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ISSN 2029-9230

673

2017, Vol. 23, No. 3 (46)

Introduction

Poplar plantations play one of the key roles in the

industrial wood supply in countries such as China, France,

India, Italy and Turkey, and each of them produces more

than 1 million m3 of poplar wood from specialised planta-

tions (Spinelli and Magagnotti 2011). Managed on 10 to

30 years rotations, some of the clones can produce ve-

neer logs (Hongyuan 1992).

Poplars are one of the most productive tree species

in Serbia, which production complexity requires rational

and well-planed management, whereby the site and spe-

cies potentials would be maximally used (Keèa and Pajiã

2010). Conventional poplar growing in Serbia is charac-

terized by the high costs of plantation establishment, as

it is common to use the technology of full ground and

soil preparation, with a lot of working operations (Keèa

and Pajiã 2015). Alluvial plains along the rivers Danube,

Sava, Tisa, Ibar and Morava Rivers are suitable for the

growth of several broadleaved tree species (Quercus

robur L., Fraxinus angustifolia Vahl., Populus spp.)

(Keèa et al. 2015). Serbias forest reserves, which cover

approximately 27% of the countrys land area, or about

two million hectares, are estimated to be containing 235

million m3 of the standing inventory (Keèa and Keèa

2015). About 36.000 ha of poplar plantations are located

in Vojvodina (Bankoviã 2009).

The controversy of optimal forest management has

a long history in forestry economics (Chladna 2007).

Determination of the Optimal Financial Rota-

tion Period in Poplar Plantations

LJILJANA KEÈA

Faculty of Forestry, University of Belgrade, Chair of Forestry Economics and Organisation, 1, Kneza Viðeslava

street, 11030 Belgrade, Serbia, Tel. +381641794648 and +381113053959, E-mail: ljiljana.keca@sfb.bg.ac.rs

Keèa, L. 2017. Determination of the Optimal Financial Rotation Period in Poplar Plantations. Baltic Forestry 23(1):

673682.

Abstract

Due to trends in the consumption of wood and particularly soft broadleaves, poplar cultivation has gained importance in

Serbia and worldwide in the field of production, economics and environmental protection issues. The present study was

performed to determine the optimal financial rotation lengths for hybrid poplar plantations (Populus Euramericana Gunier

cv. I-214) in a selected area of Serbia. The aim of this study is to apply the method of assessment and calculation of the optimal

production cycle length in order to determine the optimal production cycle length of poplar plantations in the localities of

Serbia from a financial standpoint. The selected discount rate for the calculation is 6% (close to the maximum recorded

internal rate of yield in the observed compartments). It was concluded that the production cycle length of poplar in the study

area ranges from 12-19 years, depending on the soil type. The longest rotation is obtained for humofluvisol (alluvial

semigley). The estimation based on the NPVs criterion determined a desired optimal production cycle length of about 16 years

Keywords: financial rotation, poplar, plantation, optimum

Many studies applying different methodologies have

been conducted in this area, and most of them are related

to stochastic optimal rotation models (Willassen 1998,

Alvarez and Koskela 2004). Nowadays, a lot of forest

economists believe that the net present value approach

is a true innovation in forest management and economics

science. The fact that a total of 313 papers with this topic

have been published since Faustmann speaks in favour

of its importance. However, over two-thirds of these pa-

pers (211) have come since 1985 (Newman 2002).

In short rotation plantation forestry, high biomass

productivity and economic profitability are given prior-

ity and harvest time usually coincides with the age when

mean annual increment is the highest (Tullus et al. 2012).

Therefore, the economic success of poplar plantations

usually depends on obtaining the largest possible

amount of top grade veneer logs, whose value can com-

pensate the high establishment and management costs

(Spinelli and Magagnotti 2011).

The aim of this research is to apply the method of

assessment and the method of calculating the optimal

production cycle length in order to determine the optimal

production cycle length (Keèa 2014) of poplar planta-

tions in the studied localities from an economic stand-

point.

The purpose of this research is to provide guide-

lines for forestry practices aimed at the improvement of

the situation in the field of assessment of the optimal

production cycle length in poplar plantations.

L. KEÈA

BALTIC FORESTRY

DETERMINATION OF THE OPTIMAL FINANCIAL ROTATION PERIOD IN POPLAR PLANTATIONS

The research objects are: the number of trees, vol-

ume of trees and other elements that will be quantified

and numerically analyzed.

Material and methods

The method of assessment was used in the article to

prove the hypothesis that poplar achieved the best finan-

cial effects of production at the ages between 10 and 20

years. This problem comes down to the choice of the ap-

propriate criterion in financial analysis and the monitoring

of its trend for different lengths of the production cycle,

as well as finding the age when the value of the selected

criteria culminates. This is achieved by using regression

and correlation analysis. If statistical significance of the

regression model of the selected indicators trend is pro-

vided, we find the maximum of curves and determine the

time when the financial success is the highest.

