Next Article in Journal
Mixed-Species Plantation Effects on Soil Biological and Chemical Quality and Tree Growth of A Former Agricultural Land
Previous Article in Journal
Evaluation of Soil Organic Layers Thickness and Soil Organic Carbon Stock in Hemiboreal Forests in Latvia
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Imitated Whole Tree Harvesting Show Negligible Effect on Economic Value of Spruce Stands

Latvian State Forest Research Institute “Silava”, 111 Rigas Street, LV-2169 Salaspils, Latvia
Author to whom correspondence should be addressed.
Forests 2021, 12(7), 841;
Submission received: 13 May 2021 / Revised: 10 June 2021 / Accepted: 23 June 2021 / Published: 25 June 2021
(This article belongs to the Section Forest Ecology and Management)


The increased removal of forest-derived biomass with whole-tree harvesting (WTH) has raised concerns about the long-term productivity and sustainability of forest ecosystems. If true, this effect needs to be factored in the assessment of long-term feasibility to implement such a drastic forest management measure. Therefore, the economic performance of five experimental plantations in three different forest types, where in 1971 simulated WTH event occurred, was compared with pure, planted and conventionally managed (CH) Norway spruce stands of similar age and growing conditions. Potential incomes of CH and WTH stands were based on timber prices for period 2014–2020. However, regarding the economics of root and stump biomass utilization, they were not included in the estimates. In any given price level, the difference of internal rate of return between the forest types and selected managements were from 2.5% to 6.2%. Therefore, Norway spruce stands demonstrate good potential of independence regardless of stump removal at the previous rotation.

1. Introduction

The importance of forest-derived biomass has increased over the last decades [1]. Therefore, bioenergy sources such as forest-residues have potential as partial alternatives for conventional fossil fuels [2]. The use of biomass for energy production also reduces carbon emissions [3,4]. However, the increased removal of biomass from forest stands with whole tree harvesting (WTH) raises uncertainties about the long-term productivity of forest ecosystems [1,4,5,6,7,8,9]. Compared to WTH, conventional harvesting (CH) has a lower impact on site productivity in long-term, mainly because the nutrient-rich components such as foliage and twigs are left in the forest stand [1]. Norway spruce (Picea abies (L.) Karst.) is an economically important tree species which covers extensive areas [10] and has high potential as a source of renewable energy in Northern Europe [11]. Under such conditions, it is crucial to understand responses of the species to intensifying management, including WTH and particularly its effects on the economic value of forests.
The application of WTH might affect soil nutrient dynamics and sustainability of forest ecosystems [12] via changes in soil structure and biochemical cycles [6]. The decrease of soil carbon and nitrogen pools can significantly reduce tree growth, and hence accumulation of biomass [13,14]. However, the effect of WTH can differ regionally and locally [1,5,15,16], for instance in boreal forests no or slight effect of WTH on seedling growth has been observed [8,12,15,17]. On the other hand, 10 to 20 years after a WTH event, some negative effects on tree growth have been reported [8]. Significant growth reduction for Sitka spruce has been reported [18], and growth loss occurs if a high amount of nutrients has been removed from the stand, particularly in nutrient-poor sites [5]. Accordingly, local information is necessary to evaluate the potential for application of WTH as a source for additional biomass. The aim of this study was to evaluate the effect of WTH on economic performance of Norway spruce stands in hemiboreal forests in Latvia. We hypothesized that WTH might have reduced the growth and economic performance of Norway spruce stands growing on mesotrophic soils, compared to conventionally managed stands.

2. Materials and Methods

2.1. Site Description

Five experimental plantations of Norway spruce located in the eastern part of Latvia (56°68′ N, 25°99′ E) growing on dry mineral (Hylocomiosa), wet mineral (Myrtilloso-sphagnosa) and drained mineral (Myrtilloso mel) soils were studied. The plantations were established in 1971, in an area where, after clearcutting, stumps with the top layers of soil and nutrient-rich residues were pushed away with a bulldozer. The experimental design was the same as previously described for Scots pine [19]. As a result, areas of up to 0.5 ha with heavily scarified bare soil and practically absent residual woody biomass were formed. The areas were reforested using two-year-old bare rooted seedlings of Norway spruce raised in a local nursery; the spacing between seedlings was 1 × 2 m. Mechanized plough was used for soil preparation (harrowing). Accordingly, such management and soil erosion resulted in soil depletion [20]. Such effects were previously evidenced by the ground cover vegetation under oligotrophic conditions [19,21]. After reforestation, mechanical weed control was administered for three years; no other management was performed.
In each of the experimental plantations, two circular sampling plots of 500 m2 (r = 12.62° m) were established. Within each sampling plot, diameter at breast height (DBH) of all living trees of DBH ≥ 6.1 cm was measured. In addition, within each sampling plot, tree height of 10 to 15 living trees of different canopy status were measured with accuracy of 0.2 m. For comparison, data from the National Forest Inventory (NFI) were acquired. Data on pure, planted and conventionally managed Norway spruce stands of similar age, growing in comparable conditions across Latvia were selected. Data on 68 plots were selected in total. The NFI uses the same methodology (sampling plots and measurements), as the experimental plantations were sampled.

