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Article

Results of a 57-Year-Long Research on Variability of Wood Density of the Scots Pine (Pinus sylvestris L.) from Different Provenances in Poland

by
Jarosław Szaban
,
Tomasz Jelonek
*,
Alicja Okińczyc
and
Wojciech Kowalkowski
Faculty of Forestry and Wood Technology, Poznan University of Life Sciences, Wojska Polskiego Str. 71 A, 60-625 Poznan, Poland
*
Author to whom correspondence should be addressed.
Forests 2023, 14(3), 480; https://doi.org/10.3390/f14030480
Submission received: 31 December 2022 / Revised: 15 February 2023 / Accepted: 21 February 2023 / Published: 27 February 2023
(This article belongs to the Section Wood Science and Forest Products)
Browse Figures
Versions Notes

Abstract

:
This research was conducted in the forests of Poland between 2019 and 2022. The aim was to study Scots pine provenances and compare the wood density variability among the various provenances growing on one experimental plot (in situ). The experiment was established in 1962 in the Zielonka Forest Division, Potasze Forest District. In 2019, five model trees from each provenance, which grew on the experimental plot, were chosen. In total, 40 trees were cut down, from which samples were collected in order to determine their wood density variability. The results indicate significant differences among the Scots pine provenances. It is not necessary to repeat it in situ. It appears that genetic factors highly impact the process of forming the wood density of the Scots pine. The research revealed that the best-quality wood, as far as wood density is concerned, comes from the Zielonka provenance, whereas the lowest relative density comes from the Gleboki Brod provenance. Both the provenance experiments and the analyses allowed for the selection of the research material that indicated the best genetic properties. Moreover, the research provides analytical tools that will allow for the prediction of the Scots pine provenance with the best quality together with high resistance to exogenous factors, such as habitat conditions, which can be vital to improving wood quality.

1. Introduction

Despite significant technological advancements and a trend toward substituting wooden products with new generation materials, the demand for wood remains high. Among the issues that are quite often mentioned in the literature of the subject is the shortage of wood [1], and studies describing the levels of interpopulation differentiation provide a variety of choices to achieve the best-quality wood and production of wood [2,3,4,5,6,7,8,9,10,11].
Wood density is an important element in determining the potential use of wood and its applicability and technical quality [12,13,14]. It is one of the most often described and studied wood properties, as physical, mechanical, and technological properties are conditioned by wood density [15,16,17,18,19]. Both properties, density and porosity, are informative as far as the microstructure, macrostructure, and weight of the wood are concerned. In addition, they are also explicitly linked to basic wood properties, such as cell wall chemical composition and the anatomical structure of xylem. Therefore, wood density seems to be a perfect wood property that enables us to describe many characteristics of wood tissues.
The structure and properties of wood are determined by genetic, environmental, and anthropogenic factors [20]. From the listed predispositions, genetic predispositions appear to be essential to shaping the value and quality of wood; hence, the literature of the subject matter pays them a lot of attention [21,22,23,24,25,26]. Despite ongoing research, the problem of locating and determining the genes responsible for the formation of xylem is still not fully understood.
Wood growth depends on many factors, including environmental conditions and anthropogenic activities. These factors, together with trees’ genotypes, affect the formation of wood tissues [27,28]. The literature that describes the influence on the qualitative and quantitative formation of wood properties is extensive. Exogenous factors that impact the growth of trees and tree stands and the macro- and microstructure of wood have been described by many authors [16,18,29,30,31,32,33].
The geographical scope and adaptability to various conditions are the reasons why the Scots pine is characterized by exceptional morphological diversity. This sparked interest in the area long before modern genetics had been created [34,35,36,37,38,39,40,41]. The research allows for the determination of inherited differences and the comparison of the biological characteristics of particular provenances. It also allows for the determination of the interdependence between biometrical and breeding features [42,43,44]. Despite over 100-year-long research on the provenances in Poland, the data concerning genetic variations in the population contain vague and ambiguous elements, which make the research on the subject matter uncompleted [45].
As far as the influence of provenance on the wood quality is concerned, it is necessary for the trees to reach a suitable age to undergo the analysis, which makes the research difficult and long lasting. So far, a number of studies have been conducted on young trees [46,47,48,49,50,51]. The possibility to collect samples from the unique 57-year-old research area enabled comparative studies of the trees at various stages of maturity.

