Next Article in Journal
A Comparative Study to Evaluate Accuracy on Canopy Height and Density Using UAV, ALS, and Fieldwork
Previous Article in Journal
Potential of Genome-Wide Association Studies and Genomic Selection to Improve Productivity and Quality of Commercial Timber Species in Tropical Rainforest, a Case Study of Shorea platyclados
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 11
Issue 2
10.3390/f11020240
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Aboveground Carbon Content and Storage in Mature Scots Pine Stands of Different Densities

by
Andrzej Węgiel
* and
Krzysztof Polowy
Faculty of Forestry, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland
*
Author to whom correspondence should be addressed.
Forests 2020, 11(2), 240; https://doi.org/10.3390/f11020240
Submission received: 19 January 2020 / Revised: 18 February 2020 / Accepted: 19 February 2020 / Published: 21 February 2020
(This article belongs to the Section Forest Ecology and Management)
Browse Figures
Versions Notes

Abstract

:
Background and Objectives: The continuous increase in the amount of atmospheric CO2 is a factor that significantly contributes to global warming. Forests can be used to mitigate climate change by absorbing carbon and storing it. Scots pine (Pinus sylvestris L.) is the most abundant tree species in Polish forests and can substantially aid carbon accumulation. The aim of the study was to determine the carbon content in the dry mass of various parts of Scots pine trees and to evaluate the relationship between the accumulation of carbon in aboveground tree biomass and some stand parameters. Materials and Methods: The research was carried out in 20 even-aged (81–90 years old) Scots pine stands in northwestern Poland (Drawno Forest District). The densities of these stands ranged from 476 to 836 trees per hectare. The aboveground biomass was calculated as the sum of the following tree compartments: stem (wood and bark), dead branches, thick branches, thin branches and needles. The carbon content and storage in these compartments was determined. Results: The mean carbon content was lowest in stem wood (47.0%) and highest in needles (50.3%). No correlation between the stand density and the level of carbon stored in the aboveground biomass of Scots pines was found.

1. Introduction

Carbon dioxide is one of the most important greenhouse gases contributing to global warming. The concentration of CO2 in the air depends on natural and anthropogenic emissions and on the accumulation of CO2 by living organisms, particularly forests. Human activities to limit the emissions of greenhouse gases, especially carbon dioxide, have been undertaken worldwide. Over 190 countries signed the Kyoto Protocol, which obliges the signatories to reduce atmospheric emissions of greenhouse gasses. Furthermore, the signatories are committed to estimating and reporting both the level of a country’s emissions and changes in forest and agricultural land cover that can influence CO2 sequestration. The Kyoto Protocol allows for balancing anthropogenic emissions with carbon sequestration by land ecosystems [1].
Forests, as the most important carbon sink in terms of carbon sequestration, are suitable measures for controlling the carbon content in the atmosphere. Forest ecosystems store more than 80% of all terrestrial aboveground C and more than 70% of all soil organic C [2,3,4]. For this reason, a precise estimation of the amount of carbon stored in various types of forests should be a baseline for further actions [5,6]. These actions could involve increasing carbon sequestration in forests by expanding forest areas and improving the accumulation capabilities of existing forests [7].
Carbon is stored in various parts of the forest ecosystem, mostly in wood. Based on many studies, an overall carbon concentration of 50% of tree biomass has been assumed and widely accepted [8,9,10]. However, research has shown that carbon content may vary, depending on tree species, tree compartment and some environmental issues [5,11,12,13,14,15].
Scots pine (Pinus sylvestris L.) is one of the most important tree species in carbon accumulation. It has the broadest geographical range of all pines and is probably the most widespread coniferous species in the world [16]. Scots pine covers 24% of the forest area in Europe [17] and over 52% in Poland [18]. Pine is therefore a species of substantial economic and environmental significance [19,20,21]. Thus, many scientific studies on carbon accumulation in Scots pine stands have been carried out in multiple European countries, e.g., Belgium [17], Estonia [22], Finland [11,23], Lithuania [24], Poland [25,26] and Turkey [27,28,29,30]. Among the factors influencing carbon sequestration in pine forests, the most investigated factors are the site preparation method [31], thinning intensity [32,33] and management methods [34,35,36,37,38].
The goal of this study was to determine the carbon content in the dry mass of needles, branches and stems of mature Scots pine stands and to assess the relationship between the carbon storage in aboveground biomass and stand density, along with some parameters of stands (mean diameter at breast height (DBH), mean height, stand density, volume, basal area and biomass).