2.2. Data Analysis

For each tree in the sampling plots of the experimental plantations, height was estimated (extrapolated) based on DBH according to Näslund’s and Gaffrey’s approach [22]. The tree volume with tops was calculated according to a local equation [23], based on the measured DBH and the estimated tree height as follows:
v = 2.3106 × 10 4   ×   H 0.78193 ×   DBH 0.34175 × lg ( H ) + 1.18811
where H is height of tree (m) and DBH is stem diameter at breast height (cm).
The assortment outcome from each harvested tree was calculated using a local model [24]. The calculation of the economic performance of CH and simulated WTH stands was based on timber prices for the period 2014–2020 (Table 1). Considering the local specifics regarding the economics of root and stump biomass utilization [25], they were not included in the estimates.
For each tree based on DBH, incomes were calculated as:
A = ( 1.013 × 0.958 + ( 0.112 ) ×   DBH 0.203 ) ( 0.958 + DBH 0.203 )
where A is the sawlog assortment relative incomes (%) and DBH is the steam diameter at breast height (cm).
Potential income from the forest stand on ha was calculated using following equation:
NWV =   I ha H
where Iha is the potential income from the selected forest type on ha; T is the total timber value per sample plot; and S is the area of the sample plot in m2.
For the calculation of net wood value (NWV), the following equation was used:
NPV = ( NWV E ) ( 1 + r ) n
where Iha is the income from harvesting and H is the harvesting costs (according to the data from Central Statistics Bureau of Latvia). Income and costs were included in the analysis for calculation of net present value (NPV), which was calculated as the discount value of the expected net cash flow:
NPV = ( NWV E ) ( 1 + r ) n
where E is the establishment costs from 2014 to 2020 year; r is the discount rate (3% and 5%); and n is the number of years (48). The establishment costs were acquired from the Central Statistical Bureau of Latvia. To estimate the profitability of the WTH event, the internal rate of return (IRR) was calculated using the following equation:
IRR = r a + NPV a NPV a NPV b ( r b r a )
where ra is the lower discount rate (3%); rb is the higher discount rate (5%); NPVa is NPV at ra; and NPVb is NPV at rb discount rate.
Linear mixed effect models were used to assess the effect of management (CH or WTH) on the economic indicators and stand productivity (basal area and wood volume). The model in general form was:
  Y ijk = μ +   M i +   F i + M i   : F i + ( t i ( j ) ) + ( p k ) +   ε ijk
where Yijk is the calculated economic indicators and stand productivity; Mi is the fixed effect of management (two levels: CH and WTH); Fi is the fixed effect of forest types (three levels); and Mi:Fi is the interaction of both. To account for dependencies in data arising from the different locations (sample plots and forest stands) (tij; 77 levels) and years (pk; 7 levels), they were included in models as nested random effects. The models were estimated in program R v.4.0.4. [26] using the package “lme4” [27].

3. Results and Discussion

From the management perspective, maintaining long-term forest productivity (across tree generations) is essential, and it is also crucial to ensure the overall sustainability of management, since different forest ecosystem services depend on the state of trees in a stand [28]. However, the ecological and economic effects of WTH are still controversial [1]. Regarding such management, there are many concerns, particularly related to nutrient and carbon depletion [29], and excessive disturbance to soil [6,30]. Among of the studied factors, only forest type had a significant individual non-interacted effect on basal area and stand wood volume (Table 2), which could be explained by differences in stand productivity [31]. However, no effect of management type on standing volume and basal area was observed, which might be related to soil mixing (harrowing) during the planting, which has reduced soil compaction and has facilitated ascent of nutrients [32]. In boreal forests in Sweden, long-term studies showed significant loss of basal area and wood volume for Norway spruce 20 years after a WTH event [31]. In boreal forests, lack of nitrogen after biomass removal causes greater tree growth loss compared to CH [17,33]. In hemiboreal forest, however, no nitrogen limitation has been observed after WTH [34]; accordingly, WTH had a negligible effect on Norway spruce stand productivity (Table 3). The variance of random effects (Table 2) of location demonstrated high variability of growth of Norway spruce between and within stands. This implies varying responses to disturbances [1] independent from management (CH and WTH) during the 50-year period. Although the studied experiment represented only ca. half of rotation period of conventional stands in the region (According to Law on Forests in Latvia), the effects of WTH can decrease with age [9]; hence, the observed results could be extrapolated for a full rotation period.
The economic indicators, which integrate effects of stand productivity and market volatility, show no significant difference between WTH and CH (Table 2). Timber market has cyclic patterns, which is a result of interaction of demand, price and timber supplies (assortment structure) [35]. However, due to timber market fluctuation, the NPV provides more accurate estimates for comparison of management types [36,37]. The mean NPV (at 3% discount rate) was 2803 ± 136 EUR ha−1, 2637 ± 292 EUR ha−1 in favorable timber market conditions at conventional and WTH stands, respectively, which demonstrates good potential of financial return after 50 years. Regarding IRR, values in WTH stands ranged from 4.6% to 6.0% (data not shown) when timber prices were low (2015) (Table 1). In the conventional stands, IRR ranged from 2.5% to 6.2% in an unfavorable and from 3.9% to 6.2% in a favorable timber market (data not shown). Under such conditions, WTH stands show good profitability depending on timber market conditions; however, the estimated revenues might decrease due to parity costs [38]. The economic indicators were based on timber value with exclusion of below ground biomass. Hence, stump harvesting was not considered due to technical challenges and costs of harvesting operations [26,39]. However, considering that studied stands did not lose productivity after the simulated repeated WTH, and due to increasing interest in renewable resources, stump harvesting is to be likely revisited as a sustainable resource of additional revenue [40].

4. Conclusions

Norway spruce stands showed good financial return as suggested by economic indicators (such as NPV), even when timber prices were low. If economically and ecologically feasible, WTH as management can be applied. Considering that studied experiments represented severe management practices imitating repeated WTH events, we suggest that additional harvesting of biomass from conventional mesotrophic Norway spruce stands would not compromise their sustainability (performance in following rotations).

Author Contributions

Conceptualization, Ā.J. and I.D.; methodology, I.D. and Z.L.; formal analysis, A.K. and I.D.; data curation, A.A. and A.P.; writing—original draft preparation, A.K., R.M. and I.D.; writing—review and editing, Ā.J., R.M. and Z.L.; supervision, Ā.J.; project administration, Z.L. All authors have read and agreed to the published version of the manuscript.


This research was funded by LVM project “Impact of forest management on forest and related ecosystem services”.

Data Availability Statement

Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Wall, A. Risk analysis of effects of whole-tree harvesting on site productivity. For. Ecol. Manag. 2012, 282, 175–184. [Google Scholar] [CrossRef]
  2. Hamberg, L.; Hotanen, J.-P.; Nousiainen, H.; Nieminen, T.M.; Ukonmaanaho, L. Recovery of understorey vegetation after stem-only and whole-tree harvesting in drained peatland forests. For. Ecol. Manag. 2019, 442, 124–134. [Google Scholar] [CrossRef]
  3. Uri, V.; Aosaar, J.; Varik, M.; Becker, H.; Kukumägi, M.; Ligi, K.; Pärn, L.; Kanal, A. Biomass resource and environmental effects of Norway spruce (Picea abies) stump harvesting: An Estonian case study. For. Ecol. Manag. 2015, 335, 207–215. [Google Scholar] [CrossRef]
  4. Lim, H.; Olsson, B.A.; Lundmark, T.; Dahl, J.; Nordin, A. Effects of whole-tree harvesting at thinning and subsequent compensatory nutrient additions on carbon sequestration and soil acidification in a boreal forest. Glob. Chang. Biol. Bioenergy 2020, 12, 992–1001. [Google Scholar] [CrossRef]
  5. Kaarakka, L.; Tamminen, P.; Saarsalmi, A.; Kukkola, M.; Helmisaari, H.-S.; Burton, A.J. Effects of repeated whole-tree harvesting on soil properties and tree growth in a Norway spruce (Picea abies (L.) Karst.) stand. For. Ecol. Manag. 2014, 313, 180–187. [Google Scholar] [CrossRef]
  6. Kaarakka, L.; Vaittinen, J.; Marjanen, M.; Hellsten, S.; Kukkola, M.; Saarsalmi, A.; Palviainen, M.; Helmisaari, H.-S. Stump harvesting in Picea abies stands: Soil surface disturbance and biomass distribution of the harvested stumps and roots. For. Ecol. Manag. 2018, 425, 27–34. [Google Scholar] [CrossRef]
  7. Egnell, G. Is the productivity decline in Norway spruce following whole-tree harvesting in the final felling in boreal Sweden permanent or temporary? For. Ecol. Manag. 2011, 261, 148–153. [Google Scholar] [CrossRef]
  8. Tamminen, P.; Saarsalmi, A. Effects of whole-tree harvesting on growth of pine and spruce seedling in southern Finland. Scand. J. For. Res. 2013, 28, 559–565. [Google Scholar] [CrossRef]
  9. Karlsson, K.; Tamminen, P. Long-term effects of stump harvesting on soil properties and tree growth in Scots pine and Norway spruce stands. Scand. J. For. Res. 2013, 28, 550–558. [Google Scholar] [CrossRef]
  10. Schelhaas, M.J.; Varis, S.; Schuck, A.; Nabuurs, G.J. EFISCEN Inventory Database; European Forest Institute: Joensuu, Finland, 2006. [Google Scholar]
  11. Egnell, G. A review of Nordic trials studying effects of biomass harvest intensity on subsequent forest production. For. Ecol. Manag. 2017, 383, 27–36. [Google Scholar] [CrossRef]
  12. Saarsalmi, A.; Tamminen, P.; Kukkola, M.; Hautajärvi, R. Whole-tree harvesting at clear-felling: Impact on soil chemistry, needle nutrient concentrations and growth of Scots pine. Scand. J. For. Res. 2010, 25, 148–156. [Google Scholar] [CrossRef]
  13. Weatherall, A.; Proe, M.F.; Craig, J.; Cameron, A.D.; McKay, H.M.; Midwood, A.J. Tracking N, K, Mg and Ca released from decomposing biomass to new tree growth. Part II: A model system simulating root decomposition on clearfell sites. Biomass Bioenergy 2006, 30, 1060–1066. [Google Scholar] [CrossRef]
  14. Hyvönen, R.; Kaarakka, L.; Leppälammi-Kujansuu, J.; Olsson, B.A.; Palviainen, M.; Vegerfors-Persson, B.; Helmisaari, H.-S. Effects of stump harvesting on soil C and N stocks and vegetation 8-13 years after clear-cutting. For. Ecol. Manag. 2016, 371, 23–32. [Google Scholar] [CrossRef]
  15. Wall, A.; Hytönen, J. The long-term effects of logging residue removal on forest floor nutrient capital, foliar chemistry and growth of Norway spruce stand. Biomass Bioenergy 2011, 35, 3328–3334. [Google Scholar] [CrossRef]
  16. Thiffault, E.; Hannam, K.D.; Paré, D.; Titus, B.D.; Hazlett, P.W.; Maynard, D.G.; Brais, S. Effects of forest biomass harvesting on soil productivity in boreal and temperate forests—A review. Environ. Rev. 2011, 19, 278–309. [Google Scholar] [CrossRef]
  17. Helmisaari, H.; Hanssen, K.H.; Jacobson, S.; Kukkola, M.; Luiro, J.; Saarsalmi, A.; Tamminen, P.; Tveite, B. Logging residue removal after thinning in Nordic boreal forests: Long-term impact on tree growth. For. Ecol. Manag. 2011, 261, 1919–1927. [Google Scholar] [CrossRef]
  18. Vanguelova, E.; Pitman, R.; Luiro, J.; Helmisaari, H.-S. Long term effects of whole tree harvesting on soil carbon and nutrient sustainability in the UK. Biogeochemistry 2010, 101, 43–59. [Google Scholar] [CrossRef]
  19. Jansons, Ā.; Robalte, L.; Čakšs, R.; Matisons, R. Long-term effect of whole tree biomass harvesting on ground cover vegetation in a dry Scots pine stand. Silva Fenn. 2016, 50, 1661. [Google Scholar] [CrossRef] [Green Version]
  20. Kalēja, S.; Lazdiņš, A.; Zimelis, A.; Spalva, G. Model for cost calculation and sensitivity analysis of forest operations. Agron. Res. 2018, 16, 2068–2078. [Google Scholar]
  21. Čakšs, R.; Čakša, L.; Desaine, I.; Lībiete, Z.; Elferts, D.; Butlers, A.; Jansons, Ā. Long-Term influence of stump-removal on components of hemiboreal pine forest ecosystem. Sustainability 2021, 13, 2095. [Google Scholar] [CrossRef]
  22. Sharma, R.P.; Vacek, Z.; Vacek, S. Nonlinear mixed effect height-diameter model for mixed species forests in the central part of the Czech Republic. J. For. Sci. 2016, 62, 470–484. [Google Scholar]
  23. Liepa, I. Tree Growth Study; LLU: Jelgava, Latvia, 1996; p. 31. (In Latvian) [Google Scholar]
  24. Ozoliņš, R. Forest stand assortment structure analysis using mathematical modelling. For. Stud. 2002, 7, 33–42. [Google Scholar]
  25. Zimelis, A. Technology for Extraction and Transportation of Coniferous Stumps. Ph.D. Thesis, Latvia University of Life Sciences and Technologies, Jelgava, Latvia, 2020. [Google Scholar]
  26. R Core Team R. A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2020; Available online: (accessed on 15 December 2020).
  27. Bates, D.; Maechler, M.; Bolker, B.; Walker, S. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw. 2015, 67, 1–48. [Google Scholar] [CrossRef]
  28. Lindner, M.; Suominen, T.; Palosuo, T.; Garcia-Gonzalo, J.; Verweij, P.; Zudin, S.; Päivinen, R. ToSIA—A tool for sustainability impact assessment of forest-wood-chains. For. Ecol. Manag. 2010, 221, 2197–2205. [Google Scholar] [CrossRef]
  29. McLaughlin, J.W.; Phillips, S.A. Soil carbon, nitrogen, and base cation cycling 17 years after whole-tree harvesting in a low-elevation red spruce (Picea rubens)-balsam fir (Abies balsamea) forested watershed in central Maine, USA. For. Ecol. Manag. 2006, 222, 234–253. [Google Scholar] [CrossRef]
  30. Persson, T. Environmental consequences of tree-stump harvesting. For. Ecol. Manag. 2013, 290, 1–4. [Google Scholar] [CrossRef]
  31. Helmisaari, H.-S.; Kaarakka, L.; Olsson, B.A. Increased utilization of different tree parts for energy purposes in the Nordic countries. Scand. J. For. Res. 2014, 29, 312–322. [Google Scholar] [CrossRef]
  32. Palviainen, M.; Finer, L. Estimation of nutrient removals in stem-only and whole-tree harvesting of Scots pine, Norway spruce, and birch stand with generalized nutrient equations. Eur. J. For. Res. 2012, 131, 945–964. [Google Scholar] [CrossRef]
  33. Tveite, B.; Hanssen, K.H. Whole-tree thinnings in stands of Scots pine (Pinus sylvestris) and Norway spruce (Picea abies): Short- and long-term growth results. For. Ecol. Manag. 2013, 298, 52–61. [Google Scholar] [CrossRef]
  34. Kļaviņš, I.; Bārdule, A.; Lībiete, Z.; Lazdiņa, D.; Lazdiņš, A. Impact of biomass harvesting on nitrogen concentration in the soil solution in hemiboreal woody ecosystems. Silva Fenn. 2019, 53, 10016. [Google Scholar] [CrossRef]
  35. Banaś, J.; Kożuch, A. The Application of Time Series Decomposition for the Identification and Analysis of Fluctuations in Timber Supply and Price: A Case Study from Poland. Forests 2019, 10, 990. [Google Scholar] [CrossRef] [Green Version]
  36. Simonsen, R.; Rosvall, O.; Gong, P.; Wibe, S. Profitability of measures to increase forest growth. For. Policy Econ. 2010, 12, 473–482. [Google Scholar] [CrossRef]
  37. Holopainen, M.; Mäkinen, A.; Rasinmäki, J.; Hyytiäinen, K.; Bayazidi, S.; Pietilä, I. Comparison of various sources of uncertainty in stand-level net present value estimates. For. Policy Econ. 2010, 12, 377–386. [Google Scholar] [CrossRef]
  38. Gailis, A.; Kārkliņa, A.; Purviņš, A.; Matisons, R.; Zeltiņš, P.; Jansons, Ā. Effect of Breeding on Income at First CommercialThinning in Silver Birch Plantations. Forests 2020, 11, 327. [Google Scholar] [CrossRef] [Green Version]
  39. Lībiete, Z.; Bārdule, A.; Kļaviņš, I.; Kalvīte, Z.; Lazdiņš, A. Medium-term impact of stump harvesting on general soil parametrs in Hylocomiosa site type. Res. Rural Dev. For. Wood Process. 2019, 1, 58–64. [Google Scholar]
  40. Jönsson, M.; Sjögren, J.; Hannrup, B.; Larsolle, A.; Mörtberg, U.; Nordström, M.; Olsson, B.A.; Strömgren, M. A Spatially Explicit Decision Support System for Assessment of Tree Stump Harvest Using Biodiversity and Economic Criteria. Forests 2020, 12, 8900. [Google Scholar] [CrossRef]
Table 1. The assortments by diameter at the top end and monetary value during the period from 2014 to 2020.
Table 1. The assortments by diameter at the top end and monetary value during the period from 2014 to 2020.
AssortmentLength, mDiameter at the Top End, cmPrice, EUR m3
Sawlog A3.026.073696768767464
Sawlog B3.018.071676066747060
Sawlog C3.014.050495646555343
Table 2. The effect (Chi square) of management, forest type and their interaction on economic performance and stand productivity, and the variances of random effect. The asterisks denote statistical significance (p-values) of the effects: * < 0.05, ** < 0.01, and *** < 0.001.
Table 2. The effect (Chi square) of management, forest type and their interaction on economic performance and stand productivity, and the variances of random effect. The asterisks denote statistical significance (p-values) of the effects: * < 0.05, ** < 0.01, and *** < 0.001.
Fixed EffectRandom Effect
ManagementForest TypeManagement × Forest TypeSample Plot × LocationLocationYearResiduals
Chi SquareVariance
NWV0.0219.50 ***0.3328,975,815975,1251,449,187989,183
NPV (3%)0.0317.71 ***0.411,702,977105,20549,04957,095
NPV (5%)0.0315.01 ***0.43284,44320,83775149353
IRR0.159.37 **0.182.59 × 10−51.60 × 10−62.44 × 10−62.60 × 10−6
Basal area (m2·ha−1)0.107.54 *1.5067.020.27 8.83
Wood volume m3·ha−10.1911.25 **0.561.14 × 10+41.10 × 10−7 9.46 × 10+2
Table 3. The mean values of tree stand productivity for the analyzed forest types in the conventional (CH) and whole tree harvested (WTH) stands.
Table 3. The mean values of tree stand productivity for the analyzed forest types in the conventional (CH) and whole tree harvested (WTH) stands.
ManagementForest TypeBasal Area, m2/ha−1Wood Volume, m3/ha−1
Hylocomiosa29.1 ± 3.9295.0 ± 52.3
CHMyrtilloso-sphagnosa23.4 ± 2.9206.5 ± 33.6
Myrtillosa mel29.6 ± 3.0305.1 ± 37.1
Hylocomiosa24.3 ± 0.5264.8 ± 7.1
WTHMyrtilloso-sphagnosa21.4 ± 2.8203.7 ± 26.8
Myrtillosa mel36.4 ± 4.3367.7 ± 44.4
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Desaine, I.; Kārkliņa, A.; Matisons, R.; Pastare, A.; Adamovičs, A.; Lībiete, Z.; Jansons, Ā. Imitated Whole Tree Harvesting Show Negligible Effect on Economic Value of Spruce Stands. Forests 2021, 12, 841.

AMA Style

Desaine I, Kārkliņa A, Matisons R, Pastare A, Adamovičs A, Lībiete Z, Jansons Ā. Imitated Whole Tree Harvesting Show Negligible Effect on Economic Value of Spruce Stands. Forests. 2021; 12(7):841.

Chicago/Turabian Style

Desaine, Iveta, Annija Kārkliņa, Roberts Matisons, Anna Pastare, Andis Adamovičs, Zane Lībiete, and Āris Jansons. 2021. "Imitated Whole Tree Harvesting Show Negligible Effect on Economic Value of Spruce Stands" Forests 12, no. 7: 841.

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