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The timber and energy biomass potential of intensively managed cloned Norway spruce stands

Authors


Correspondence: Heli Peltola, tel. + 358 40 588 0005, fax + 358 13 251 3634, e-mail: heli.peltola@uef.fi

Abstract

We used ecosystem model simulations to study the timber and energy biomass potential offered by intensively managed cloned Norway spruce stands. More specifically, we analysed how the use of cloned trees compared with non-cloned trees, together with thinning, nitrogen (N) fertilisation and rotation length (from 60 to 100 years), affects the annual mean production of timber (i.e., saw logs, pulpwood) and energy biomass (i.e., stumps and harvesting residuals in the final felling) and its economic profitability [annual mean of net present value (NPV) with a 2% interest rate]. Furthermore, we employed a life cycle analysis/emission calculation tool to assess the total net CO2 emissions per unit of energy (kg CO2 MW h−1) produced based on energy biomass. We found that both the annual mean production of timber and the NPV increased substantially, regardless of the management regime, if cloned trees with an annual growth increase of up to 30% compared with non-cloned trees were used in regeneration. In general, the use of a short rotation with N fertilisation clearly increased the annual mean of the NPV. Consequently, the use of cloned trees also clearly increased the annual mean production of energy biomass and decreased the total net CO2 emissions per unit of energy produced based on energy biomass. However, the total annual net CO2 emissions were the lowest if a long rotation was used with N fertilisation. To conclude, the use of cloned trees together with intensive management could potentially be highly beneficial for the cost-efficient and sustainable production of timber and energy biomass in an integrated way.

Introduction

Norway spruce [Picea abies (L.) Karst] is among the most important coniferous species, both in Finland and Sweden and elsewhere in Europe. It is an important source of raw material, especially for solid wood products and pulp and paper products, but also for bioenergy. Recent commitments regarding the shares of renewable energy in the European Union have increased the pressure to use forest biomass for renewable energy to decrease the carbon emissions resulting from the use of fossil fuels. Thus, there is increasing demand to produce both timber and energy biomass simultaneously in a sustainable and cost-efficient way. For the same reason, there is increasing pressure to increase the intensity of forest management substantially in selected areas to balance the needs for timber and energy biomass with the need to produce other ecosystem goods and services such as wildlife, recreational environments and the maintenance of biodiversity in forested ecosystems.

Under the boreal conditions of the Nordic countries, the growth of Norway spruce is affected primarily by the prevailing temperature conditions (e.g., the temperature sum) during the growing season and the availability of nitrogen (N) because the species naturally occupies sites with a moderate and ample supply of soil water (Linder & Axelsson, 1982; Linder, 1987; Bergh et al., 1999; Sampson & Allen, 1999). In terms of management, the use of a higher initial stand density, a suitable thinning regime, N fertilisation and a shorter rotation may increase both the annual production of timber and energy biomass and its economic profitability in Norway spruce (e.g., Routa et al., 2011b, 2012). In contrast, longer rotations may be needed to reduce the annual net carbon emissions resulting from the production of wood-based energy (e.g., Routa et al., 2011b, 2012).

In general, the productivity of Norway spruce stands can be further increased with improved seeds collected from seed orchards (half-sib and full-sib families) or vegetative propagation (clones) to provide seedlings for planting. The use of clonal material in Norway spruce is still limited in practical forestry due in part to the high costs of such seedlings, even though their potential to produce high genetic gains is obvious (Karlsson, 2000; Högberg, 2003). Based on recently harvested clonal material in Norway spruce from trials established in the 1970s in southern and central Finland, it has also been found that certain clones have, on average, a higher stem volume and above-ground biomass production (including the stem, branches, and needles) but also have a higher wood density compared with the average over all clones (Zubizarreta Gerendiain et al., 2008, 2009; Kilpeläinen et al., 2010).

The growth of different genetic entries in the seedling phase or at a young age has typically been used to evaluate their potential as regeneration material for practical forestry. Isik et al. (2010) found that the growth in height at a young age effectively ranks different genetic entries in Norway spruce in terms of their productivity, even at a later stage during the rotation. However, the trials with improved genetic entries, such as clones of Norway spruce, are still at an early stage (age <50 years) both in Finland and in Sweden. Therefore, it remains difficult to be certain whether the most successful genetic entries at an early age could maintain their ranking after canopy closure, as was found in Loblolly pine (Pinus taeda), for example (Svensson et al., 1999). For the same reason, it is difficult to determine whether their superior growth will persist over the rotation, compared with non-improved seedlings. Nevertheless, the use of forest ecosystem models may provide a useful way to evaluate how sensitive the sustainable and cost-efficient production of timber and energy biomass may be in the long run to the use of various genetic entries (i.e., representing different growth rates) and to management, e.g., spacing in planting, thinning, N fertilisation and the length of the rotation.

Based on simulations with an ecosystem model, we studied the timber and energy biomass potential offered by intensively managed cloned Norway spruce stands. More specifically, we analysed how the use of cloned trees, with an increase of 10–30% in the annual growth rate compared with non-cloned trees, together with thinning and nitrogen fertilisation and rotation length (from 60 to 100 years), affects the annual mean production of timber (i.e., saw logs, pulpwood) and energy biomass (i.e., stumps and harvesting residuals in the final felling) and economic profitability [the annual mean of net present value (NPV)]. In addition, a Life Cycle Analysis/Emission calculation tool (Kilpeläinen et al., 2011) was employed to assess the net CO2 emissions per unit of energy (kg CO2 MW h−1) produced based on energy biomass. In previous papers on related subjects published, for example, by Routa et al. (2011a,b, 2012), the potential offered by cloned trees in forest regeneration was not considered at all in model-based analyses.

Materials and methods

Outlines of the ecosystem model

In this work, a gap-type ecosystem model, SIMA (Kellomäki et al., 2005, 2008), was used to simulate the growth and dynamics of tree stands over the rotation as controlled by management. A time step of 1 year was used. In the model, tree growth is based on the diameter growth at breast height [D, cm a−1], the product of the diameter growth [Do, cm a−1] in optimal conditions and the growth conditions for trees, i.e., D = Do·M1…M5, where M1…M4 are the multipliers for the temperature sum, the within-stand light conditions and the availability of soil moisture and nitrogen. The diameter growth under optimal conditions is as follows:

display math(1)

where CO2 is the carbon dioxide concentration in the atmosphere and a, b and DGRO are parameters with the values −1.307, −1643 and −0.0562, respectively, for Norway spruce (Kellomäki et al., 2008).

The tree height is calculated from the stem diameter at breast height. This calculation is based on the method presented by Näslund (1936). The calculation of the mass components (stem, foliage, branches and roots) of the tree is based on the allometric relationship between the diameter and mass of tree components [Mass(i,j)]:

display math(2)

where a(i,j), b(i,j) and c(i,j) are parameters specific for tree species i and mass component j (Kolström, 1998). Furthermore, the form and the volume of the stem are calculated using methods presented by Laasasenaho (1982). Based on the stem form, the yield of saw logs, pulpwood and the top part of the stem were determined by the minimum top diameter for pulpwood and saw logs (6.5 and 14.5 cm, respectively).

In the simulations, the Monte Carlo technique is used, i.e., events, such as the death of trees, are stochastic. Therefore, the simulations should be repeated many times (in this study, 150 times) to determine the central tendency of the variation over time in the growth and development of the tree stand under the selected management regime. The death of the trees is determined by the level of crowding and the resulting reduction in growth. These factors determine the probability that a tree will die at a given moment. Litter and dead trees ultimately decompose in contact with the soil, where they release nitrogen over long time periods in response to the quality of the litter (the lignin and nitrogen content) and the evapotranspiration at the site (Kellomäki et al., 2008).

The possible management options may include varying the initial stand density (spacing), tending the seedling stand (cleaning), thinning, nitrogen fertilisation and varying lengths of rotation. These options affect the growth of trees and the production of timber (saw logs and pulpwood) and energy biomass. The energy biomass includes logging residuals (foliage, branches, and top parts of stems not suitable for timber), coarse roots and stumps.

Previous simulations with the SIMA model (e.g., Kellomäki et al., 2008; Routa et al., 2011a,b) have shown good agreement with the measured values of volume growth on the permanent sample plots of the National Forest Inventory (NFI) throughout Finland. Furthermore, parallel simulations with the empirical growth and yield model Motti (Hynynen et al., 2002) and the SIMA model have exhibited good agreement for the predicted volume growth (Kellomäki et al., 2008; Routa et al., 2011a,b, 2012). Based on fertilising experiments, Mäkipää et al. (1998) have also shown good agreement between the simulated and measured growth responses of Norway spruce to nitrogen fertilisation. Good agreement also resulted from the comparison by Routa et al. (2011a) of parallel simulations performed with the SIMA and Motti models to evaluate the response of Norway spruce stands to nitrogen fertilisation.