2. Material and Methods

The research material was collected from a plot established in 1962 by the Department of Forest Silviculture in the Zielonka Experimental Forest Division, Potasze Forest District (52.52712 N, 17.02469 E). The methodical assumptions that were agreed upon at the beginning of the experiment were described by Rzeznik and Handel [52]. The seedlings used to set up the provenance experiment were collected from eight known sources of Scots pine in Poland, which are as follows: Woziwoda, Rospuda, Dluzek, Zielonka, Gleboki Brod, Radawnica, Bartel Wielki, and Lipowa (Figure 1). The pine population that grows in these locations is characterized by wood of high technological quality.
The experimental plot consisted of 16 lots of 1400 m2 each. Each of the eight provenances was distributed at random over two lots. The lots were of the same dimensions, and over 1000 1-year-old pine seedlings were planted. The initial cultivation spacing was 1.4 × 0.5 m. The experimental plot consisted of even-aged pine monocultures, which were distinguished by intense interindividual competition.
In 2019, model trees, which represented each particular provenance, were chosen from the area (Table 1). Each provenance was given the following codes: 1—Woziwoda; 2—Rospuda; 3—Dluzek; 4—Zielonka; 5—Gleboki B.; 6—Radawnica; 7—Bartel W.; 8—Lipowa.
In order to select the trees from each provenance, the DBH of all the trees was measured with a calliper, as well as the height of the trees in proportion to their number in the degree of thickness. On the basis of the thickness–height characteristics of the trees and following the Ulrich model (variant 2), 40 model trees were selected [53]. The trees chosen from each of the studied provenances were similar to each other as far as tree crown cover and other biometric features are concerned. Five trees from each provenance were selected, and special attention was paid to ensuring that no visible defects of the trunk occurred, such as hollows, bracket fungus, rot, or any mechanical damage. The geographical north was determined for each tree. After felling and hewing the trees, the next step included preparing cross-sewing logs of 1.35 m in length. The end part of the log was 1 m high, and the upper end had a height of 2.35 m.
The collected material was transported to a sawmill, where a 20 mm thick middle plank was cut from each log, and special attention was paid to the point where the geographical north had been determined. Two strips (caption 1 and 2 in Figure 2) were cut (1.35 m long and 20 mm×20 mm wide) from the north part of each plank in the girth adjacent layer, and the samples were prepared from them (dimensions: 20 mm (tangential) × 20 mm (radial) ×30 mm (longitudinal). Out of the 1000 samples prepared from each provenance, 900 model samples were chosen. In total, 713 pieces of the material were analyzed. The samples were identical to one another and without any visible defects. Figure 2 depicts a diagram of the material collection for the laboratory analysis.
The measurement of relative wood density is defined as the ratio of the amount of actual wood (in an absolutely dry state) to the volume of wood with a moisture content equal to or higher than the fiber saturation point [54]. In order to obtain an absolutely dry material, the samples were placed in a dryer, which kept a steady temperature of 105 °C. The process of determining the mass began only when the mass of the samples stabilized at an equal level. The mass of the dry samples was measured with electronic scales (Steinberg System SBS-LW Balance Scales, Hamburg, Germany) with an accuracy of up to 0.001 g and rounded up to 0.01 g. Next, the material was immersed in distilled water at room temperature in order to achieve a moisture content equal to or higher than the fiber saturation point. The moment the maximal dimensions of the sample were reached, the linear dimensions of the cross-section were measured using an electronic calliper (Limit cdm 150 mm flex 263990103 model) with an accuracy of up to 0.01 mm. The results of the measurements were used in order to calculate the relative wood density. The following formula was used to perform the calculations:
Qu = m0/Vmax, [kg/m3]
where:
  • m0—mass of the sample in an absolutely dry state
  • Vmax—the volume of the sample in the maximal saturation state.
We used descriptive statistics to analyze and present the results, including the arithmetic mean, minimum and maximum values, and standard deviation. Shapiro–Wilk tests were used to check the normal distribution. Since the studied variables had a normal distribution, an ANOVA significance test was used to test for differences in wood density. The analysis of the differences between the features was performed using post hoc tests. All of the statistical analyses and preparation images were performed using the Statistica (TIBCO Software Inc., Palo Alto, CA, USA) v13.1 software.

3. Results

The study, which was conducted on materials that were collected from eight areas of various provenances, revealed that the mean density of all analyzed samples without the division into provenance was 436.3 g/cm3, whereas the maximal and minimum values were 535.4 g/cm3 and 331.2 g/cm3, respectively. In total, 713 samples were analyzed. The highest mean density was found in provenance 4 (Zielonka), whereas the lowest mean density was in provenance 5 (Gleboki Brod). The maximal value of the studied feature occurred in provenance 4 (Zielonka), and the minimal value occurred in provenance 5 (Gleboki Brod). The greatest distribution of the results, especially for the mean values, was observed in the material collected from provenance 8 (Lipowa). However, the most consistent relative wood density results were found in provenance 2 (Woziwoda). The standard deviation of the density was between 29.11 kg/m3 and 44.90 kg/m3. The differences in the standard deviations were minor. The median value, as in the case of the mean density, was the highest for provenance 4, whereas the lowest value was for provenance 5 (Table 2). The median values were comparable or slightly lower than the mean density values. This means that, similarly to the standard deviation, the comparable populations were characterized by a homogenous density distribution without any outliers.
The distribution of the studied features was similar to the normal one; hence, the variability of the relative wood density in each provenance was collated and compared by means of the HSD (post hoc Tukey test) with a level of significance at p ≤ 0.05 (Table 3).
The conducted analysis showed the occurrence of statistically significant differences in wood density between the compared provenances. The results from provenance 5 deviated the most from the others. The mean wood density of the Scots pine for this provenance was 417.59 kg/m3 and was statistically significantly lower than the other provenances, except for the values of provenance 8 (Table 3).
In the case of the Scots pine that came from provenance 2, the wood density was statistically significantly higher only when compared with the pine wood density from provenances 5 and 8. Provenances 3 and 4 indicated that the density was statistically significantly higher than provenances 5 and 8, similarly to provenances 6 and 7 (Table 3; Figure 3).

4. Discussion

Density is one of the most important physical properties of wood. Its universality allows density to be correlated with other features and properties of wood [13,55]. Wood density allows for the precise determination of the mass, as it indicates the amount of woody substance in a unit of volume [56]. The most important factors that are able to influence the variation of wood tissue among individuals within a population are climate, tree stand, biosocial position of the tree, and silvicultural treatments, which have been discussed by a number of scholars [22,57].
Jelonek [58] studied the variability of relative wood density, which focused on the mechanical and physical properties of Scots pine growing on former farmland and in forests. The conducted experiment revealed that the trees that had been grown on former farmlands indicated lower wood density (407.35 kg/m3) compared to the relative density of the material collected from trees that had been grown in forests (435.04 kg/m3). Our experiment described in this paper showed that the mean relative density for all provenances that grew on the experimental plot possessed similar values as the ones in Jelonek’s study, which was 436.45 kg/m3. Other scholars [59,60,61] reached similar conclusions.
Similar studies focusing on the physical properties of wood were conducted by Witkowska [62], who studied the variability of the relative wood density of Scots pine in tree stands of different ages. She proved that the wood of 40–60-year-old trees indicates a similar relative wood density as the wood of older trees. It can signify that the wood density of the 57-year-old trees studied in our experiment will not change drastically over the years.
Paschalis [63] studied the variable wood density of Scots pine in Poland due to the geographical location. He analyzed the variable regional wood density in the eastern part of Poland. He pointed to the correlation between geographical location and the particular properties of wood. The author concluded that density is lower in the directions of north–south and east–west, and the intensity of the changes in both cases is similar. The phenomenon can be observed in sapwood rather than in hardwood.
The Scots pine is a unique species that shows considerable variability as far as the properties and quality of xylem are concerned, which proves the great flexibility of the species to adjust to the growth and development conditions. Moreover, in an individual tree, the properties of xylem vary according to its position in the stem or the tree’s age [64,65]. Within one tree species, the density depends not only on where the wood is in the tree but also on many other basic factors, such as the amount of late wood, the width of annual rings, defects, and the moisture of the material [66,67,68,69,70]. The quality of the wood and its features are conditioned by the economic activities performed in a particular tree stand. Other elements that impact wood properties are as follows: mixture format, planting spacing, species composition, and a series of improvements in felling and trimming [62,71]. Age class has the greatest impact on wood density of all the other factors [72].
In the context of the study, the findings of Naibas et al. [73] seem to be the most interesting. They noticed that in 8 out of the 25 studied species, wood density is determined genetically. For 15 species, the vital factors that improved wood density were competition, soil fertility, and pathogens. The authors concluded that wood density is a property susceptible to variation, so it is difficult to describe it synthetically. It is also difficult to specify and indicate the influence of exogenous and endogenous factors on wood density due to the large number of differences that occur between trees of the same species. The variability of wood density and its technical parameters depend on the population, species, and individual variability. It is important to continue provenance studies, as they will allow us to explore and better understand wood properties and improve wood quality.
Due to provenance studies, it will be possible to select a provenance from which the wood, once it has matured, will achieve the best technical parameters.

5. Conclusions

The studies conducted are not only scholarly but also practical in nature. Further provenance studies can help optimize the production of the best, predetermined quality of forest raw material. The presented results of the long-term experiment indicate the impact of genotype on the formation of wood density. The wood density of the compared provenance ranged between 417,59 kg/m3 and 450,59 kg/m3, and the differences between the populations were usually statistically significant. The highest value for the mean relative density and, at the same time, the best technical parameters were in the Zielonka provenance, which came from the place where the experimental plot had been first established. However, the wood that came from the very popular provenance Gleboki Brod had the lowest wood density. The results also show that caution is advised when relocating native species to other locations. Moreover, genotype plays a significant role in shaping the properties and characteristics of wood tissues in the Scots pine. The trees from which the material was collected were 57 years old, i.e., the trees were mature. However, the felling age for the pine is higher in Poland and is about 100 years; hence, at this stage, it is difficult to predict wood density since the trees from the experimental plot need to reach technical maturity. Naturally, this justifies and validates the need for provenance studies to be continued.

Author Contributions

Conceptualization, J.S., W.K. and T.J.; methodology, J.S. and W.K.; validation, T.J. and J.S.; formal analysis, T.J. and J.S.; data curation, A.O. and J.S.; writing—original draft preparation, J.S.; writing—review and editing, T.J. and J.S.; supervision, T.J.; project administration, J.S. and A.O.; funding acquisition, T.J. All authors have read and agreed to the published version of the manuscript.

Funding

The publication was financed within the framework of a science subsidy granted by the Minister of Science and Higher Education (data acquisition and laboratory work). The publication was co-financed within the framework of the Polish Ministry of Science and Higher Education’s program “Regional Initiative Excellence” in the years 2019–2023 (No. 005/RID/2018/19) with a financing amount of 12,000,000.00 PLN (proofreading and open access fee).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare that they have no competing interest.

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Forests 14 00480 g001 550
Figure 1. (a) Locations of native Scots pine stands used for the provenance study and research area; (b) Distribution of research plots with pine provinces in the Zielonka research plot.
Figure 1. (a) Locations of native Scots pine stands used for the provenance study and research area; (b) Distribution of research plots with pine provinces in the Zielonka research plot.
Forests 14 00480 g001
Forests 14 00480 g002 550
Figure 2. A diagram showing the process of collecting material for calculating the relative wood density. The numbers 1 and 2 show the places where the samples for the analysis were taken from.
Figure 2. A diagram showing the process of collecting material for calculating the relative wood density. The numbers 1 and 2 show the places where the samples for the analysis were taken from.
Forests 14 00480 g002
Forests 14 00480 g003 550
Figure 3. Relative wood density (Qu kg/m3) of the Scots pine (Pinus sylvestris L.) from various provenances in Poland (1—Woziwoda; 2—Rospuda; 3—Dluzek; 4—Zielonka; 5—Gleboki B.; 6—Radawnica; 7—Bartel W; 8—Lipowa).
Figure 3. Relative wood density (Qu kg/m3) of the Scots pine (Pinus sylvestris L.) from various provenances in Poland (1—Woziwoda; 2—Rospuda; 3—Dluzek; 4—Zielonka; 5—Gleboki B.; 6—Radawnica; 7—Bartel W; 8—Lipowa).
Forests 14 00480 g003
Table
Table 1. The mean values of the model trees’ characteristics for each provenance and the characteristics of the experimental plot.
Table 1. The mean values of the model trees’ characteristics for each provenance and the characteristics of the experimental plot.
ProvenanceDBH [cm]H [m]Crown CoverStockingSiteLatitude and Longitude
1—Woziwoda21.424.8moderate crown coverfull stocking—1.0Fresh mixed forest52.52712 N
17.02469 E
2—Rospuda21.725.0
3—Dluzek21.825.1
4—Zielonka21.324.9
5—Gleboki B.21.724.7
6—Radawnica21.824.7
7—Bartel W.22.125.2
8—Lipowa21.224.8
Table
Table 2. Statistics of relative wood density for the compared Scots pine (Pinus sylvestris L.) provenances in Poland.
Table 2. Statistics of relative wood density for the compared Scots pine (Pinus sylvestris L.) provenances in Poland.
Relative Wood Density—Qu [kg/m3]
ProvenanceMeanNStand. DeviationMinimumMaximumQ25Q50Q75
1—Woziwoda439.668929.11385.44508.18421.97438.72456.81
2—Rospuda435.419030.72383.66533.56415.05429.64448.99
3—Dluzek444.469032.96371.52518.83415.50443.18458.31
4—Zielonka450.599029.58380.70535.45429.52445.26468.99
5—Głęboki B.417.598542.23331.25530.14398.96412.06439.66
6—Radawnica439.348929.47355.77506.06418.42438.13460.57
7—Bartel W.442.179032.85385.31518.98420.68437.40457.11
8—Lipowa420.579044.90337.55499.16381.10416.89464.17
Total436.3571335.87331.25535.45
Q25—quartile 25; Q50—quartile 50 (Median); Q75—quartile 75.
Table
Table 3. Analysis of variance and HSD test for mean wood density of the Scots pine (Pinus sulvestris L.) from various provenances in Poland (1—Woziwoda; 2—Rospuda; 3—Dluzek; 4—Zielonka; 5—Głęboki B.; 6—Radawnica; 7—Bartel W.; 8—Lipowa).
Table 3. Analysis of variance and HSD test for mean wood density of the Scots pine (Pinus sulvestris L.) from various provenances in Poland (1—Woziwoda; 2—Rospuda; 3—Dluzek; 4—Zielonka; 5—Głęboki B.; 6—Radawnica; 7—Bartel W.; 8—Lipowa).
Qu [kg/m3]SSdfMSSSdfMSFp
81,434.07711,633.44834,811.87051184.1309.8244580.000000
ProvenanceProvenance
12345678
1
20.992
30.9830.644
40.4020.0610.933
50.0010.0170.0000.000
61.0000.9950.9760.3630.001
71.0000.8921.0000.7250.0000.999
80.0050.0740.0000.0000.9990.0070.001
The red values indicate statistically significant differences in conventional wood density between the pine origins (p ≤ 0.05).
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Szaban, J.; Jelonek, T.; Okińczyc, A.; Kowalkowski, W. Results of a 57-Year-Long Research on Variability of Wood Density of the Scots Pine (Pinus sylvestris L.) from Different Provenances in Poland. Forests 2023, 14, 480. https://doi.org/10.3390/f14030480

AMA Style

Szaban J, Jelonek T, Okińczyc A, Kowalkowski W. Results of a 57-Year-Long Research on Variability of Wood Density of the Scots Pine (Pinus sylvestris L.) from Different Provenances in Poland. Forests. 2023; 14(3):480. https://doi.org/10.3390/f14030480

Chicago/Turabian Style

Szaban, Jarosław, Tomasz Jelonek, Alicja Okińczyc, and Wojciech Kowalkowski. 2023. "Results of a 57-Year-Long Research on Variability of Wood Density of the Scots Pine (Pinus sylvestris L.) from Different Provenances in Poland" Forests 14, no. 3: 480. https://doi.org/10.3390/f14030480

APA Style

Szaban, J., Jelonek, T., Okińczyc, A., & Kowalkowski, W. (2023). Results of a 57-Year-Long Research on Variability of Wood Density of the Scots Pine (Pinus sylvestris L.) from Different Provenances in Poland. Forests, 14(3), 480. https://doi.org/10.3390/f14030480

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