The total net present value (NPV) and the average

net present value (NPVs) of wood production in the

analyzed poplar plantations were selected as the criteria

for the assessment of the financial effects, calculated

according to the method of the present value and the

resultant value and then expressed per unit area. The

basic principle on which the method of the present value

is based is that stand value is equated with the value of

timber of the selected trees (in this case poplar), in the

exact proportion that represented the assortment volume

of categories that at the time of assessment are present

in the market, reduced by the costs of forest utilization:

Vs = (V1·P1+ V2·P2++Vn·Pn) - Cs

where: Vs-value of the stand, V1,2,n - volume of the timber

assortment categories, P1,2,n prices of timber assort-

ment categories, Cs costs of forest utilization.

The investigated sample plots were established from

Populus × euramericana cl. I-214, with a 6 × 3 m (555 trees

per ha) planting spacing for technical wood production,

and they were located in the Northern province of

Vojvodina. Nineteen (19) compartments (52 stands) aged

24-42 years with a total area of 362.35 ha were investi-

gated. Soil types in these plots are: a / b-b gley; alluvial

semigley; fossil hydromorphic black soil on loess-alluvium

and fossil hydromorphic black soil (humosemigley) on

loess-alluvium. The research was carried out in poplar plan-

tations located in the area of the Sava River during the

2002 2014 period. Data pertaining to costs during years

0-5 (soil preparation, planting, care and protection, etc.)

were obtained from the archives of the forest enterprise

which managed the studied plantations, and also the data

from material books (Keèa 2010a). The costs of ground

preparation for afforestation are 2040.50 /ha in the start-

ing year. In the first year, the costs of maintenance and

protection of plants are 209.44 /ha. In the second year,

afforestation with rooted cuttings and maintenance and

protection of the plantation costs are 207.48 /ha. In the

third, fourth and fifth years, the costs of tending (inter-

row treatment and weed control) amount to 305.45 /ha.

The costs in the sixth year are 825.91 /ha, because of the

costs of schematic thinning and cutting, processing and

extraction of timber, and in the final year, the costs amount

to 3397.0 /ha. On the other hand, the revenues range be-

tween 11 088.3 23 676.36 /ha. Since all the studied stands

are state-owned and managed by the Public Forest Enter-

prise Vojvodinaðume, the value (cost) of the land (land

rent) did not enter into the calculations (Keèa et al. 2011).

Estimates were made separately for each soil type,

bearing in mind the possibility that different surfaces can

behave differently and the effects of financial trends ob-

served. The criteria for the assessment of the financial

effects were the selected total net present value (NPV)

and the average net present value (NVPs) of production of

poplar wood in the analyzed plantations, calculated ac-

cording to the method of the present value of felling ripe-

ness, and the resultant value then expressed per unit area.

The chosen discount rate to be used in the calcula-

tion was 6%. This discount rate is very close to the maxi-

mum recorded internal rate of return in the observed

stands, which amounts to 5.56% (Keèa 2010, Tullus et al.

2012). The return on investment from the stands at a cer-

tain age should be equal to the available alternative rate

of return on the capital invested (rather than percentage

changes in costs). Stands or trunks are only in this case

the financial mature (Duerr et al. 1956, Keèa and Keèa

2014). In forestry, the valuation of forests is performed

with the interest rate of capitalization (it is the basis for

the capitalization of rents, discounting and prolonging

of financing rents). Therefore, the basis for determining

interest rates in forestry is the rate of value growth. The

higher increment of a stand, the higher the interest rate

(Figuriã 1996).

The assessment was made separately for each soil

type in three variants. The first variant (M0) is based on

real data on costs and revenues created in the compart-

ments on the same ground, totally focused on them when

calculating total and average net present value of pro-

duction. Bearing in mind that in all cases it has reliable

information at the beginning of the production cycle (es-

tablishment and care of plantations costs) and its end

(harvest and production assortments revenues and

associated costs).

The following two variants are created as an attempt

to compile an expert assessment of data about possible

values from the central segment of production cycle

length. In that way, the obtained data were incorporated

into the calculation. The assessment starts from the two

typical cases which form two clearly visible contradic-

tions. The second variant (M1) is based on an estimation

that in the period of culmination of the financial effects

ISSN 2029-9230

674

2017, Vol. 23, No. 3 (46)

L. KEÈA

BALTIC FORESTRY

DETERMINATION OF THE OPTIMAL FINANCIAL ROTATION PERIOD IN POPLAR PLANTATIONS

there is no complex assortment structure, but at this age

stacked wood usually dominates in the assortment struc-

ture of the produced volume of poplar wood. It was taken

as an assumption that the entire realized production is of

simple assortment structure and belongs to the category

of cordwood.

The third variant (M2) is based on the assumption

that the assortment structure may still affect movement

of the culminating point of the observed criterion. How-

ever, at this moment there are no data related to complete

final felling at these ages in sample plots, remaining as

an opportunity to assess the income and expenses at

these ages. The estimation of revenues from timber, in

this case, is the most complex part of the assessment,

and is made through the assortment structure obtained,

based on the method of model tailoring of the trunks

(Nikoliã 1988). This method assumes that assortment

structure depends only on the dimensions of trunks and

does not take into account possible errors of the spin-

dles of tree trunks that affect the result of cutting in prac-

tice. Such a developed assortment structure can be con-

sidered ideal, and (theoretically) as a result brings the

highest revenues from the sales of wood.

In this way, there is the opportunity to compare the

results of three assessments (real lack of data from

the central segment of the length of the production cy-

cle, minimalistic the actual data associated data, where

income is assessed only on the basis of the least valu-

able assortments and maximalistic the actual data

associated the data were obtained on the basis of a

calculation of income based on the ideal assortment struc-

ture). Such access is provided to summarize the possible

similarities or differences in results and provide a more

precise definition of the age range at which the greatest

financial effects can be expected.

To conduct the calculation of missing data on in-

come in the variant M2, for stands at ages that are miss-

ing, in the field we required compartments to meet the

requirement that they include trees of such ages (rang-

ing between 9-23 years). Such departments are found in

each category of soil, but their number is not the same in

each of them. In the next step, data on the dimensions

(diameter and height) of all trees from each of the se-

lected compartments were collected and processed. The

dimensions of trees in the selected classes were obtained

from the Special plan of forest management of this area.

During data processing, it was noticed that trees in the

researched artificial poplar plantations at the same age

(same compartment) have approximately the same dimen-

sions (height variation coefficient is Ch = 5.23%, and the

thickness of Cd = 4.31%) (Table 1). That means it can be

operated with a single tree of average size (mean tree

as a representative of all trees in the department in which

the trees are of the same age (Bankoviã and Pantiã 2006).

Model tailoring based on the principle of maxi-

mum utilization (Nikoliã 1988) was applied for the selected

trees (Table 2), and a total of 33 trees of different ages

(from 12-28 years) were chosen.

Ta b l e 1 . Coefficients of variations of

dimensions of trees in plantations of

poplar with a 6×6 m planting space;

T age of plantation, N number of

stands, Cd coefficient of variations

in diameter, Ch coefficient of vari-

ations in height

T N Cd Ch

age % %

15

1 7,5 4,8

2 6,8 5,1

3 6,9 5,2

Average 7,1 5,0

20

1 7,1 4,6

2 7,5 5,3

3 5,2 4,2

Average 6. 6 4,7

25

1 5,8 4,1

2 7,0 4,4

3 6,4 4,7

Average 6, 4 4,4

Tab le 2. Age and number of stands whose derived trees

were used for the purposes of model tailoring

So il T ype Age of the stands Numb er of

stands year

* á / â-â gley 12, 14, 16, 18, 19, 23, 26, 28 8

*RC 13, 14, 1 5, 16, 1 7, 19, 23, 25, 26, 2 7 10

14, 15, 16, 18, 19, 22, 23 7

ASG 9, 1 2, 14 , 15, 16, 18, 23, 24 8

Ó / 33

As a result of the model tailoring, mean trees by

volume assortments were obtained in each selected de-

partment. These mean trees are the next step multi-

plied by the appropriate prices and the number of trees in

each of these departments, in order to obtain the value of

revenues by departments. These are dependent on the

assortment structure, soil type and the age of stands. In

the following calculation, the resulting value of income

is divided by the surface area of each department to ob-

tain the amount of revenue per hectare. So, as input data

for the assessment of income, we used data on the

number and size of trees in the selected departments on

the ground (to obtain the average dimensions of trees

and assess assortment structure), market prices assort-

ments for 2014 (the valid price list PE Vojvodinaðume)

and the area of the observed compartments. The whole-

sale prices of PE Vojvodinaðume (VAT is excluded) for

tree assortments are as follows: for class F, the price is

66.06 /m3, class L 51.75 /m3, class I 38.53 /m3 and class

II 30.28 /m3.

The present value of the income and expenses (with

a discount rate of 6%), total and average net present

value were calculated on the basis of the database, and

finally the time of their culmination was estimated. The

assessment of culmination was done in a way that data

were flat out (even) by a regression curve (cubic parable,

i.e. polynomial of third-degree). After that, we found the

maximum of the given function as the time of culmination

*RC-fossil hydromorphic black soil (humosemigley) on loess-al-

luvium, AS ASGalluvial semigley, LC-fossil hydromorphic black

soil on loess-alluvium, a / b-b gley

a / b-b

S

ISSN 2029-9230

675

2017, Vol. 23, No. 3 (46)

L. KEÈA

BALTIC FORESTRY

DETERMINATION OF THE OPTIMAL FINANCIAL ROTATION PERIOD IN POPLAR PLANTATIONS

of the total and average net present income for the 4

researched types of poplar forests.

Finally, the criteria for the greatest financial impacts

were chosen. In order to compare the financial effects of

the total and average net present values, it is necessary

to reduce them to the same level. Therefore, procedures

are multiplying the average net present value with the

age at which the total net present value (tNPVmax) culmi-

nates. After that, we compared the result obtained in that

way between the results (NPVt) and the total net present

value (NPV), and the selected value that has a higher

validity (Rankoviã 1996). The formula for such a calcula-

tion would have the following form:

a choice when compared would be as follows:

if the requirement that the NPVt ³ NPV is met, then

further analysis related to the average net present value

(NPVs would be a criterion for observation and analysis);

if the opposite condition (NPVt £ NPV) is fulfilled,

then total net present value (NPV) is the criterion in rela-

tion to which further observation and analysis are to be

performed.

Results

According to the available data from the field on a /

b-b gley soil type, 8 stands aged 12, 14, 16, 18, 19, 23, 26

and 28 years (Table 3) were researched. They were evalu-

ated in terms of the size of NPV and NVPs presented by the

regression curve trend (cubic parabola) (Figures 1, 2).

tNPV

max

s

NPV NPV t

Tabl e 4. Optimal lenght of production cycle and the highest

value of NPV and NPVs

On the basis of these elements, it can be stated that

the estimation based on criteria NPVs represents the re-

quired optimum length of the production cycle and it is

17 years (Table 4).

y = -0,0066x3 - 1 ,4092x2 + 109,0 6x - 2688 ,7

R2 = 0,798 5

y = 0,1464x3 - 11,248x

2 + 252,7 7x - 1690,9

R2 = 0,860 7

-3000

-2500

-2000

-1500

-1000

-5 00

0

500

010203040

Figure 1. NPV and NPVs in estimation variant M1 (in all

figures NPV is in red, and NPVs is in blue)

y

= -0, 1458x3 + 6,415 8x2 + 26, 626x - 2521

R2 = 0,8733

y

= 0,1415x3 - 1 0,989x2 + 250,5 2x - 1687,4

R2 = 0,8637

-30 00

-25 00

-20 00

-15 00

-10 00

-5 00

0

500

1000

010203040

Figure 2. NPV and NPVs in estimation variant M2

Variant of

estim ation

Time of

culmination Maximum value Verification of

criteri a

NPV NPVs NPVmax

NPVsmax NPVsmax· tNPVmax

(tNPVmax=32)

year ·ha 1

M / / / / /

M 32 7 855, 72,82 2.33,2

M2 32 7 23,26 9,8 2.95,8 7

According to the data available from the field on RC

soil type was researched 10 stands aged 13, 14, 15, 16, 17,

19, 23, 25, 26 and 27 years (Table 5) (Figures 3, 4, 5).

On the basis of these elements, it can be said that

the estimation based on the NPVs criterion represents the

required optimum length of the production cycle, which

is 15 years (Table 6).

According to available data from the field, on LC

soil type was researched 7 stands of the following ages:

14, 15, 16, 18, 19, 22 and 23 years (Table 7) (Figures 6, 7).

Tab le 3 . Values of NPV and NPVs in three variants of esti-

mation

Age

year

Variants of estimation

M0 M1 M

2

NPV NP Vs NP V NPVs NPV NPV s

·ha1

1 2.040,48 2.04 0,4 8 2.040,48 2.040,48 2.040,4 8 2 .040, 48

2 2.238,06 1.11 9,0 3 2.238,06 1.119,03 2.238,0 6 1 .119, 03

3 2.422,72 807 ,57 2.422,72 807 ,57 2.42 2,7 2 807,57

4 2.516,46 629 ,12 2.516,46 629 ,12 2.51 6,4 6 629,12

5 2.593,22 518 ,64 2.593,22 518 ,64 2.59 3,2 2 518,64

6 2.665,63 444 ,27 2.665,63 444 ,27 2.66 5,6 3 444,27

7 2.227,16 318 ,17 2.227,16 318 ,17 2.22 7,1 6 318,17

12 / / 1.270,07 105,84 1. 392,1 5 116,01

14 / / 1.131,06 80,79 1 .133,4 2 8 0,9 6

16 / / 1.129,19 70,57 843,70 52,73

18 / / 1.077,86 59,88 273,23 15,18

19 / / 1.005,04 52,90 427,12 22,48

23 / / 1.117,19 48,57 784,25 34,10

26 / / 1.039,30 39,97 597,52 22,98

28 / / 1.144,09 40,86 326,94 11,68

43 1060,86 24,67 1.060,86 24,67 1.060,8 6 2 4,67

ISSN 2029-9230

676

2017, Vol. 23, No. 3 (46)

L. KEÈA

BALTIC FORESTRY

DETERMINATION OF THE OPTIMAL FINANCIAL ROTATION PERIOD IN POPLAR PLANTATIONS

Age

year

Variants of es timat ion

M0 M1 M2

NPV NP Vs NPV NPV s NPV NPVs

·ha1

1 2040, 48 2040, 48 2040, 48 2040, 48 2040, 48 20 40,48

2 2238, 06 1119, 03 22 38,06 1119, 03 2238, 06 11 19,03

3 2422, 72 80 7,57 24 22,72 80 7,5 7 2422, 72 807,57

4 2516, 46 62 9,12 25 16,46 62 9,1 2 2516, 46 629,12

5 2593, 22 51 8,64 25 93,22 51 8,6 4 2593, 22 518,64

6 2665, 63 44 4,27 26 65,63 44 4,2 7 2665, 63 444,27

7 2227, 16 31 8,17 22 27,16 31 8,1 7 2227, 16 318,17

13 / / 1141,62 87,82 13 19,09 10 1,4 7

14 / / 1141,99 81,57 608,6 0 43 ,47

15 / / 1119,72 74,65 10 83,78 72 ,25

16 / / 90 3,1 9 56,45 10 29,56 64 ,35

17 / / 80 5,4 1 52,65 144, 58 8,50

19 / / 89 5,0 3 61,04 43 ,41 2,28

23 / / 1159,81 50,43 396,3 8 17 ,23

25 / / 1237,94 49,52 107,3 5 4, 29

26 / / 1205,75 46,38 443,7 9 17 ,07

27 / / 1158,08 42,89 569,7 0 21 ,10

29 27 5,6 0 9, 50 275,60 9,50 27 5,60 9,50

30 38,2 4 1, 27 38,24 1,27 38 ,24 1,27

32 31 5,8 9 9, 87 315,8 9 9,87 31 5,89 9,87

Tab le 5 . Values of NPV and NPVs in three variants of esti-

mation

y = -0, 4145x3 + 21,504x

2 - 212,72x - 1920,7

R2 = 0,9833

y = 0,3185 x3 - 20,686x2 + 401,73x - 2066,1

R2 = 0,9175

-3000

-2500

-2000

-1500

-1000

-500

0

500

0 5 10 15 20 25 30 35

Figure 3. NPV and NPVs in estimation variant M0

y = 0,058 5x3 - 3,9599x2 + 141,85 x - 2759,7

R2 = 0,7815

y = 0,2875 x

3 - 17,176x2 + 317,5 x - 1836

R2 = 0,9013

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

0 10203040

Figure 4. NPV and NPVsin estimation variant M1

y = -0,3082x3 + 12,069x2 - 12 ,088x - 2462,1

R2 = 0,8711

y = 0,2716x 3 - 1 6,519x2 + 312x - 1826,7

R2 = 0,9021

-3000

-2500

-2000

-1500

-1000

-500

0

500

0 5 10 15 20 25 30 35

Figure 5. NPV and NPVs in estimation variant M2

Tab le 6. Optimal lenght of production cycle

and the highest value of NPV and NPVs

Varian t of

estimation

Time of

culm inat ion Max imum value Verifi cation

of criter ia

NPV NPVs NPVma x NPV

year ·ha1

M0 28 15 116,83 380,44 10.652,32

M1 / 15 / 32,21 /

M2 26 15 34,67 53,18 1.382,55

Ages

year

Variants of estimation

M0 M1 M2

NPV NPVs NPV NPVs NP V NP Vs

·ha1

1 2.040,48 2.040,48 2.040,48 2.040,48 2.040,48 2.040,48

2 2.2 38,06 1.119,03 2.238,06 1.1 19 ,03 2.2 38, 06 1.119,03

3 2.422 ,72 807,57 2.422 ,72 8 07,57 2 .422,72 807,57

4 2.516 ,46 629,12 2 .5 16,46 6 29 ,12 2 .516 ,46 629,12

5 2.593 ,22 518,64 2.593,22 518,6 4 2.5 93,22 518,64

6 2.665 ,63 444,27 2.665,63 444,2 7 2 .665 ,63 444,27

7 2.227 ,16 318,17 2.227,16 318,1 7 2 .227 ,16 318,17

14 / / 1.358 ,64 97,05 1.168 ,11 8 3, 44

15 / / 1.259 ,21 83,95 8 11,7 1 5 4,11

16 / / 1.217 ,31 76,08 823 ,81 5 1, 49

18 / / 1.186 ,83 65,94 6 21,6 5 3 4,54

19 / / 1.114 ,57 58,66 804,19 42,33

22 / / 1.175 ,63 53,44 341,51 15,52

23 / / 1.199 ,77 52,16 339,48 14,76

25 237,3 5 9,49 237,35 9 ,49 2 37 ,35 9,49

Ta b l e 7 . Values of NPV and NPVs in three variants of esti-

mation

y = -0, 4224x3 + 1 8,2 99x2 - 138,56x - 2115

R2 = 0,8734

y = 0,62 95x3 - 30,339x2 + 4 53,32x - 2121,3

R2 = 0,9357

-3 00 0

-2 50 0

-2 00 0

-1 50 0

-1 00 0

-500

0

500

1000

0 10203040

Figure 6. NPV and NPVs in estimation variant M1

ISSN 2029-9230

677

2017, Vol. 23, No. 3 (46)

L. KEÈA

BALTIC FORESTRY

DETERMINATION OF THE OPTIMAL FINANCIAL ROTATION PERIOD IN POPLAR PLANTATIONS

On the basis of these elements, it can be said that

the estimation based on the NPVs criterion represents the

required optimum length of the production cycle, which

is 12 years (Table 8).

According to the data available from the field 8 stand

at the AS ASG soil type of the ages: 9, 12, 14, 15, 16, 18, 23

and 24 years (Table 9), which were evaluated in NPV and

NVPs (Figures 8, 9, 10).

Table 8. Optimal lenght of production cycle and

the highest value of NPV and NPVs

y = -1, 2307x3 + 50,073x2 - 421,3x - 1587,4

R2 = 0,9482

y = 0,5867x3 - 28,713x2 + 439,51x - 2096,3

R2 = 0,9322

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

0 10203040

Figure 7. NPV and NPVs in estimation variant M2

Vari ant of

estimation

Time of

culm ination Maximum value Verific ation

of criteria

NPV NPVs NPVmax NPV

year ·ha1

M

0 / / / / /

M

1 25 12 742,13 3 7 , 5 0 937,50

M

2 22 12 274,8 4 56,97 1.253,34

Age

year

Variants of estimation

M0 M1 M2

NPV NP Vs NPV NPV s NPV NP Vs

·ha1

1 2.040,48 2.040,48 2.040,48 2.040,48 2.040,48 2.040,48

2 2.227,48 1.113,74 2 .23 8,06 1.11 9,03 2 .238, 06 1.119, 03

3 2.392,88 797,63 2.42 2, 72 807,57 2.42 2, 72 8 07,57

4 2.472,35 618,09 2.516,46 629,12 2.516,46 6 29 ,12

5 2.533,93 506,79 2.59 3, 22 518,64 2.593,22 518,64

6 2.588,92 431,49 2.665,63 444,27 2.66 5, 63 4 44 ,27

7 2.273,80 324,83 2.22 7, 16 318,17 2.22 7,16 3 18,17

9 / / 856,69 95,19 1.881,25 209,03

12 / / 859,78 71,65 1.64 6,98 137,25

14 / / 943,98 67,43 1.444, 57 103,18

15 / / 854,08 56,9 4 800 ,30 53,35

16 / / 833,39 52,09 411,19 25,70

18 / / 899,12 49,9 5 447,41 24,86

23 / / 1.011,41 43,97 527,92 22,95

24 / / 1.021,35 42,56 514,06 21,42

25 1.743,02 69,7 2 237,35 9,49 237,35 9,49

27 1.609,37 5 9,6 1 553,64 20,51 553,64 20,51

29 1.725,41 59, 50 335,17 11,56 335,17 11,56

30 1.896,30 6 3,2 1 363,49 12,12 363,49 12,12

38 1.999,57 5 2,6 2 124 ,02 3,26 124,02 3,26

43 2.161,99 50,28 1.097,84 25,53 1.097,84 25,53

Tab le 9 . Values of NPV and NPVs in three variants of esti-

mation

y = -0, 1078x3 + 6,5503x2 - 85,523x - 2130

R2 = 0,816

y = 0,1938x3 - 15,119x2 + 338,15x - 1913,6

R2 = 0,8898

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

-5 5 15253545

y = -0,0875x3 + 2,7829x2 + 79,488x - 2579,7

R2 = 0,7928

y = 0,1242x3 - 9,8204x2 + 233,07x - 1631,7

R2 = 0,8565

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

-5 5 15253545

y = -0,1758x3 + 7,3024x2 + 42,339x - 2621,7

R2 = 0, 8763

y = 0,117x3 - 9 ,399 1x 2 + 227,71x - 1627,8

R2 = 0,8666

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

0 1020304050

Figure 8. NPV and NPVs in estimation variant M0

Figure 9. NPV and NPVs in estimation variant M1

Figure 10. NPV and NPVs in estimation variant M2

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DETERMINATION OF THE OPTIMAL FINANCIAL ROTATION PERIOD IN POPLAR PLANTATIONS

On the basis of these elements, it can be said that

the estimation based on the NPVs criterion represents the

required optimum length of the production cycle ranging

from 16 to 19 years (Table 10).

According to the available data from the field, 19

compartments of different ages (1-7, 25, 27, 29, 30, 32, 38

and 43) were available on all soil types together, and they

were evaluated in the size of NPV and NVPs. If we analyze

the results of NVPs for the researched soil types (Table

11) and evaluation methods, it can be concluded that the

average value for all types of soil is 16 years. This sug-

gests that the estimated optimal length of the production

cycle is not dependent on the method of estimation. The

culminating point of NPVs is regularly the same, and does

not depend on whether the whole harvested volume is

treated as stacked wood (minimalistic variant) or used as

assortment structure obtained by model tailoring

(maximalistic variant). In other words, according to these

findings, and used methods of evaluation of the revenues

from timber, the time of NPVs (optimal length of the pro-

duction cycle) culmination is not sensitive to the assort-

ment structure between the ages of 10 and 20, although it

was found exactly at this segment of age (Figure 11).

Table 10. Optimal lenght of production cycle and

the highest value of NPV and NPVs

Variant of

estimation

Tim e of

culmination Max imum val u e Ve rifi cation

of criteria

NPV NPVs NPVmax NPV

year ·ha1

M0 32 16 1.692,62 420,14 13.444,48

M1 31 18 47,92 106,10 3.289,10

M2 30 19 474,03 108,18 3.245,40

Soil type

Variant of estim ation

M2 M0 M1

NPVs R

2 NPVs R

2 NPVs R

2

* á / â-â gley 17 0,87 / / 17 0,80

*RC 15 0, 90 15 0,92 15 0,90

12 0, 93 / / 12 0,94

ASG 19 0, 87 16 0,89 18 0,86

Average 16 / 16 / 16 /

sis can be used for project design, the selection of ap-

propriate size of the project, optimization of the timing of

activities and determination of the strategy of forest man-

agement. However, in addition to financial parameters,

decision-making on plantation establishment must take

other parameters into account, such as the interests of

local communities, government policy and environmen-

tal protection (Neumayer 2011, Perez 2004). Forests are

among the most valuable natural resources that human-

ity possesses, but it is difficult to make economic quan-

tification of their values. There are benefits of forests,

especially plantations, which cannot be quantified finan-

cially, such as their aesthetic, habitat, protective and anti-

erosion functions.

And finally, if a forest ecosystem has to fulfil all the

requirements it is facing (especially environmental pro-

tection, reduction of CO2 in the atmosphere (Holopainen

2008) and mitigation of the greenhouse effect), it is nec-

essary to establish the sustainability of their manage-

ment. According to some authors, for sustainable man-

agement it is necessary to size the plantations be at least

several hundred hectares (Rose et al. 1981, Medareviã

2006, Allen et al. 2008).

The optimal length of the production cycle in poplar

plantations may be treated as short, compared to the pro-

duction cycle of other economically important species

such as beech, spruce, oak and others. The duration of a

short rotation can be divided into three categories (Pope

Table 12. Optimal lenght of production cycle and the high-

est value of NPV and NPVs

Tab le 11 . The estimated optimal length of

the production cycle to NPVs and coeffi-

cients of the regression of model

a / b-b

On the basis of these elements, it can be stated that

the estimation based on the NPVs criterion represents the

required optimum length of the production cycle, which

is 16 years (Table 12).

Discussion

Financial analysis is an objective means by which

cost-intensive plantations can be compared to cultivat-

ing crops (e.g. agriculture) (Mitchell et al. 1999, Current

et al. 1995, Sharma 1996, Sabadi 1986, 1997). This analy-

y = -0, 2328x3 + 13,154x2 - 111,05x - 2161,4

R2 = 0,9408

y = 0,1745x3 - 14,025x2 + 325,41x - 1890, 8

R2 = 0,908

-3000

-2500

-2000

-1500

-1000

-500

0

500

010203040

Figure 11. NPV and NPVs in estimation variant Mo

Variant of

estimation

Tim e of

culmination

Maximu m

value

Verification

of c rite ria

Variant of

estimation

Tim e of

culmination

NPV NPVs

M0

32 16 132,52 445,26 14.693,58

M1 / / / / /

M2 / / / / /

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2017, Vol. 23, No. 3 (46)

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DETERMINATION OF THE OPTIMAL FINANCIAL ROTATION PERIOD IN POPLAR PLANTATIONS

and Dawson, 2005): (I) 5-10 years - of intense culture for

obtaining biomass; (II) 10-20 years - for receiving pulp-

wood (for paper, wood chips for the production of pan-

els, firewood, pallets, certain chemicals such as ethylene

glycol, and alcohols); (III) 20-40 years for obtaining

technical wood (for construction, peeled veneer, produc-

tion of furniture). The largest poplar plantation areas are

intended for the production of veneer, peeling and cutting

logs, all of which (about 350,000 m3 round wood year-1) is

processed in Serbia and used in the production of pack-

aging, veneer, pallets, various types of board, furniture,

and other articles (Keèa et al. 2012). Short rotations (5-10

years) and the long ones (15 years) are different, both in

terms of cost-efficiency, and energy efficiency. Short ro-

tation plantations generate income earlier and more of-

ten. Due to shorter rotations, the risk of loss has not yet

been so great, and the occurrence of damages was not so

often. They allow the use of all technological advances

and frequent introduction of newly selected hybrids in

plantations (Rose et al. 1981). There are several factors

that significantly affect the length of production cycle,

but the most important are: the choice of the planting

site, planting density, the costs of establishing planta-

tions and the wood market conditions (Birler 1984).

The values obtained for the optimal length of the

production cycle ranged in the interval from 16 to 19 years.

The longest rotations in poplar plantations were obtained

for alluvial semigley. This is the most suitable soil of all

studied soils for the cultivation of poplar (Keèa and Keèa

2012), in addition to fluvisol and therefore the return that

is achieved can bear financial burden with an interest

rate of 6% (Keèa et al. 2011). A shorter length of rotation

was obtained on the black soil type. Similar results were

obtained by Kohn J.P. (1994), except that in hybrid pop-

lars with a 6 × 6 m planting space and different soil types

this interval ranges from 11 to 17 years (Chapman and

Meyer, 1947, Tahvonen and Seppo 1999). Researches

conducted in Turkey estimated the length of financial

rotation to 11 years (Engindeniz 2003). In the United

States, there is legislation (Forest Practice Act of 2008)

which exactly prescribes the production cycle length in

12-20 years old poplar plantations, depending on their

purpose. In Canada, van Kooten (1999) stated that the

optimal production cycle length for poplar ranged from 9

to 12 years.

It should be emphasized that the length of the eco-

nomic and financial rotation, generally do not overlap

(Anderson and Luckert 2006). The reason for this situa-

tion can be explained by the fact that the financial rota-

tion usually varies depending on the price of poplar wood

and interest rates (rate of interest), while the economic

changes if there is a change in the productivity of land

and habitat productivity (Kohn 1997).

Conclusions

The length of the production cycle for poplar in the

project area ranges from 10-20 years. The values obtained

for the length of financial rotation are in the range be-

tween 12 and19 years. The longest rotations were ob-

tained for alluvial semigley and they ranged between 16

and 19 years, depending on the applied methods. The

estimation based on the NPVs criterion represents the

required optimum length of the production cycle, which

is about 16 years for poplar plantations in Serbia. How-

ever, it has been noted that the better soil for growing

poplar (e.g. alluvial semigley) suffers a longer produc-

tion cycle (19 years) in the case of NPVs. According to

the optimal length of the production cycle for Euro-

American poplars, it is recommended to use the culmina-

tion of the average net present value. The statistical

analysis shows that the obtained results for the two re-

gression curves are characterized by high values of the

coefficient of determination and the parameters are the

most significant at the 0.05 level of significance, while

the parameters in NPVs in all variants are statistically sig-

nificant, so that the observations and reasoning based

on these regression models can be accepted as reliable.

The level of statistical significance is high (R2³0,91),

and the correlation coefficient is precisely calculated

(F=42.75).

In the future, private forest owners can be advised

to invest in such a production of poplar wood. On the

other hand, there is a state interest in poplar plantations.

Plantations are very efficient in CO2 consumption, as

shelterbelts, as well as in flood control, etc. Therefore, in

the future the state can stimulate forest owners to invest

in poplar production on river banks and on more quality

soil types, which tends to be more profitable.

Acknowledgement

Gratitude for the implementation of this research

authors suggest the Ministry of Education and Science

of the Republic of Serbia, which financially supported

this research within the project Sustainable manage-

ment of total resources of forests in the Republic of Ser-

bia EVNo. 37008, and Forest plantations in order

to increase afforestation in Serbia EVNo. 31041 COST

Action FP1403 NON-NATIVE TREE SPECIES FOR EU-

ROPEAN FORESTS: EXPERIENCES, RISKS AND OP-

PORTUNITIES (NNEXT)".

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2017, Vol. 23, No. 3 (46)

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DETERMINATION OF THE OPTIMAL FINANCIAL ROTATION PERIOD IN POPLAR PLANTATIONS