Content uploaded by Şükrü Teoman Güner
Author content
All content in this area was uploaded by Şükrü Teoman Güner on Apr 20, 2021
Content may be subject to copyright.
© by PSP Volume 30– No. 06A/2021 pages 6920-6927 Fresenius Environmental Bulletin
6920
RELATIONSHIPS BETWEEN SITE INDEX AND
ECOLOGICAL VARIABLES OF ORIENTAL BEECH FOREST
IN THE MARMARA REGION OF TURKEY
Sukru Teoman Guner*
Bartin University, Ulus Vocational School, Department of Forestry, 74600 Ulus, Bartin, Turkey
ABSTRACT
Determination of the habitat efficiency of forest
ecosystems is crucial for sustainable management of
forest resources. This study was conducted to evalu-
ate the relationships between habitat characteristics
and height growth of oriental beech (Fagus orien-
talis Lipsky) forests. Samples were collected from
35 plots with varying inclination, aspect, elevation,
slope position and site index. A soil pit was dug in
each sampling plot, and soil samples were collected
at different soil depths. An individual tree with the
highest stand height was cut and its height and age
were determined. Physical and chemical properties
of the soil samples collected from the site were ana-
lysed. Relationships between site index (SI100) and
physiographic factors, climatic attributes and soil
properties were assessed with correlation and step-
wise multiple regression analyses. Site index had a
significant relationship with aspect, a physiographic
factor, and pH, a soil property. The height growth of
beech forests was found to be 35.1% according to
stepwise multiple regression analysis. The multiple
regression models obtained may be used to deter-
mine the potential distributional range of oriental
beech in the region and similar habitats.
KEYWORDS:
Fagus orientalis, site properties, site index, modelling
INTRODUCTION
Oriental beech (Fagus orientalis Lipsky),
which is native to Turkey, is distributed across Bul-
garia, Romania, Greece, Crimea, the Caucasus and
northern Iran. Its widest distribution in Turkey is in
the pure and mixed forests at moderate and high ele-
vations, especially the northern aspects of the moun-
tains that extend parallel to the coast of the Black Sea.
It is also sporadically observed in the Marmara, Cen-
tral Anatolia and the Eastern Mediterranean Regions.
Oriental beech prefers a temperate climate with high
humidity and balanced precipitation [1, 2].
Turkey’s forested area is 22.3 million ha,
within which oriental beech forests account for 8.5%
distributed over 1.9 million ha [3]. Oriental beech is
the top species among other broad-leaved tree spe-
cies in Turkey for wood production and afforestation
potential [4].
It is important to determine the relationships
between forest development and site index to find
the impacts of climate change on forest ecosystems
and the properties of potential distributional ranges
of species. In this regard, several studies have con-
sidered different tree species [5–8], using different
statistical methods [7, 9–11], at local and regional
levels [12–17] and at countrywide or wider geo-
graphical scales [8, 18–20]. In the case of oriental
beech, studies have been conducted in the eastern
[21, 22] and central [23] Black Sea Region of Turkey.
However, this study is different from the others as it
was conducted in the Marmara Region.
This study (i) determined the relationships be-
tween site index and ecological variables (land form,
climate and soil properties) of oriental beech forests
and (ii) developed models to predict the ecological
variables and site index. The findings of this study
may be used to identify the site index of areas to be
afforested with oriental beech.
MATERIALS AND METHODS
Study area. The study was conducted in orien-
tal beech forests in the Marmara Region of Turkey
(Figure 1).
The study area was situated on a granite, gran-
odiorite and quartz diorite bedrock [24]. The most
dominant soil type in the study area is Luvisols [25].
The main soil texture types in the study area where
the beech forests are distributed include sand, loamy
sand, sandy loam, sandy clay loam, sandy clay, clay
loam, and loam in non-calcareous and saltless soils.