2. Materials and Methods

The study was carried out on 20 0.5-hectare rectangular sample plots in semi-natural, planted, mature stands of Scots pine (Pinus sylvestris L.) (Table 1). All sample plots were located in one forest complex in the Drawno Forest District (Figure 1), northwestern Poland (E 15°50′–16°0′, N 53°10′–53°13′). The same stands have already been used in a study on the value of timber assortments [39].
All stands were characterized by shared attributes: single-layer, single-species, even-aged 81–90-year-old stands, flat terrain (without hills or pits), same soil type (Carbic Podzol), not damaged or deformed, without any gaps or undergrowth, and with forest floor plants typical to this habitat type (not grass-covered). In these stands, no thinning had been performed in the past 5 years. The differentiating factor was the stand density, expressed as the number of trees in a given area, ranging from 476 to 836 trees per hectare (Table 1).
Tree measurements and sample collections were performed from July to September 2012. On each 0.5-hectare sample plot, the DBH of each tree and the height of 20% of the trees (every fifth tree) were measured. The DBH was measured (in two directions N-S and E-W) using calipers (accurate to 1 mm) and the height of the trees was recorded with a Haglof Vertex Laser hypsometer (accurate to 0.1 m). Based on these data, Näslund’s height curves were developed for each plot to assign a height to each tree. Out of 20 sample plots, five plots with different densities were selected. In each selected plot, 10 model trees, representing the range of diameters (from 16.5 cm to 37.5 cm), were designated (50 trees in total) for detailed measurements. Model trees were felled and divided into fractions (compartments): stem, branches and needles. Stem volume was established by a sectional volume measurement and the fresh mass of each compartment was obtained. From the stem, samples were taken as 10-cm cross sections that were cut every meter along the stem. The fresh mass of each compartment was measured immediately on site. The crowns of the model trees were divided into two parts: the living branches and the dead branches. The tips with needles (thin branches about 4 mm in diameter) were then cut off from the living branches. Finally, the needles were separated from the thin branches by hand. From each compartment, samples were taken randomly. These samples were weighed fresh, dried to a constant mass at 65 °C and weighed again. For each sample, a conversion factor was calculated for estimating the dry mass of each compartment of every model tree. Based on the data obtained from these 50 model trees, allometric equations were developed [40]. The best fitting equations to determine the dry mass of each compartment were selected based on: Akaike’s Information Criterion (AIC), the coefficient of determination (R2) and the residual standard error (RSE). These equations allowed for calculating the dry mass of its aboveground biomass divided into the following compartments: stem, dead branches, thick branches, thin branches and needles, using DBH and tree height for each tree as the input variables (Table 2). The stand volume was calculated based on empirical equations developed by Bruchwald [41].
To estimate the carbon content, out of the 10 model trees for each plot, 3 trees were selected. There were 15 trees in total for all sample plots. These model trees were divided into three equal groups (5 trees each) according to their diameter: small (DBH: 16.8–21.9 cm), medium (DBH: 23.8–26.1) and large (DBH: 28.2–34.0). From a list of model trees for a sample plot, ordered by diminishing diameter, a second, fifth and ninth tree were considered. For the carbon content estimation, samples previously used for determining dry weight were used. Sections cut from stems were used to calculate the proportion between the masses of bark and wood, as previously these fractions were not differentiated. Samples from each compartment were ground, labeled and sent to the laboratory. Carbon content was determined using LECO TruMac CNS (Leco Corporation, St. Joseph, MO, USA).
A statistical analysis was performed using the “Multivariate Platform” tool in the statistical software JMP 10.0 (SAS Institute Inc., Cary, NC, USA). The correlations between the carbon content and various tree and stand characteristics were calculated. Pearson’s correlation coefficients and the corresponding significance levels were calculated. Data normality was assessed using a Shapiro–Wilk normality test.

3. Results

Stems accounted for most of the biomass (average 116.0 Mg·ha−1), followed by branches (average 21.3 Mg·ha−1), stem bark (average 10.1 Mg·ha−1) and needles (average 4.7 Mg·ha−1) (Table 3).
The mean carbon content in the various tree compartments ranged from 47.0% in the stem wood to 50.3% in the needles. The lowest carbon content was found in thick branches (45.5%) and the highest (52.5%) in dead branches (Table 3). In cases of stem wood and needles, the C content was correlated with tree size (DBH) and both correlations were negative (Figure 2).
The dry mass of the aboveground part of Scots pine stands ranged from 118.0 to 183.7 Mg·ha−1, with an average of 152.1 Mg·ha−1 (Table 4). In all stands, the most carbon was stored in the stem wood and the least carbon in the needles (Table 4, Figure 3). Stand density was not correlated with the carbon content in any tree compartment or in the aboveground stand biomass. Density was also not correlated with stand volume, basal area or the dry aboveground stand biomass. On the other hand, stand density was correlated with mean DBH and with mean height. Carbon stock and percentage of carbon stock in particular tree compartments in several cases were correlated with mean DBH, mean height, stand volume, basal area and the aboveground stand biomass (Table 5).

4. Discussion

The mean carbon contents in the various tree compartments of Scots pine did not differ considerably from the generally accepted level of 50% [5,27]. The largest discrepancies were found in the stem wood and bark, where the mean contents were 47.0% and 47.1%, respectively (Table 3). Other studies reported higher contents in stem wood: 49.8% [24], 51.2% [27], 49.3%–54.9% [28] and 51.1%–54.8% [30] and stem bark: 51.3% [24], 53.5% [27], 49.2%–53.9% [28] and 51.1%-54.8% [30]. The mean carbon content in the thick branches was 48.8% and in the thin branches 50.2% (Table 3). These figures were smaller than those reported by others, which ranged between 51.5% and 54.7% [24,27,28]. The carbon content of the needles (50.3%) was in the lower-middle range of the results given in the literature: 50.1%–55.2% [24,27,28,30].
Because the amount of carbon stored in plants is strongly correlated with the amount of biomass, the accumulation level in the stand depends mostly on the growth rate, especially the wood biomass increment. Biomass production in forests can be regulated, to some extent, by controlling stand density. This process is usually performed when designing the intensity and frequency of thinning operations. Thinning reduces the density, improves the resource availability for the remaining trees and increases tree growth [16,21,42]. Long-term experiments show that the higher the intensity of thinning (i.e., reduction in density), the lower the stand growth is. More intense growth was noted in non-thinned control stands [43,44,45]. Due to intensive thinning, the stand volume increment was smaller than in control stands [19,20,46], whereas due to low intensity management, the influence of thinning was weak or none [46,47]. Some studies show a complete lack of influence of thinning on either stand growth [21,48] or biomass production [49]. It was found that, immediately after thinning, there was a decrease in stand volume growth, typically lasting approximately 10 years, levelling off after this period [50]. In addition, the remaining trees had a greater volume increment if thinning was more intense [44,48,51].
Many studies reported that the carbon stock in aboveground biomass changes significantly with the intensity of thinning. The total C stored at the end of the rotation period was greater in Scots pine stands with a longer rotation period and a lighter thinning regime [32,33,34,37]. Furthermore, C storage in aboveground biomass after partial cutting decreased linearly with cutting intensity [52]. While thinning has a similar effect on the stand structure as harvesting, its range is much more limited and the effect on carbon fluxes could be indistinguishable from natural inter-annual variability or is very short-term [7]. Zhou et al. [52] reported that thinning more than doubled diameter growth, increased understory biomass 4-fold, but had no noticeable effect on the forest floor and mineral soil C pools.
Another aspect was the influence of various stand characteristics on carbon content in tree biomass. The C content in the wood and needles was negatively correlated with DBH (Figure 2). This result means that in comparison to smaller trees, larger trees had a lower content of C in the dry mass of their wood and needles. A similar pattern was found for Scots pine in Turkey by Erkan and Güner [30]. In their study, the C content in the needles was negatively correlated with DBH, but the C content in the wood was positively correlated with tree diameter. Such correlations have also been found for other pine species [12,53].
The studied stands showed a strong relationship between stand density and mean DBH, a correlation which is widely known [20,45,54]. Therefore, if stand density is correlated with tree size and tree size is correlated with carbon content, then it could be expected that there is a correlation between the stand density and the carbon content in tree biomass. However, such a correlation was not confirmed in this study. The aboveground biomass of trees, the amount of stored carbon and C allocation patterns were shown to be independent of stand density. A similar absence of a relationship was shown in the USA for Pinus contorta [55]. However, studies carried out in Spain for Scots pine showed that in dense stands, where no thinning (or mild thinning) was conducted, the accumulation of carbon was greater than that in other stands [33,37].

5. Conclusions

The obtained results may have some practical significance for forest management. As expected, the carbon stock in mature Scots pine stands was correlated with basal area, stand volume and aboveground biomass of the stand i.e., the amount of wood. This means that optimizing forest management for increased wood production does not impair a high carbon accumulation.
The carbon content in the dry mass of the various compartments of the Scots pine trees differed from the widely reported level of 50%. The lowest C content was in stem wood (47.0%) and stem bark (47.1%) and the highest in needles (50.3%). In pine stands, stems accumulate the most carbon (about 80%) despite the main constituents of stems (i.e., bark and wood) having the lowest carbon content. To increase the precision of estimating the amount of carbon stored in forest ecosystems, it is worth measuring the carbon content of individual species at various geographical locations.