Introducing the effect of genetic entries on growth into the ecosystem model

The effect of genetic entries was introduced into the ecosystem model SIMA by tuning the values of parameter b in Eqn (1) to represent the variation in growth among genetic entries. Figure 1 shows that the function has the same form regardless of the parameter value but that the level of growth is relative to the value of parameter b, scaling the value of potential growth. This claim is supported by the analyses of the diameter growth of Norway spruce clones in two clonal trials established in the 1970s by the Finnish Forest Research Institute, as discussed in detail below.

Figure 1.

Performance of the potential diameter growth of Norway spruce as a function of diameter if the value of parameter b in Eqn (1) is increased by 10% and by 30%.

The first data set represents the clonal trial established in Imatra (61°08′N, 28°48′E) in 1974 on agricultural soil (fertility representing the Oxalis-Myrtillus site type (OMT, see Cajander, 1926). In the plantation, the initial spacing was 2 × 2.5 m, and the clones were of southern and central Finnish origin. In 2004, a set of sample trees was harvested representing 20 clones. Nine to ten sample trees per clone were selected randomly for growth measurements. The second data set represents the clonal trial established in Kangasniemi (61°59′N, 26°38′E) in 1979. Its initial spacing was 2 × 2 m, and the trial was situated on an upland forest site representing the Myrtillus (MT) site type. In 2007, a set of sample trees was harvested from this trial, representing 10 clones of southern and central Finnish origin. Four to five sample trees per clone were selected randomly for growth measurements.

ITRAX X-ray microdensitometer (Cox Analytical Systems, Göteborg, Sweden) measurements were performed (for the details of the methodology, see Zubizarreta Gerendiain et al., 2008, 2009; Kilpeläinen et al., 2010). The annual ring widths from pith to bark were measured based on wood discs cut at a height of 1.3 m for each sample tree. First, the measurements were used to define the diameter over all cambial ages and the diameter 10 years previously. Second, the measurements were used to determine whether the genetic entries showing the highest final diameter also showed the highest diameter 10 years earlier. Figure 2 shows that the diameter of the sample trees 10 years earlier correlated well with the final diameter for both trials. Furthermore, the rank of the clones with the highest diameter remained the same over time, as assumed in the introduction of the effects of genetic entries into the ecosystem model through the tuning of the values of parameter b in Eqn (1).

Figure 2.

Correlation between the diameter differences (%) measured 10 years apart for sample trees harvested from the Imatra and Kangasniemi trials. The x-axis represents the diameter at the first measurement 10 years previously, and the y-axis represents the final diameter. The same clones showed the greatest diameter growth regardless of the time period studied.

The performance of the SIMA model was evaluated with a sensitivity analysis. For this purpose, the simulations were performed both without tuning and with tuning of the value of parameter b in Eqn (1) to calibrate the model for the growth of the clonal trees. In the first simulation exercise (without tuning), the mean diameter of sample trees of all clones at the seedling phase was used for the initial diameter of the trees. This value was obtained from the ring width measurements. In the second simulation exercise (with tuning), the mean diameter of the sample trees of the three clones with the largest growth at the seedling phase (and the largest final diameter) was used for the initial diameter of the trees. The details of the simulation results are given in Table 1, which also shows the mean values of the initial diameter and the number of trees in the three cohorts used to initialise all simulations for both trials. The simulations for Imatra and Kangasniemi extended over 25 and 23 years, respectively. In the simulations excluding tuning, the value of parameter b (−1.643) was the estimate obtained by Kellomäki et al. (2008) from NFI data for Norway spruce over all of Finland. In the simulations including tuning, the value of parameter b was selected to represent increases in the potential diameter growth of 10% (b = −1.309), 20% (b = −1.005) and 30% (b = −0.725) These values represented the possible range of increase resulting from the use of clonal Norway spruce.

Table 1. The comparison of measured and simulated diameter (D, at breast height) and tree height, on average of all the clones and for three clones with highest final diameter in Imatra and Kangasniemi trials. Minus means, that simulation underestimated the real measurements and vice versa
 Final valuesSimulated diff.: growth not tunedSimulated diff.: growth tuned +10%Simulated diff.: growth tuned +20%Simulated diff.: growth tuned +30%
D, mm ± SDH, dm ± SDD, % changeH, % changeD, % changeH, % changeD, % changeH, % changeD, % changeH, % change
  1. a

    In Imatra trial the average diameter was 2.8 ± 0.5 cm for all sample trees (with DBH age 4 years) and 3.1 ± 0.4 cm for selected three clones (C308, C43 and C331), respectively. The number of seedlings ha−1 was 600, 800 and 600 for three cohorts in simulations over next 25 years.

  2. b

    In Kangasniemi trial the average diameter was 2.8 ± 1.0 cm for all sample trees (with DBH age 2 years) and 3.5 ± 1.1 cm for selected three clones (C430, C354 and C338), respectively. The number of seedlings ha−1 was 750, 1000 and 750 for three cohorts in simulations over next 23 years.

Imatraa
 Average of all clones136 ± 20129 ± 12−19.7−15.3−13.7−9.3−6.8−2.8−2.51.2
 Average of selected 3 clones (V308, V43, V331)154 ± 16137 ± 6−25.7−17.0−17.8−9.0−14.3−5.5−10.9−2.2
Kangasniemib
 Average of all clones98 ± 30111 ± 27−6.2−22.3−3.6−19.71.0−16.14.9−13.0
 Average of selected 3 clones (V430, V354, V338)117 ± 25125 ± 11−12.6−23.3−9.7−15.4−6.4−18.2−3.0−15.6

In the analysis, the simulated values of final diameter and height were compared with the corresponding measured values. In case 1, the simulated values were compared with the mean values over all the clones. In case 2, the simulated values were compared with the mean values of the three clones with the highest measured values of the diameter. In the simulations excluding the tuning of parameter b, the simulated diameter in case 1 was 19.7% lower in Imatra and 6.2% lower in Kangasniemi than the measured values, whereas in case 2 the corresponding simulated diameters were 25.7% and 12.6% lower than the measured values (Table 1). The results obtained for the height showed that the differences between the simulated and measured values were of the same magnitude but larger in Kangasniemi than in Imatra in both cases.

In the simulations in which the value of b was tuned to increase the potential diameter growth by 30%, the difference between the measured and simulated diameter ranged from −2.5 to +4.9% in case 1 and from −10.9 to −3.0% in case 2 in Imatra and Kangasniemi, respectively (Table 1). The simulations of height and of diameter showed contrasting results. The simulated height differed less from the measured height in Imatra (+1.1 to −2.2%) than in Kangasniemi (−13.0 to −15.6%). The tuning of the value b to increase the potential diameter growth by 30% appears to be reasonable to calibrate the model for simulations of the growth of clonal Norway spruce to agree with the measured values. Nevertheless, we used 10%, 20% and 30% increases in the potential diameter growth in the final simulations to demonstrate the sensitivity of the timber and energy biomass yields and the subsequent CO2 emissions from the use of energy biomass to the use of clonal trees in regeneration. Based on previous work by Kilpeläinen et al. (2010), the allometry of the Norway spruce clones was expected to follow that of the non-clonal trees. Therefore, we used Eqn (2) with its original parameter values to calculate the mass of the crown. We also assumed that the original parameter values are also valid for the calculation of the masses of the stump and the coarse roots.

Model-based analyses

The simulations were performed on a medium-fertile (Myrtillus type, MT) site in central Finland (61.59°N, 26.38°E, 1150–1200 d.d.). The initial amount of organic matter in the soil was 67 Mg ha−1, as estimated from NFI data for the region (Kellomäki et al., 2008). At the beginning of the simulations, the average diameter of the trees was 2 cm, but the initial stand density ranged from 2000 to 3000 trees per hectare depending on the management scenario. The thinning rules used in the simulations followed those recommended for Norway spruce in central Finland (Anon, 2006). The first commercial thinning (from below) was performed at the dominant height of 13 m to achieve a stand density of 900–1000 trees ha−1. Thinning was performed one to three times over a rotation, depending on the rotation length. If nitrogen fertilisation (150 kg N ha−1 a−1) was used, it was performed twice; i.e., first at the time of the first thinning and once thereafter, 10 years later. In each management scenario, the rotation lengths of 60, 80 and 100 years were used. In thinning, only timber (saw logs and pulpwood) was harvested, whereas in the final felling both timber and energy biomass were harvested.

Based on the model outputs (i.e., timber and energy biomass), the annual mean of the net present value (NPV, € ha−1 a−1, with a 2% interest rate) for timber and energy biomass production was calculated. For this purpose, all incomes and costs over the simulation time were discounted. The regeneration costs included soil preparation (mounding, 264 € ha−1) and planting costs (0.2 € per tree for non-cloned and 0.3 € per tree for cloned trees; see Aronen, 2011). The cost of nitrogen fertilisation was 214 € ha−1. The average stumpage prices used were 48.6 and 21.5 € m−3 for saw logs and pulpwood, whereas the price used for the energy biomass was 4 € m−3. An average wood density of 400 kg m−3 was used in the calculations of the volume of the energy biomass based on its dry weight. The prices and management costs used are the average values for the years 2000–2010 (Metinfo – forest information services, 2011).

Based on the outputs of the ecosystem model, the Life Cycle Assessment (LCA) Tool (Kilpeläinen et al., 2011) was used to calculate the net carbon dioxide (CO2) emissions due to the main phases of forest production from nursery to the yard of the power plant using energy biomass. These phases included the CO2 uptake during growth and the CO2 emissions from management, the decomposition of the soil organic matter and the burning of the energy biomass. In the LCA calculations, the following output variables of the SIMA model were used: (i) the annual growth (stem, branches, foliage, coarse roots and fine roots) and (ii) the amount of timber harvested in thinning and the timber and energy biomass harvested in the final felling (assuming a 30% harvesting loss of the needles). Furthermore, the SIMA model provides the value of the annual litter fall for the decomposition and associated emissions of carbon from the soil for the LCA analyses. The net emissions for energy biomass were converted into CO2 emissions per unit of energy (kg CO2 MW h−1). The value used for the energy content of the fuel (diesel) was 38.6 MJ l−1, and the value used for the carbon content of the fuel was 0.857 kg l−1. In the calculations, the dry biomass was assumed to have a carbon content of 50%.

Results

Yield of production of timber and energy biomass

The annual yield of timber varied from 4.4–5.3 and 4.8–5.5 m3 ha−1 a−1 without and with nitrogen fertilisation, if non-cloned Norway spruce seedlings were planted. The corresponding values were 6.4–7.0 and 6.5–7.4 m3 ha−1 a−1 if cloned Norway spruce seedlings were planted and 30% increase in the potential diameter growth was assumed (cloned trees +30% hereafter) (Fig. 3). In general, a rotation length of 80 years produced the highest timber yield. The use of cloned trees +30% increased the annual yield of timber by 29–41% and 34–35% without and with fertilisation. The increase in the annual yield was greatest for a rotation length of 60 years. The use of a higher initial stand density of 3000 trees ha−1 (compared with 2000 trees ha−1) increased the timber yield by only 1–5% and 1–4% without and with fertilisation, regardless of the rotation length and the seedling material used in planting.

Figure 3.

Mean annual timber yield (m3 ha−1 a−1) with varying initial stand density and rotation length, without and with nitrogen fertilisation, for cloned and non-cloned seedlings.

The annual yield of energy biomass varied from 2.3–3.2 and 2.5–3.4 m3 ha−1 a−1 without and with nitrogen fertilisation, if non-cloned trees were planted (Fig. 4). The corresponding values were 2.4–3.7 and 2.7–3.6 m3 ha−1 a−1 if cloned trees (+30%) were planted. A rotation length of 60 years gave the highest annual mean yield of energy biomass. The use of cloned trees (+30%) increased the annual yield of energy biomass by 4–22% and 1–21% without and with fertilisation. The increase was the greatest for a rotation length of 80 years. The use of a higher initial stand density increased the average yield of energy biomass by 6% without fertilisation. However, no increase in the average yield of energy biomass occurred with fertilisation, regardless of the rotation length and the seedling material used in planting.

Figure 4.

Mean annual yield of energy biomass (m3 ha−1 a−1) with varying initial stand density and rotation length, without and with nitrogen fertilisation, for cloned and non-cloned seedlings.

Profitability of production of timber and energy biomass

The NPV with an interest rate of 2% varied from 29.8–44.1 and 29.5–47.2 € ha−1 a−1 without and with nitrogen fertilisation, if non-cloned trees were planted. The corresponding values were 47.8–69.9 and 52.4–72.2 € ha−1 a−1, if cloned trees (+30%) were planted. In general, a rotation length of 60 years gave the highest NPV per year. The use of cloned trees (+30%) increased the NPV by 36–60% and 45–88% without and with fertilisation, regardless of the rotation length (Fig. 5). The NPV was also 2–4% higher with an initial stand density of 2000 trees ha−1 than with a higher initial stand density, regardless of the rotation length and the seedling material used in planting.

Figure 5.

Difference (%) in the annual mean net present value (NPV, € ha−1 a−1) with varying initial stand density and rotation length, without and with nitrogen fertilisation, for cloned and non-cloned seedlings.

Our results also showed that the increase in the yield of timber and energy biomass and the NPV (with 2% interest rate) were all strongly affected by the expected increase in the potential diameter growth of the cloned trees (up to +30%) (see Figs 3-5). The difference between the cloned and non-cloned trees was clearly less if only a 10–20% increase in potential diameter growth was expected for the cloned trees compared with the non-cloned trees, i.e., 11–17% and 26–30% for the NPV without and with fertilisation, respectively.

Total net CO2 emissions per unit of energy produced based on energy biomass

The total annual net CO2 emissions per unit of energy based on biomass varied from 1.0–2.4 and 1.0–2.0 kg CO2 MW h−1 a−1 without and with nitrogen fertilisation, if non-cloned Norway spruce trees were planted. The corresponding values were 0.3–0.8 and 0.2–0.6 kg CO2 MW h−1 a−1, if cloned trees were planted (+30%) (Fig. 6). In general, a rotation length of 100 years gave the lowest total net CO2 emissions, but the use of cloned trees (+30%) reduced the total net CO2 emissions by 34–76% and 61–80% without and with fertilisation. The reduction was the greatest for the rotation lengths of 80 and 100 years without and with fertilisation. Thus, the use of cloned trees (+30%) simultaneously provided both higher annual means for NPV and lower total net CO2 emissions per unit of energy based on biomass, as shown in Fig. 7. The use of a higher initial stand density of 3000 trees ha−1 (compared with 2000 trees ha−1) reduced the average emissions by 11% and 6% without and with fertilisation, regardless of the rotation length and the seedling material used in planting.

Figure 6.

Annual means for total net CO2 emissions with varying initial stand density and rotation length, without and with nitrogen fertilisation, for cloned and non-cloned seedlings.

Figure 7.

Relationship between annual means of net present value and total net CO2 emissions per unit of energy produced based on energy biomass with varying initial stand density and rotation length, without and with nitrogen fertilisation, for cloned and non-cloned seedlings.

Discussion

Based on simulations with a forest ecosystem model, we studied the timber and energy biomass potential offered by intensively managed cloned Norway spruce stands. More specifically, we studied the sensitivity of the production of timber and energy biomass and its economic profitability (NPV) to the use of cloned Norway spruce seedlings in planting, assuming an annual volume growth increase of up to 30% compared with non-cloned trees. In the simulations, we applied varying management regimes in which the initial stand density varied from 2000 to 3000 seedlings ha−1 and the timing and intensity of thinning followed the recommendations currently applied in Finnish private forestry. The rotation length varied from 60 to 100 years, and the simulations were performed both without and with nitrogen fertilisation. We also assessed the total net CO2 emissions per unit of energy produced (kg CO2 MW h−1) based on energy biomass by employing a Life Cycle Analysis/Emission calculation tool.

To study the potential offered by intensive management with cloned trees, we introduced the clonal effect into the SIMA model by modifying the parameterisation of the function describing the potential diameter growth based on experimental data obtained from two clonal trials in southern and central Finland. This simulation analysis showed that the potential diameter growth of cloned Norway spruce trees was 30% higher than that of the non-cloned trees. We also assumed that this difference would persist over time, as indicated by our experimental data. Previously, Isik et al. (2010) also suggested that the height development of seedlings of Norway spruce could effectively predict the height development later in the rotation.

In the simulations, the use of clonal trees, with a 30% increase in the potential diameter growth compared with non-cloned trees, increased the yield of timber by 29–41% and that of energy biomass by 1–22% compared with the use of non-cloned trees. In general, the nitrogen fertilisation enhanced the growth of the trees but reduced the yield differences between the cloned and non-cloned trees. These yield differences were also reduced by increases in the rotation length. Our simulation results demonstrate the benefits resulting from the use of cloned regeneration material. These results are consistent with the findings reported for the first generation of seed orchards of Norway spruce in Sweden. The use of seedlings derived from contemporary Swedish seed orchards generally results in a volume production gain of 10–15% relative to that achieved with unimproved trees. The new seed orchards that are being established are expected to raise this gain to ca. 25% (Rosvall et al., 2001). In contrast, the selection of a rapidly growing genetic entry with high volume growth may have a negative influence on dry biomass production if it simultaneously produces a significant decrease in wood density. However, previous studies have found that certain Norway spruce clones have a higher aboveground biomass production and a higher wood density, on the average, than the corresponding averages over all clones used in those studies (e.g., Zubizarreta Gerendiain et al., 2009; Kilpeläinen et al., 2010).

In assessing the profitability of the use of cloned trees in planting, we used regeneration costs that were 50% higher for cloned trees than for non-cloned trees. Nevertheless, the annual mean NPV of management with cloned trees was substantially higher than that found for the non-cloned trees. Depending on the rotation length, the use of cloned trees with a 30% increase in the potential diameter growth increased the NPV by 36–60% and 45–88% without and with fertilisation, respectively. However, the production of timber and energy biomass and its economic profitability were sensitive to the magnitude of potential growth. For example, the use of cloned trees with a 10% increase in the potential diameter growth resulted, on the average, in NPVs that were 11% and 17% higher without and with fertilisation, respectively. If higher interest rates had been used, the difference in the NPV between the cloned and non-cloned tree stands would have been even higher.

Previous research has shown that the harvesting of energy biomass at the first thinning has also been found profitable (compared with business-as-usual management) in non-cloned Norway spruce stands with a relatively high initial stand density. This increase in profitability is due to higher biomass production (i.e., timber and energy biomass) (see, e.g., Routa et al., 2012). The difference in the yield of energy biomass between non-cloned and cloned trees (+30%) could also have been even greater in this study if we had harvested energy biomass at the first commercial thinning. In contrast, due to the higher regeneration costs of cloned seedlings and the low unit price of energy biomass, energy biomass harvesting from precommercial thinning with a higher initial stand density may not be economically as profitable in cloned stands than in non-cloned ones. However, the NPV also depends on the prices assumed for timber and energy biomass (and on the interest rate used), and clearly a higher price for timber, especially for saw logs but also for pulpwood, will generally favour timber production rather than energy biomass production.

The results of the current analysis of energy production showed that the use of cloned trees (+30%) also clearly reduced the total net CO2 emissions per energy unit compared with the corresponding total emissions if non-cloned trees were planted. Without fertilisation, this decrease was as much as 74% for rotation lengths of 60 and 80 years and 40% for a rotation length of 100 years. The corresponding reduction with fertilisation was between 67–76% regardless of rotation length. Based on this study, the use of improved regeneration material (such as clones) and intensive management in Norway spruce stands could offer large potential gains for integrated timber and energy biomass production. From an economic perspective, clonal forestry appears, in general, to be an attractive option in biomass production. This option may also offer better potential opportunities to mitigate the CO2 emissions associated with energy production than those provided by plantations with non-cloned trees. However, few studies of this type have previously been conducted. In this context, the topic of potential mitigation opportunities should be studied further in detail to generalise our findings.

Acknowledgements

The University of Eastern Finland (UEF), School of Forest Sciences and the Finnish Forest Research Institute (FFRI), Eastern Finland Regional Unit in Joensuu and Haapastensyrjä Breeding Station are acknowledged for supporting this study. The clonal material (sample trees) used in model development was also originally selected by the Finnish Forest Research Institute. The supporting staff and trainees of FFRI (Haapastensyrjä Breeding Station) and Mr Jarmo Pennala, Ms Marja Kuskelin, Dr Antti Kilpeläinen and Dr Ane Zubizarreta Gerendiain from the School of Forest Sciences at UEF helped with the field work. Furthermore, Jarmo Pennala assisted with the X-ray measurements. This work was also supported through the Project under the Finland Distinguished Professor Programme (FiDiPro, No. 127299-A5060-06) of the Academy of Finland.

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