The mean annual temperature in the sampling
plots is 6.8–10.2 °C, average high temperature is
26.5–29.9 °C, average low temperature (-9.2)–(-
5.8) °C, the mean temperature of the coldest month
is (-3.4)–0 °C, and the mean temperature of the hot-
test month is 16.7–20.1 °C. The mean annual precip-
itation is 903–1276 mm, while the precipitation in
the driest month is 24–34 mm, in spring (March to
May) 241–340 mm, and in summer (June to August)
© by PSP Volume 30– No. 06A/2021 pages 6920-6927 Fresenius Environmental Bulletin
6921
161–227 mm [26]. According to the Erinç method,
the climate of the study plots ranges from sub-humid
to humid [27].
The dominant tree species in the study area is
Fagus orientalis. On a bedrock of schist in the study
area, the plant association Trachystemo orientalis–
Fagetum orientalis is distributed at an altitude of
600–1100 m. The characteristic species in this asso-
ciation are Trachystemon orientalis, Cardamine
bulbifera and Campanula olympica. The floristic
composition of this association consists of 54.5% of
plant taxa belonging to the Euro-Siberian flora zone
while 1.8% belongs to the Mediterranean flora zone.
Pluriregional or unknown taxa account for 43.7%
[28, 29].
Sampling procedure. Samples were collected
from 35 plots 20 × 20 m in dimension, with different
elevation, aspect, inclination, slope position and
stand development.
For each plot, elevation, inclination, slope po-
sition and aspect were recorded. Equation (1) was
used to convert the aspect values to the radiation in-
dex (RI) [30, 31]:
RI = [1‒cos((π/180)(Q‒30))]/2 (1)
where, Q was the azimuth angle of the sample
plot to the north.
Soil samples were taken using volume cylin-
ders at depth intervals of 0‒10, 10‒30, 30‒60 and
60‒100 cm from soil pits in each plot (35 sample
plots × 4 soil depths = 140 soil samples). The top
height was determined based on the average of the
total height of three dominant trees in each plot, and
one of the trees was felled to obtain age and height
measurement.
Laboratory analysis. The soil samples col-
lected were air-dried and weighed to the nearest 0.01
g to determine soil bulk density. The soil samples
ground with a pestle and mortar and passed through
a 2-mm screen for analysis. The moisture content of
the soil was calculated by oven-drying soil samples
at 105 °C until a constant weight. Soil bulk density
was determined with the core method [32]. The par-
ticle size distribution of the soil samples was deter-
mined by the hydrometer method [33]. To determine
the organic carbon, the Walkley-Black wet oxidation
method [34] was used; while pH was determined by
an electrometric method in a solution of v/5v
soil/water [35], and electrical conductivity deter-
mined by an electrometric method in a solution of
m/5v soil/water [36]. The calcimeter method was
applied to find the total CaCO3 content of the soil
samples [37].
Data analysis. Based on the age and height of
the trees felled in the plots, the site index (SI100) of
the plots at age 100 was calculated using the model
proposed by Carus [38] for oriental beech forests.
The site index obtained was used as the dependent
variable in regression analysis.
FIGURE 1
Location of the study area
© by PSP Volume 30– No. 06A/2021 pages 6920-6927 Fresenius Environmental Bulletin
6922
To determine the climate properties of the plots,
data were retrieved from the meteorological station
(Fig. 1) closest to the study area. For interpolation of
this meteorological data, the temperature was re-
duced by 0.5 °C for every 100 m and annual rainfall
increased by 54 mm for every 100 m in altitude. The
data were then proportionally distributed by month
[27].
Correlation analysis was used for assessment of
the relationships between SI100 and ecological fac-
tors. Stepwise multiple regression analysis was per-
formed to develop models which may yield the most
appropriate set of variables that had a significant re-
lationship with SI100. For model evaluation, ten-fold
cross validation was applied [31, 39, 40].
RESULTS AND DISCUSSION
The top height of the stands aged 100 years in
the sampling plots varied from 18.0 m to 39.7 m (Ta-
ble 1). According to the yield table developed by Ca-
rus [38] for oriental beech forests, 23 sample plots
(66%) were in site class I (SI100 > 29.26 m), 6 plots
(17%) in site class II (SI100 = 26.78–29.26 m), 2 plots
in site class III (SI100 = 24.30–26.78 m), 2 plots in
site class IV (SI100 = 21.82–24.30 m), and 2 plots
(6%) in site class V (SI100 < 21.82 m).
The sampling plots were located at an elevation
of 980–1670 m. Of those, 42.9% (15) were below
1200 m and 17.1% (6) were situated at an elevation
of 1200–1400 m, while 40% (14) were above 1400
m. In addition, 25.7% of the sampling plots were sit-
uated on flat, low- and moderate-incline terrain (1–
17%) and 68.6% were on high-incline terrain (18–
36%), while 5.7% were on steep slopes (˃ 37%). The
distribution of the sampling plots across the upper
slope (1–25%), upper middle slope (25–50%), lower
middle slope (50–75%) and lower slope (75–100%)
was 26%, 20%, 26% and 29%, respectively. Of the
sampling plots, 65.7% had a northern aspect (NE, N,
E, NW) and 34.3% had a southern aspect (SE, W, S,
SE), while 74% of the 23 sampling plots in site class
I had a northern aspect and 26% had a southern as-
pect. This suggests that productive sites have a shad-
ier aspect.
TABLE 1
Variables used in statistical analyses and their codes.
Variables Code Unit Min. Max. Mean Std. dev.
Stand properties
Site index
SI
100
m
18.0
39.7
30.4
4.4
Physiographic factors
Elevation
Elv
m
980
1670
1325
221
Inclination
Inc
%
5
38
22.8
10.3
Slope position
SP
%
6.3
93.9
52.8
27.9
Radiation index (dimensionless)
RI
0.017
0.933
0.413
0.245
Soil properties
Fine earth (Ø < 2 mm)
Fne
g/l
387
1519
978
214
Sand
Sand
%
36.6
87.1
54.8
8.2
Silt
Silt
%
8.1
41.7
21.6
4.7
Clay
Clay
%
4.8
37.5
23.5
5.3
Organic carbon
Corg
%
0.09
14.77
1.86
2.01
Total lime (CaCO
3
)
Tlm
%
0.01
0.23
0.06
0.04
Soil reaction (dimensionless)
pH
4.16
6.11
5.21
0.31
Electrical conductivity
EC
mS/cm
0.02
0.70
0.04
0.05
Climatic attributes
Mean annual temperature
Mat
°C
6.8
10.2
8.5
1.1
Mean maximum temperature
Mmat
°C
26.5
29.9
28.2
1.1
Mean minimum temperature
Mmit
°C
-9.2
-5.8
-7.5
1.1
Mean temperature of the coldest month
Mtcm
°C
-3.4
0
-1.7
1.1
Mean temperature of the warmest month
Mtwm
°C
16.7
20.1
18.4
1.1
Annual precipitation
Ap
mm
903
1276
1090
119
Rainfall in spring (March+April+May)
Rsp
mm
241
340
291
32
Rainfall in summer (June+July+August)
Rsm
mm
161
227
194
21
Rainfall of the driest month
Rdm
mm
24
34
29
3
© by PSP Volume 30– No. 06A/2021 pages 6920-6927 Fresenius Environmental Bulletin
6923
FIGURE 2
Relationships between site index (SI100), physiographic factors, and climatic attributes
(** Correlation significant at 0.01 level; Elv: elevation, Inc: inclination, Sp: slope position, RI: radiation index, Mat: mean
annual temperature, Mmat: mean maximum temperature, Mmit: mean minimum temperature, Mtcm: mean temperature of the
coldest month, Mtwm: mean temperature of the warmest month, Ap: annual precipitation, Rsp: rainfall in spring, Rsm: rainfall
in summer, Rdm: rainfall of driest month).
In this study, a negative correlation was found
between site index (SI100) and aspect (p < 0.01, r = -
0.430; Figure 2). Beech developed better in sites
with a shady aspect rather than with a sunny aspect.
Similarly, in a study conducted in the Trabzon-Rize
part of the eastern Black Sea Region, negative rela-
tionships were found between the height growth of
beech stands and aspect (p < 0.01, r = -0.619) [21].
As aspect is an important factor that affects the tem-
perature and humidity of a place, it is expected to
have an effect on site index. However, no significant
relationships have been found between aspect and
height growth in studies conducted so far [20, 22, 41,
42]. This may be explained by the challenge of in-
corporating aspect into statistical calculations as a
numerical parameter.
In our study, no significant relationship was
found between site index, elevation, inclination and
slope position (p > 0.05; Figure 2). However, in a
study conducted in the eastern Black Sea Region, a
negative relationship was found between the height
growth of beech stands and elevation [21]. The dif-
ference between our study conducted in the Marmara
and the other in the eastern Black Sea Region may
be due to the difference in rainfall between the two
areas. The importance of elevation is due to its im-
pact on climate. Higher elevations are associated
with increased precipitation, decreased temperature
and decreased evaporation, and thus formation of
less humid habitats. The negative relationship be-
tween the height growth of beech and elevation in
the eastern Black Sea Region may be interpreted as
an effect of decreased temperature due to increased
elevation; although there is no water deficit in the re-
gion, the shorter growth period leads to a decrease in
height growth. Other studies conducted on oriental
beech in the eastern Black Sea Region [14, 17, 43]
also reported similar results.
Slope inclination affects not only local climate
but also water and nutrient availability in the soil;
therefore, it is natural that there are good site classes
at lower inclinations. However, in this study, no sig-
nificant relationship was found between site index
and inclination (p > 0.05). Likewise, other studies on
oriental beech [21] and black pine [44, 45] have re-
ported similar results. This suggests that the effect of
the inclination factor may be suppressed because of
the medium- and coarse-textured soils and high pre-
cipitation in the study areas.
Trees have more opportunity to take up water
and nutrients from soil from the upper edge of the
slope to the lower slopes. Almost all studies on this
topic have reported a positive relationship between
the distance from the upper edge of the slope (slope
position) and site index [21, 44–47]. However, we
did not find a significant association between slope
position and site index (p > 0.05). This may be ex-
plained by the fact that the effect of slope position is
not pronounced due to the high site index of our
study plots similar to the inclination factor.
No significant relationship was found between
climate properties and site index in our study
(p > 0.05; Figure 2). This may be explained by the
fact that temperature and rainfall in the study plots
were optimal for beech forest development and these
factors did not have a limiting effect.
© by PSP Volume 30– No. 06A/2021 pages 6920-6927 Fresenius Environmental Bulletin
6924
FIGURE 3
Relationship between site index and soil properties
(* Correlation is significant at the 0.05 level, ** Correlation is significant at the 0.01 level; Fne: fine earth (Ø < 2 mm), Corg:
organic carbon, Tlm: total lime, pH: soil reaction, EC: electrical conductivity).
TABLE 2
Multiple linear regression models developed using a stepwise procedure based on
ecological variables to predict site index.
Mod-
els
Training R2
Testing R2
p (Models)
SEE (m)
Variables in models p (Variables) VIF
1
0.223
0.081
0.004
3.96
Constant
71.324
0.000
-
pH (in 30-60 cm depth)
-7.679
0.004
1.000
2
0.351
0.205
0.001
3.67
Constant
73.594
0.000
-
pH (in 30-60 cm depth)
-9.622
0.000
1.111
Sand (in 60-100 cm
depth)
0.140
0.017
1.111
R2: coefficient of determination, p: significant level, SEE: standard error of the estimate, VIF: variance inflation factor
Negative relationships were found between the
site index of oriental beech (SI100) and pH at the
depths of 0–10, 10–30 and 60–100 cm with p < 0.05,
and at the depth of 30–60 cm with p < 0.01 (Fig. 3).
SI100 did not have a significant relationships with
fine earth (Ø < 2 mm), sand (%), silt (%), clay (%),
organic carbon (%), total lime (%) and EC (mS/cm;
Fig. 3). However, a study on beech forests in the
eastern Black Sea Region reported a positive rela-
tionship between height growth and absolute soil
depth (cm), thickness of the Ah horizon (cm), thick-
ness of the B horizon (cm), fine earth (%), clay (%)
and silt (%), and a negative relationship with stoni-
ness (%), organic matter content in the Ah horizon
(%), sand (%) and Ca (me/100 g) [21]. Except for pH,
no significant relationship was found between SI100
and the soil properties analysed. This may mainly be
because the soils in the study plots were almost de-
void of lime (0.01–0.23%) and salt (0.02–0.70
mS/cm); in addition, the sites were on bedrock of the
same origin and were under the same climatic condi-
tions. In this study, the negative correlation between
SI100 and pH was mainly associated with rainfall. In
areas with high rainfall, soil leaching increases and
pH decreases. Decreased pH leads to the formation
of a more humid habitat, which positively affects
height growth.
The stepwise multiple regression analysis per-
formed for the relationship between SI100 and physi-
ographic factors, climate properties and soil depth
intervals yielded two models. The second model in-
cluded pH at the soil depth of 30–60 cm and clay at
the soil depth of 60–100 cm as variables. These two
variables explained 35.1% of the height growth of
beech (Table 2). The site index of beech increased in
parallel to the decrease in pH and increase in the per-
centage of sand. A study conducted in the eastern
Black Sea Region reported that 35% of the height
growth of beech was explained by fine earth (%),
depth of the Ah horizon (cm) and absolute soil depth
(cm) [21]. In a study conducted in the central Black
Sea Region (Sinop-Ayancık), a site index map was
created using different statistical models. Aspect (de-
gree), age (year) and sand (%) explained 23% and 98%
of the height growth of beech using the lowest MLR
(multiple linear regression) method and the RBFK
(radial basis function kriging) method, respectively
[23].
© by PSP Volume 30– No. 06A/2021 pages 6920-6927 Fresenius Environmental Bulletin
6925
CONCLUSIONS
Oriental beech is an important tree species with
a high economic value. It is expected that it will be
one of the species most affected by drought due to
climate change, and its distributional range is likely
to change. Therefore, it is important to identify the
habitat requirements of this species, conserve strictly
protected areas and its potential range, and select po-
tential afforestation sites in both Turkey and other
countries. This study showed that oriental beech de-
veloped well on soils with lower pH values and a
northern aspect. The multiple regression models ob-
tained may be used to determine the site index of bar-
ren areas for afforestation with oriental beech.
ACKNOWLEDGEMENTS
This research was funded by the Turkish Gen-
eral Directorate of Forestry.
REFERENCES
[1] Atalay, İ. (1992) The ecology of beech (Fagus
orientalis Lipsky) forests and their regioning in
terms of seed transfer. Forest Tree Seeds and
Tree Breeding Research Directorate, Ankara.
209. (In Turkish)
[2] Anşin, R., Özkan, Z.C. (1997) Spermatophyta.
Karadeniz Technical University, Faculty of For-
estry Press No. 167, Trabzon. (In Turkish)
[3] GDF. (2015) Forest Resources in Turkey. Turk-
ish General Directorate of Forestry. Ankara. 32.
(In Turkish)
[4] Ko s k i , V. , Antola, J. (1993) Turkish National
Tree Breeding and Seed Production Program for
Turkey (1994-2003). Cooprepared with ENSO
Forest Development Inc and Forest Tree Seeds
and Tree Breeding Institute, Ankara. 49.
[5] Bravo-Oviedo, A., Montero, G. (2005) Site in-
dex in relation to edaphic variables in stone pine
(Pinus pinea L.) stands in south west Spain. An-
nals of Forest Science. 62, 61–72.
[6] Bravo-Oviedo, A., Roig, S., Bravo, F., Montero,
G., Del-Rio, M. (2011) Environmental variabil-
ity and its relationship to site index in Mediter-
ranean maritime pine. Forest Systems. 20(1),
50-64.
[7] Bueis, T., Bravo, F., Pando, V., Turrion, M.B.
(2016) Relationship between environmental pa-
rameters and Pinus sylvestris L. site index in
forest plantations in northern Spain acidic plat-
eau. iForest. 9, 394-401.
[8] Moreno-Fernández, D., Álvarez-Gonzálezc,
J.G., Rodríguez-Soalleirod, R., Pasalodos-Tatoa,
M., Cañellasa, I., Montesa, F., Díaz-Varelae, E.,
Sánchez-Gonzáleza, M., Crecente-Campof, F.,
Álvarez-Álvarezg, P., Barrio-Antag, M., Pérez-
Cruzadoc, C. (2018) National-scale assessment
of forest site productivity in Spain. Forest Ecol-
ogy and Management. 417, 197-207.
[9] Seynave, I., Gégout, J.C., Hervé, J.C., Dhôte,
J.F., Drapier, J., Bruno, É., Dumé, G. (2005)
Picea abies site index prediction by environ-
mental factors and understorey vegetation: a
two-scale approach based on survey databases.
Canadian Journal of Forest Research. 35, 1669–
1678.
[10] Aertsen, W., Kint, V., Orshoven, J.V., Muys, B.
(2011) Evaluation of modelling techniques for
forest site productivity prediction in contrasting
ecoregions using stochastic multicriteria accept-
ability analysis (SMAA). Environmental Mod-
elling & Software. 26, 929-937.
[11] Gülsoy, S., Çınar, T. (2019) The relationships
between environmental factors and site index of
Anatolian black pine (Pinus nigra Arn. subsp.
pallasiana (Lamb.) Holmboe) stands in Demirci
(Manisa) district, Turkey. Applied Ecology and
Environmental Research. 17(1), 1235-1246.
[12] Br avo, F., Montero, G. (2001) Site index estima-
tion in Scots pine (Pinus sylvestris L.) stands in
the High Ebro Basin (northern Spain) using at-
tributes. Forestry. 74(4), 395-406.
[13] Diéguez-Aranda, U., Álvarez González, J.G.,
Barrio Anta, M., Rojo Alboreca, A. (2005) Site
quality equations for Pinus sylvestris L. planta-
tions in Galicia (northwestern Spain). Annals of
Forest Science. 62, 143–152.
[14] Ercanlı, İ., Günlü, A., Altun, L., Başkent, E.Z.
(2008) Relationship between site index of orien-
tal spruce [Picea orientalis (L.) Link] and eco-
logical variables in Maçka, Turkey. Scandina-
vian Journal of Forest Research. 23, 319-329.
[15] Bravo, F., Lucà, M., Mercurio, R., Sidari, M.,
Muscolo, A. (2011) Soil and forest productivity:
a case study from Stone pine (Pinus pinea L.)
stands in Calabria (southern Italy). iForest. 4,
25-30.
[16] Álvarez-Álvarez, P., Khouri, E.A., Cámara-
Obregón, A., Castedo-Dorado, F., Barrio-Anta,
M. (2011) Effects of foliar nutrients and envi-
ronmental factors on site productivity in Pinus
pinaster Ait. stands in Asturias (NW Spain). An-
nals of Forest Science. 68, 497–509.
[17] Yener, İ., Altun, L. (2018) Predicting site index
for oriental spruce (Picea orientalis L. (Link))
using ecological factors in the eastern black sea,
Turkey. Fresen. Environ. Bull. 27(5), 3107-3116.
© by PSP Volume 30– No. 06A/2021 pages 6920-6927 Fresenius Environmental Bulletin
6926
[18] Chen, H.Y.H., Krestov, P.V., Klinka, K. (2002)
Trembling aspen site index in relation to envi-
ronmental measures of site quality at two spatial
scales. Canadian Journal of Forest Research. 32,
112–119.
[19] Eckhart, T., Pötzelsberger, E., Koeck, R., Thom,
D., Lair, G.J., Loo, M.V., Hasenauer, H. (2019)
Forest stand productivity derived from site con-
ditions: an assessment of old Douglas-fir stands
(Pseudotsuga menziesii (Mirb.) Franco var.
menziesii) in Central Europe. Annals of Forest
Science. 76, 19.
[20] Özel, C., Güner, