending properties and strength grading of Norway spruce: Variation within and between stands. Can. J. For. Resour. 2014, 44, 128–135. [Google Scholar] [CrossRef]
- Linke, G. Festigkeitssortierung Von Holzbauteilen Beim Bauen Im Bestand–Ein Beitrag Zur Substanzschonenden Erhaltung Historischer Gebäude. Doctoral Dissertation, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany, 2023. [Google Scholar]
- DIN 4074-1; Strength Grading of Wood–Part 1: Coniferous Sawn Timber. Deutsches Institut für Normung e.V., Beuth Press GmbH: Berlin, Germany, 2012.
- Roblot, G.; Coudegnat, D.; Bleron, L.; Collet, R. Evaluation of the visual stress grading standard on French Spruce (Picea excelsa) and Douglas-fir (Pseudotsuga menziesii) sawn timber. Ann. For. Sci. 2008, 65, 812. [Google Scholar] [CrossRef]
- Algin, Z. Multivariate performance optimization of scaffold boards with selected softwood defects. Constr. Build. Mater. 2019, 220, 667–678. [Google Scholar] [CrossRef]
- Stapel, P.; van de Kuilen, J.-W.G. Influence of cross-section and knot assessment on the strength of visually graded Norway spruce. Eur. J. Wood Wood Prod. 2013, 72, 213–227. [Google Scholar] [CrossRef]
- Hu, M.; Olsson, A.; Johansson, M.; Oscarsson, J. Modelling local bending stiffness based on fiber orientation in sawn timber. Eur. J. Wood Wood Prod. 2018, 76, 1605–1621. [Google Scholar] [CrossRef]
- Briggert, A.; Olsson, A.; Oscarsson, J. Prediction of tensile strength of sawn timber: Models for calculation of yield in strength classes. Mater. Struct. 2020, 53, 53–55. [Google Scholar] [CrossRef]
- Viguier, J.; Jehl, A.; Collet, R.; Bleron, L.; Meriaudeau, F. Improving strength grading of lumber by grain angle measurement and mechanical modeling. Wood Mater. Sci. Eng. 2015, 10, 145–156. [Google Scholar] [CrossRef]
- Auty, D.; Achim, A.; Macdonald, E.; Cameron, A.D.; Gardiner, B.A. Models for Predicting Clearwood Mechanical properties of Scots Pine. For. Sci. 2016, 62, 403–413. [Google Scholar] [CrossRef]
- Olofsson, L.; Broman, O.; Oja, J.; Sandberg, D. Product-Adapted Grading of Scots pine Sawn Timber by an industrial CT-scanner Using a Visually-Trained Machine-Learning Method. Wood Mater. Sci. Eng. 2021, 16, 279–286. [Google Scholar] [CrossRef]
- Burawska-Kupniewska, I.; Krzosek, S.; Mańkowski, P. Mechanical Properties of Machine Stress Graded Sawn Timber Depending on the Log Type. Forests 2021, 12, 532. [Google Scholar] [CrossRef]
- Burawska-Kupniewska, I.; Krzosek, S.; Mańkowski, P. Efficiency of Visual and Machine Strength Grading of Sawn Timber with Respect to Log Type. Forests 2021, 12, 1467. [Google Scholar] [CrossRef]
- Rais, A.; Pretzsch, H.; van de Kuilen, J.-W.G. Roundwood pre-grading with longitudinal acoustic waves for production of structural boards. Eur. J. Wood Wood Prod. 2014, 72, 87–98. [Google Scholar] [CrossRef]
- Hecker, M.; Ressmann, J.; Becker, G.; Merforth, C. Prognose der Schnittholz-Qualität auf der Grundlage der Rundholz-Sortierung. Eur. J. Wood Wood Prod. 2000, 58, 168–176. [Google Scholar] [CrossRef]
- Houllier, F.; Leban, J.-M.; Colin, F. Linking growth modelling to timber quality assessment for Norway spruce. For. Ecol. Manag. 1995, 74, 91–102. [Google Scholar] [CrossRef]
- Kliger, I.R.; Perstorper, M.; Johansson, G.; Pellicane, P.J. Quality of timber products from Norway spruce. Part 3. Influence of spatial position and growth characteristics on bending stiffness and strength. Wood Sci. Technol. 1995, 29, 397–410. [Google Scholar]
- Brüchert, F.; Becker, G.; Speck, T. The mechanics of Norway spruce [Picea abies (L.) Karst]: Mechanical properties of standing trees from different thinning regimes. For. Ecol. Manag. 2000, 145, 45–62. [Google Scholar] [CrossRef]
- Lindström, H. Intra-Tree Models of Basic Density in Norway Spruce as an Input to Simulation Software. Silva Fenn. 2000, 34, 411–421. [Google Scholar] [CrossRef]
- Kuprevicius, A.; Auty, D.; Achim, A.; Caspersen, J.P. Quantifying the influence of live crown ratio on the mechanical properties of clear wood. Forestry 2013, 86, 361–369. [Google Scholar] [CrossRef]
- Krajnc, L.; Farrelly, N.; Harte, A.N. The influence of crown and stem characteristics on timber quality in softwoods. For. Ecol. Manag. 2019, 435, 8–17. [Google Scholar] [CrossRef]
- Øvrum, A. In-forest assessment of timber stiffness in Norway spruce (Picea abies (L.) Karst.). Eur. J. Wood Wood Prod. 2013, 71, 429–435. [Google Scholar] [CrossRef]
- Stöd, R.; Marttila, J.; Tomppo, L.; Haapala, A.; Verkasalo, E. Modulus of Elasticity and Bending Strength of Scots Pine (Pinus sylvestris L.) Wood from Commercial Thinnings. Forests 2024, 15, 567. [Google Scholar] [CrossRef]
- Nagelkerke, N.J. A note on a general definition of the coefficient of determination. Biometrika 1991, 78, 691–692. [Google Scholar] [CrossRef]
- Hu, B.; Shao, J.; Palta, M. Pseudo-R2 in logistic regression model. Stat. Sin. 2006, 16, 847–860. [Google Scholar]
- Fagerland, M.W.; Hosmer, D.W. Tests for goodness of fit in ordinal logistic regression models. J. Stat. Comput. Simul. 2016, 86, 3398–3418. [Google Scholar] [CrossRef]
- Hoewler, K.; Seidel, D.; Krenn, T.; Berthold, D.; Ehbrecht, M.; Mueller, J.; Kietz, B. Evaluation of softwood timber quality—A case study on two silvicultural systems in central Germany. Forests 2022, 13, 1910. [Google Scholar] [CrossRef]
- DIN EN 408; Timber Structures–Structural Timber and Glued Laminated Timber–Determination of Some Physical and Mechanical Properties; German Version EN 408:2010+A1:2012. Deutsches Institut für Normung e.V., Beuth Press GmbH: Berlin, Germany, 2012.
- DIN EN 384; Structural Timber-Determination of Characteristic Values of Mechanical Properties and Density; German Version EN 384:2016+A1:2018. Deutsches Institut für Normung e.V., Beuth Press GmbH: Berlin, Germany, 2018.
- DIN EN 338; Structural Timber–Strength Classes; German Version EN 338:2016. Deutsches Institut für Normung e.V., Beuth Press GmbH: Berlin, Germany, 2016.
- Nakagawa, S.; Johnson, P.C.D.; Schielzeth, H. The coefficient of determination R2 and Intra-class correlation coefficient from generalized linear mixed-effects models revisited and explained. J. R. Soc. Interface 2017, 14, 20170213. [Google Scholar] [CrossRef]
- Wilks, D.S. Statistical Methods in the Atmospheric Sciences; Academic Press: San Diego, CA, USA, 2005; Chapter 7. [Google Scholar]
- Brant, R. Assessing proportionality in the proportional odds model for ordinal logistic regression. Biometrics 1990, 46, 1171–1178. [Google Scholar] [CrossRef]
- Christensen, R.H.B. A Tutorial on Fitting Cumulative Link Mixed Models with clmm2 from the Ordinal Package. 2023. Available online: https://cran.r-project.org/web/packages/ordinal/vignettes/clmm2_tutorial.pdf (accessed on 1 July 2024).
- Piermattei, A.; von Arx, G.; Avanzi, C.; Fonti, P.; Gärtner, H.; Piotti, A.; Urbinati, C.; Vendramin, G.G.; Büntgen, U.; Crivellaro, A. Functional Relationships of Wood Anatomical Traits in Norway Spruce. Front. Plant Sci. 2020, 11, 683. [Google Scholar] [CrossRef] [PubMed]
- Kankare, V.; Joensuu, M.; Vauhkonen, J.; Tanhuanpää, T.; Vastaranta, M.; Hyyppä, J.; Hyyppä, H.; Alho, P.; Rikala, J.; Sipi, M. Estimation of the Timber Quality of Scots Pine with Terrestrial Laser Scanning. Forests 2014, 5, 1879–1895. [Google Scholar] [CrossRef]
- Llana, F.D.; Short, I.; Harte, A.M. Use of non-destructive test methods on Irish hardwood standing trees and small-diameter round wood timber for prediction of mechanical properties. Ann. For. Sci. 2020, 77, 62. [Google Scholar] [CrossRef]
- Villanueva, J.L. Mechanical Evaluation of Spanish Juniper (Junipera thurifera L.) Round Timber from Castilla y León. Visual Strength Grading and Resonance Evaluation. Final Project Degree. E.T.S.I. Agraria. University of Lleida. Lérida, Spain. 2009. Available online: http://hdl.handle.net/10459.1/45926 (accessed on 11 June 2024).
- Bertoldo, C. Predicting of Strength and Stiffness of Wood Using Acoustic Measurement in Trees. Ph.D. Dissertation, Faculdade de Enghenaria Agrícola, Universidade Estadual de Campinas, Campinas, SP, Brazil, 2014; 146p. [Google Scholar]
- Butler, M.A.; Dahlen, J.; Eberhardt, T.L.; Montes, C.; Antony, F.; Daniels, R.F. Acoustic evaluation of loblolly pine tree- and lumber-length logs allows for segregation of lumber modulus of elasticity, not for modulus of rupture. Ann. For. Sci. 2017, 74, 20. [Google Scholar] [CrossRef]
- Moore, J.R.; Lyon, A.Y.; Searles, G.J.; Lehneke, S.A.; Ridley-Ellis, D.J. Within- and between-stand variation in selected properties of Sitka spruce sawn timber in the UK; implications for segregation and grade recovery. Ann. For. Sci. 2013, 70, 403–415. [Google Scholar] [CrossRef]
Stand | 1 | 2 | 3 | 4 | 5 | 6 |
---|---|---|---|---|---|---|
Age (years) | 44 | 41 | 83 | 80 | 80 | 39 |
Thinning System | TFB | TFA | TFB | TFA | TFB | TFA |
Slope 1 | N | N | NW-W | N | S | S |
Altitude (m) | 450–520 | 450–490 | 430–520 | 551–600 | 501–550 | 551–600 |
Basal area (m2∙ha−1) | 37.6 | 34.1 | 37.2 | 37.1 | 28.3 | 35 |
Mean height (m) | 21.6 | 25.3 | 29.8 | 33.8 | 28.2 | 20.5 |
Mean Diameter at Breast Height (cm) | 26.9 | 28.5 | 32.3 | 46.3 | 42.4 | 28.6 |
Soil condition | Mesotrophic | Mesotrophic | Mesotrophic | Mesotrophic | Mesotrophic | Mesotrophic |
Water supply | Moderately Fresh | Moderately Fresh | Moderately Fresh | Fresh | Fresh | Fresh |
Last Thinning (m3∙ha−1 ∙year−1) | - (-) | 59 (2012) | 71 (2012) | 12.7 (2018) | 25.9 (2014) | 41.3 (2014) |
Stand | 1 | 2 | 3 | 4 | 5 | 6 | Normality | Variance | |
---|---|---|---|---|---|---|---|---|---|
Mechanical properties | Shapiro–Wilk | Levene’s Test | |||||||
b,c | b,c | a | c | b | c | >0.92 | 0.02 | ||
440.35 | 432.80 | 530.15 | 402.85 | 453.73 | 400.30 | ||||
MoR | b,c | b,c | a | b | b | c | >0.06 | 0.42 | |
35.51 | 32.53 | 48.82 | 34.69 | 37.11 | 21.52 | ||||
MoE g | b,c | b,c | a | c | b | d | >0.15 | 0.01 | |
12,081.12 | 11,478.87 | 16,802.37 | 10,958.28 | 13,298.28 | 7631.91 |
Effect Strength | Estimators | f.e. | r.e. | Correlation Coefficients | |||||
---|---|---|---|---|---|---|---|---|---|
Visual Criteria | CB | CR | TH | R2m | R2c | CB | CR | TH | HDR |
SK | 0.006 | 0.054 | 0.002 | 0.21 | 0.28 | −0.11 | 0.34 | 0.14 | −0.29 |
KC | −0.001 | 0.005 | 0.011 | 0.06 | 0.57 | −0.18 | −0.14 | −0.23 | 0.21 |
FA | 0.002 | 0.003 | 0.02 | 0.16 | 0.05 | −0.04 | −0.31 | −0.18 | |
GRW | 0.030 | 0.386 | 0.04 | 0.22 | −0.08 | 0.12 | −0.23 | −0.36 | |
TW | −1.4 × 10−5 | 4.3 × 10−5 | 0.01 | 0.06 | −0.04 | −0.03 | −0.01 | 0.04 | |
CW | −0.005 | −0.009 | −0.001 | 0.01 | 0.33 | −0.03 | 0.28 | 0.35 | −0.22 |
Correlations | SK | KC | FA | GRW | TW | CW | MoE | MoR | Quadratic Model adj. R2 |
---|---|---|---|---|---|---|---|---|---|
MoE | −0.29 | −0.34 | −0.20 | −0.48 | −0.49 | 0.03 | 0.54 | ||
MoR | −0.27 | −0.32 | −0.18 | −0.41 | −0.33 | 0.10 | 0.79 | 0.40 | |
Density | −0.15 | −0.18 | −0.09 | −0.32 | −0.3 | 0.22 | 0.65 | 0.51 | |
CLM | Coefficients | R2 Nagelkerke | |||||||
Strength class | 0.88 | −1.65 | −4.41 | −0.41 | −168.53 | 0.27 | |||
reject|C16 | C16|C24 | C24|C30 | |||||||
thresholds | −4.47 | −2.25 | −1.64 |
Pr(>|z|) | HDR | CB | TH | WS.fresh | Silv.TFB | CS | AIC | Likelihood Ratio Test |
---|---|---|---|---|---|---|---|---|
CLM 1 | 0.026 | 311.26 | - | |||||
CLM 2 | 0.081 | 0.004 | 304.61 | 0.003 | ||||
CLM 3 | 0.014 | 0.001 | 0.019 | 301.04 | 0.018 | |||
CLM 4 | 0.817 | 0.002 | 0.007 | 0.057 | 299.27 | 0.052 | ||
CLM 5 | 0.419 | 0.719 | 0.000 | 0.016 | 0.000 | 275.88 | 0.000 | |
CLM 6 | 0.383 | 0.434 | 0.023 | 0.018 | 0.000 | 0.554 | 257.84 | 0.552 |
AIC is distorted by missing values in the data of the crown surface | ||||||||
CLM 5 Estimators | −0.01 | −0.02 | 0.17 | −1.20 | 2.58 | |||
Threshold | reject|C16 | C16|C24 | C24|C30 | R2N | p value | |||
Coefficients | 1.51 | 4.1 | 4.9 | 0.35 | 2.6 × 10−9 |
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Krenn, T.; Berthold, D.; Ritter, N.; Kietz, B. Effects of Growth and Treatment Conditions on the Quality of Norway Spruce (Picea abies L.) Sawn Timber. Forests 2024, 15, 1588. https://doi.org/10.3390/f15091588
Krenn T, Berthold D, Ritter N, Kietz B. Effects of Growth and Treatment Conditions on the Quality of Norway Spruce (Picea abies L.) Sawn Timber. Forests. 2024; 15(9):1588. https://doi.org/10.3390/f15091588
Chicago/Turabian StyleKrenn, Tobias, Dirk Berthold, Nina Ritter, and Bettina Kietz. 2024. "Effects of Growth and Treatment Conditions on the Quality of Norway Spruce (Picea abies L.) Sawn Timber" Forests 15, no. 9: 1588. https://doi.org/10.3390/f15091588