Author Contributions

Conceptualization, A.W. and K.P.; methodology, A.W.; formal analysis, A.W.; investigation, A.W. and K.P.; resources, A.W.; data curation, A.W.; writing—original draft preparation, A.W.; writing—review and editing, K.P.; visualization, A.W. All authors have read and agreed to the published version of the manuscript.

Funding

The publication is co-financed within the framework of Ministry of Science and Higher Education programme as “Regional Initiative Excellence” in years 2019–2022, project number 005/RID/2018/19.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Oberthür, S.; Ott, H.E. The Kyoto Protocol: International Climate Policy for the 21st Century; Springer Science & Business Media: Berlin, Germany, 1999; p. 360. [Google Scholar]
  2. Batjes, N.H. Total carbon and nitrogen in the soils of the world. Eur. J. Soil Sci. 1996, 47, 151–163. [Google Scholar] [CrossRef]
  3. Jobbágy, E.G.; Jackson, R.B. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol. Appl. 2000, 10, 423–436. [Google Scholar] [CrossRef]
  4. Jandl, R.; Lindner, M.; Vesterdal, L.; Bauwens, B.; Baritz, R.; Hagedorn, F.; Johnson, D.W.; Minkkinen, K.; Byrne, K.A. How strongly can forest management influence soil carbon sequestration? Geoderma 2007, 137, 253–268. [Google Scholar] [CrossRef]
  5. Lamlom, S.H.; Savidge, R.A. A reassessment of carbon content in wood: Variation within and between 41 North American species. Biomass Bioenergy 2003, 25, 381–388. [Google Scholar] [CrossRef]
  6. Malmsheimer, R.W.; Bowyer, J.L.; Fried, J.S.; Gee, E.; Izlar, R.L.; Miner, R.A.; Munn, I.A.; Oneil, E.; Stewart, W.C. Managing forests because carbon matters: Integrating energy, products, and land management policy. J. For. 2011, 109, 7–51. [Google Scholar] [CrossRef]
  7. Noormets, A.; Epron, D.; Domec, J.C.; McNulty, S.G.; Fox, T.; Sun, G.; King, J.S. Effects of forest management on productivity and carbon sequestration: A review and hypothesis. For. Ecol. Manag. 2015, 355, 124–140. [Google Scholar] [CrossRef] [Green Version]
  8. Sedjo, R.A. Forests: A tool to moderate global warming. Environ. Sci. Policy Sustain. Dev. 1989, 31, 14–20. [Google Scholar] [CrossRef]
  9. Dewar, R.C.; Cannell, M.G. Carbon sequestration in the trees, products and soils of forest plantations: An analysis using UK examples. Tree Physiol. 1992, 11, 49–71. [Google Scholar] [CrossRef]
  10. Hollinger, D.Y.; Maclaren, J.P.; Beets, P.N.; Turland, J. Carbon sequestration by New Zealand’s Plantation forests. N. Z. J. For. Sci. 1993, 23, 194–208. [Google Scholar]
  11. Laiho, R.; Laine, J. Tree stand biomass and carbon content in an age sequence of drained pine mires in southern Finland. For. Ecol. Manag. 1997, 93, 161–169. [Google Scholar] [CrossRef]
  12. Bert, D.; Danjon, F. Carbon concentration variations in the roots, stem and crown of mature Pinus pinaster (Ait.). For. Ecol. Manag. 2006, 222, 279–295. [Google Scholar] [CrossRef]
  13. Thomas, S.C.; Malczewski, G. Wood carbon content of tree species in Eastern China: Interspecific variability and the importance of the volatile fraction. J. Environ. Manag. 2007, 85, 659–662. [Google Scholar] [CrossRef] [PubMed]
  14. Thomas, S.C.; Martin, A.R. Carbon content of tree tissues: A synthesis. Forests 2012, 3, 332–352. [Google Scholar] [CrossRef] [Green Version]
  15. Martin, A.R.; Doraisami, M.; Thomas, S.C. Global patterns in wood carbon concentration across the world’s trees and forests. Nat. Geosci. 2018, 11, 915–920. [Google Scholar] [CrossRef]
  16. Tahvonen, O.; Pihlainen, S.; Niinimäki, S. On the economics of optimal timber production in boreal Scots pine stands. Can. J. For. Res. 2013, 43, 719–730. [Google Scholar] [CrossRef]
  17. Janssens, I.A.; Sampson, D.A.; Cermak, J.; Meiresonne, L.; Riguzzi, F.; Overloop, S.; Ceulemans, R. Above- and belowground phytomass and carbon storage in a Belgian Scots pine stand. Ann. For. Sci. 1999, 56, 81–90. [Google Scholar] [CrossRef]
  18. GUS. Główny Urząd Statystyczny. Leśnictwo; Informacje i Opracowania Statystyczne: Warszawa, Poland, 2017. [Google Scholar]
  19. Valinger, E.; Elfving, B.; Mörling, T. Twelve-year growth response of Scots pine to thinning and nitrogen fertilisation. For. Ecol. Manag. 2000, 134, 45–53. [Google Scholar] [CrossRef]
  20. Mäkinen, H.; Isomäki, A. Thinning intensity and long-term changes in increment and stem form of Scots pine trees. For. Ecol. Manag. 2004, 203, 21–34. [Google Scholar] [CrossRef]
  21. Giuggiola, A.; Bugmann, H.; Zingg, A.; Dobbertin, M.; Rigling, A. Reduction of stand density increases drought resistance in xeric Scots pine forests. For. Ecol. Manag. 2013, 310, 827–835. [Google Scholar] [CrossRef]
  22. Karu, H.; Szava-Kovats, R.; Pensa, M.; Kull, O. Carbon sequestration in a chronosequence of Scots pine stands in a reclaimed opencast oil shale mine. Can. J. For. Res. 2009, 39, 1507–1517. [Google Scholar] [CrossRef]
  23. Vanninen, P.; Mäkelä, A. Carbon budget for Scots pine trees: Effects of size, competition and site fertility on growth allocation and production. Tree Physiol. 2005, 25, 17–30. [Google Scholar] [CrossRef]
  24. Armolaitis, K.; Varnagirytė-Kabašinskienė, I.; Stupak, I.; Kukkola, M.; Mikšys, V.; Wojcik, J. Carbon and nutrients of Scots pine stands on sandy soils in Lithuania in relation to bioenergy sustainability. Biomass Bioenergy 2013, 54, 250–259. [Google Scholar] [CrossRef]
  25. Skonieczna, J.; Małek, S.; Polowy, K.; Węgiel, A. Element content of Scots pine (Pinus sylvestris L.) stands of different densities. Drewno 2014, 57, 77–87. [Google Scholar] [CrossRef]
  26. Bembenek, M.; Giefing, D.E.; Jelonek, T.; Karaszewski, Z.; Kruszyk, R.; Tomczak, A.; Woszczyk, M.; Mederski, P.S. Carbon content in juvenile and mature wood of Scots pine (Pinus sylvestris L.). Balt. For. 2015, 21, 279–284. [Google Scholar]
  27. Tolunay, D. Carbon concentrations of tree components, forest floor and understorey in young Pinus sylvestris stands in north-western Turkey. Scand. J. For. Res. 2009, 24, 394–402. [Google Scholar] [CrossRef]
  28. Durkaya, A.; Durkaya, B.; Makineci, E.; Orhan, I. Aboveground biomass and carbon storage relationship of Turkish pines. Fresenius Environ. Bull. 2015, 24, 3573–3583. [Google Scholar]
  29. Lee, J.; Tolunay, D.; Makineci, E.; Çömez, A.; Son, Y.M.; Kim, R.; Son, Y. Estimating the age-dependent changes in carbon stocks of Scots pine (Pinus sylvestris L.) stands in Turkey. Ann. For. Sci. 2016, 73, 523–531. [Google Scholar] [CrossRef] [Green Version]
  30. Erkan, N.; Güner, S.T. Determination of carbon concentration of tree components for Scotch pine forests in Turkmen Mountain (Eskisehir, Kutahya) Region. Forestist 2018, 68, 87–92. [Google Scholar] [CrossRef]
  31. Mjöfors, K.; Strömgren, M.; Nohrstedt, H.-Ö.; Johansson, M.-B.; Gärdenäs, A.I. Indications that site preparation increases forest ecosystem carbon stocks in the long term. Scand. J. For. Res. 2017, 32, 717–725. [Google Scholar] [CrossRef]
  32. Bravo-Oviedo, A.; Ruiz-Peinado, R.; Modrego, P.; Alonso, R.; Montero, G. Forest thinning impact on carbon stock and soil condition in Southern European populations of P. sylvestris L. For. Ecol. Manag. 2015, 357, 259–267. [Google Scholar] [CrossRef]
  33. Ruiz-Peinado, R.; Bravo-Oviedo, A.; Montero, G.; del Río, M. Carbon stocks in a Scots pine afforestation under different thinning intensities management. Mitig. Adapt. Strateg. Glob. Chang. 2016, 21, 1059–1072. [Google Scholar] [CrossRef]
  34. Pohjola, J.; Valsta, L. Carbon credits and management of Scots pine and Norway spruce stands in Finland. For. Policy Econ. 2007, 9, 789–798. [Google Scholar] [CrossRef]
  35. Goetz, R.U.; Hritonenko, N.; Mur, R.J.; Xabadia, A.; Yatsenko, Y. Forest management and carbon sequestration in size-structured forests: The case of Pinus sylvestris in Spain. For. Sci. 2010, 56, 242–256. [Google Scholar] [CrossRef]
  36. Goetz, R.U.; Hritonenko, N.; Mur, R.; Xabadia, À.; Yatsenko, Y. Forest management for timber and carbon sequestration in the presence of climate change: The case of Pinus sylvestris. Ecol. Econ. 2013, 88, 86–96. [Google Scholar] [CrossRef]
  37. Moreno-Fernández, D.; Díaz-Pinés, E.; Barbeito, I.; Sánchez-González, M.; Montes, F.; Rubio, A.; Cañellas, I. Temporal carbon dynamics over the rotation period of two alternative management systems in Mediterranean mountain Scots pine forests. For. Ecol. Manag. 2015, 348, 186–195. [Google Scholar] [CrossRef]
  38. Węgiel, A.; Małek, S.; Bielinis, E.; Grebner, D.L.; Polowy, K.; Skonieczna, J. Determination of elements removal in different harvesting scenarios of Scots pine (Pinus sylvestris L.) stands. Scand. J. For. Res. 2018, 33, 261–270. [Google Scholar] [CrossRef]
  39. Węgiel, A.; Bembenek, M.; Łacka, A.; Mederski, P.S. Relationship between stand density and value of timber assortments: A case study for Scots pine stands in north-western Poland. N. Z. J. For. Sci. 2018, 48, 1–9. [Google Scholar] [CrossRef]
  40. Picard, N.; Saint-André, L.; Henry, M. Manual for Building Tree Volume and Biomass Allometric Equations: From Field Measurement to Prediction; FAO: Rome, Italy; CIRAD: Montpellier, France, 2012; p. 215. [Google Scholar]
  41. Bruchwald, A. New empirical formula for determination of volume of Scots pine stands. Folia For. Pol. 1996, 38, 5–10. [Google Scholar]
  42. Kojola, S.; Ahtikoski, A.; Hökkä, H.; Penttilä, T. Profitability of alternative management regimes in Scots pine stands on drained peatlands. Eur. J. For. Res. 2012, 131, 413–426. [Google Scholar] [CrossRef]
  43. Curtis, R.O.; Marshall, D.D.; Bell, J.F. LOGS: A pioneering example of silvicultural research in coast Douglas-fir. J. For. 1997, 95, 19–25. [Google Scholar]
  44. Kuliešis, A.; Saladis, J.; Kuliešis, A.A. Development and productivity of young Scots pine stands by regulating density. Balt. For. 2010, 16, 235–246. [Google Scholar]
  45. Nilsson, U.; Agestam, E.; Ekö, P.-M.; Elfving, B.; Fahlvik, N.; Johansson, U.; Karlsson, K.; Lundmark, T.; Wallentin, C. Thinning of Scots pine and Norway spruce monocultures in Sweden. Stud. For. Suec. 2010, 219, 1–46. [Google Scholar]
  46. Zhang, J.; Oliver, W.W.; Ritchie, M.W. Effect of stand densities on stand dynamics in white fir (Abies concolor) forests in northeast California, USA. For. Ecol. Manag. 2007, 244, 50–59. [Google Scholar] [CrossRef]
  47. Del Río, M.; Calama, R.; Cañellas, I.; Roig, S.; Montero, G. Thinning intensity and growth response in SW-European Scots pine stands. Ann. For. Sci. 2008, 65. [Google Scholar] [CrossRef] [Green Version]
  48. Gizachew, B.; Brunner, A. Density-growth relationships in thinned and unthinned Norway spruce and Scots pine stands in Norway. Scand. J. For. Res. 2011, 26, 543–554. [Google Scholar] [CrossRef]
  49. Routa, J.; Kellomäki, S.; Strandman, H. Effects of forest management on total biomass production and CO2 emissions from use of energy biomass of Norway spruce and Scots pine. Bioenergy Res. 2012, 5, 733–747. [Google Scholar] [CrossRef]
  50. Egnell, G.; Ulvcrona, K.A. Stand productivity following whole-tree harvesting in early thinning of Scots pine stands in Sweden. For. Ecol. Manag. 2015, 340, 40–45. [Google Scholar] [CrossRef]
  51. Moulinier, J.; Brais, S.; Harvey, B.D.; Koubaa, A. Response of boreal Jack pine (Pinus banksiana Lamb.) stands to a gradient of commercial thinning intensities, with and without N fertilization. Forests 2015, 6, 2678–2702. [Google Scholar] [CrossRef] [Green Version]
  52. Zhou, D.; Zhao, S.Q.; Liu, S.; Oeding, J. A meta-analysis on the impacts of partial cutting on forest structure and carbon storage. Biogeosciences 2013, 10, 3691–3703. [Google Scholar] [CrossRef] [Green Version]
  53. Güner, Ş.T.; Makineci, E. Determination of annual organic carbon sequestration in soil and forest floor of Scots pine forests on the Türkmen Mountain (Eskişehir, Kütahya). J. Fac. For. Istanb. Univ. 2017, 67, 109–115. [Google Scholar] [CrossRef] [Green Version]
  54. Alegria, C. Simulation of silvicultural scenarios and economic efficiency for maritime pine (Pinus pinaster Aiton) wood-oriented management in centre inland of Portugal. For. Syst. 2011, 20, 361–378. [Google Scholar] [CrossRef] [Green Version]
  55. Litton, C.M.; Ryan, M.G.; Knight, D.H. Effects of tree density and stand age on carbon allocation patterns in postfire lodgepole pine. Ecol. Appl. 2004, 14, 460–475. [Google Scholar] [CrossRef] [Green Version]
Forests 11 00240 g001 550
Figure 1. Distribution of sample plots in the south-eastern part of the Drawno Forest District. The same map was used in a previous paper concerning the value of timber assortments, which concerned the same stands: after [39].
Figure 1. Distribution of sample plots in the south-eastern part of the Drawno Forest District. The same map was used in a previous paper concerning the value of timber assortments, which concerned the same stands: after [39].
Forests 11 00240 g001
Forests 11 00240 g002 550
Figure 2. Average content of carbon (+SD) in tree parts (SW—stem wood, SB—stem bark, BR1—thin branches, BR2—thick branches, BR3—dead branches, and FL—foliage) of the model trees (N = 15) divided into small (A), medium (B), and large (C) trees (5 trees in each group according to DBH). The oblique lines show in which tree parts the content of carbon was significantly correlated (p < 0.05) with tree size. In both cases, correlations were negative.
Figure 2. Average content of carbon (+SD) in tree parts (SW—stem wood, SB—stem bark, BR1—thin branches, BR2—thick branches, BR3—dead branches, and FL—foliage) of the model trees (N = 15) divided into small (A), medium (B), and large (C) trees (5 trees in each group according to DBH). The oblique lines show in which tree parts the content of carbon was significantly correlated (p < 0.05) with tree size. In both cases, correlations were negative.
Forests 11 00240 g002
Forests 11 00240 g003 550
Figure 3. Carbon allocation in aboveground biomass of 20 Scots pine stands. Tree parts: FL—foliage, BR—branches, SB—stem bark, and SW—stem wood.
Figure 3. Carbon allocation in aboveground biomass of 20 Scots pine stands. Tree parts: FL—foliage, BR—branches, SB—stem bark, and SW—stem wood.
Forests 11 00240 g003
Table
Table 1. Main characteristics of sampled Scots pine stands.
Table 1. Main characteristics of sampled Scots pine stands.
Stand NumberAge
(Years)		Stand Density
(tree·ha−1)		Mean DBH ± SD (cm)Mean Height ± SD (m)Basal Area
(m2·ha−1)		Volume
(m3·ha−1)
1 *8247628.2 ± 4.522.9 ± 1.730.5325
28751827.5 ± 4.923.6 ± 2.031.8350
38253425.9 ± 4.322.4 ± 1.528.4298
48256428.0 ± 4.524.5 ± 1.435.5401
5 *8259425.7 ± 4.720.8 ± 1.431.5306
68259627.1 ± 5.221.6 ± 1.435.7358
78261824.6 ± 4.020.4 ± 1.530.2288
88263224.0 ± 4.721.1 ± 1.429.6293
98263225.6 ± 4.722.0 ± 1.433.6347
108263424.6 ± 4.621.4 ± 1.631.0311
118264026.0 ± 4.723.4 ± 1.735.1385
128264426.4 ± 4.423.0 ± 1.435.9384
138264825.9 ± 5.222.3 ± 1.735.4373
14 *8267423.6 ± 4.319.6 ± 1.530.1280
158268224.7 ± 4.922.8 ± 1.734.0363
168270821.8 ± 4.219.5 ± 2.227.3250
178272022.3 ± 4.324.7 ± 3.829.1345
188275621.7 ± 4.420.5 ± 2.028.9281
19 *8275823.9 ± 5.320.1 ± 2.035.7340
20 *8283621.8 ± 4.019.3 ± 1.731.5291
*—stands in which model trees for biomass determination were selected. DBH—diameter at breast height, SD—standard deviation. The data presented in the table are after [39].
Table
Table 2. Allometric equations used to determine the dry mass of different parts of Scots pine trees.
Table 2. Allometric equations used to determine the dry mass of different parts of Scots pine trees.
Tree PartEquationEquation CoefficientsR2RSE
abc
Stem (wood + bark)a · (D2 · H2)b0.0129960.761234 0.935722.187
Thick branchesa · Db · Hc0.0480943.333163−1.534550.72818.9224
Thin branchesa · (D2 · H2)b0.0010540.879284 0.67441.5290
Dead branchesa · Db · Hc0.0235183.5694521.871470.74573.3543
Needlesa · (D)b0.0110922.012406 0.74991.9823
D—diameter at breast height (cm); H—tree height (m); a, b, c—equation coefficients; R2—coefficient of determination; RSE—residual standard error.
Table
Table 3. Aboveground dry biomass of stands (N = 20) and content of carbon in model trees (N = 15) in different parts of Scots pine trees.
Table 3. Aboveground dry biomass of stands (N = 20) and content of carbon in model trees (N = 15) in different parts of Scots pine trees.
Tree PartAboveground Biomass (Mg·ha−1)Carbon Content (%)
MeanSDProportionMeanSDMinMax
Stem wood116.016.276.3%47.00.546.348.1
Stem bark10.11.46.6%47.11.045.849.1
Thick branches13.31.98.7%48.81.045.550.0
Thin branches3.00.32.0%50.20.649.251.3
Dead branches5.00.83.3%49.61.048.452.5
Needles4.70.43.1%50.30.349.750.9
Total152.1 100%
SD—standard deviation, min—minimum, max—maximum.
Table
Table 4. Aboveground dry biomass of Scots pine stands and carbon stock in different parts of trees (SW—stem wood, SB—stem bark, BR—branches, and FL—foliage).
Table 4. Aboveground dry biomass of Scots pine stands and carbon stock in different parts of trees (SW—stem wood, SB—stem bark, BR—branches, and FL—foliage).
Stand NumberStand Density
(tree·ha−1)		Above Ground Biomass
(Mg·ha−1)		Carbon Stock (Mg·ha−1)
SWSBBRFLTotal
1476147.652.54.610.62.369.9
2518160.258.15.110.32.375.8
3534137.349.44.39.22.165.1
4564183.767.15.911.32.686.9
5594140.748.94.311.22.366.8
6596162.956.55.013.12.677.2
7618133.146.64.110.42.263.2
8632135.848.44.29.62.264.5
9632159.757.15.011.12.575.7
10634143.451.14.510.22.368.0
11640177.665.05.710.92.684.1
12644176.263.75.611.62.783.5
13648171.161.45.411.72.681.1
14674130.045.24.010.52.261.8
15682169.061.85.410.32.580.1
16708118.041.93.78.62.056.1
17720168.464.95.77.12.279.8
18756132.548.04.28.72.163.0
19758157.354.84.812.52.674.7
20836137.148.54.210.12.365.2
Table
Table 5. Pearson’s correlation coefficients for stand density and carbon stock and selected stand parameters on the 20 Scots pine sampled stands.
Table 5. Pearson’s correlation coefficients for stand density and carbon stock and selected stand parameters on the 20 Scots pine sampled stands.
ParameterMean DBHMean HeightBasal AreaStand VolumeAbove Ground BiomassStand Density
C stock in stem0.486 *0.850 ***0.713 ***0.961 ***0.986 ***−0.160
C stock in branches0.599 ***−0.0530.827 ***0.501 *0.413−0.223
C stock in needles0.534 *0.3210.999 ***0.846 ***0.809 ***−0.045
C stock in aboveground biomass0.0110.789 ***0.815 ***0.991 ***1.000 ***−0.184
Percentage of C stock in stem−0.0190.790 ***−0.0260.447 *0.534 *0.005
Percentage of C stock in branches0.061−0.762 ***0.051−0.416−0.505 *−0.041
Percentage of C stock in needles−0.334−0.956 ***−0.186−0.666 ***−0.721 ***0.292
Stand density−0.860 ***−0.508 *−0.044−0.269−0.190−
Significance level: * p < 0.05; ** p < 0.01; *** p < 0.001.

Share and Cite

MDPI and ACS Style

Węgiel, A.; Polowy, K. Aboveground Carbon Content and Storage in Mature Scots Pine Stands of Different Densities. Forests 2020, 11, 240. https://doi.org/10.3390/f11020240

AMA Style

Węgiel A, Polowy K. Aboveground Carbon Content and Storage in Mature Scots Pine Stands of Different Densities. Forests. 2020; 11(2):240. https://doi.org/10.3390/f11020240

Chicago/Turabian Style

Węgiel, Andrzej, and Krzysztof Polowy. 2020. "Aboveground Carbon Content and Storage in Mature Scots Pine Stands of Different Densities" Forests 11, no. 2: 240. https://doi.org/10.3390/f11020240

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop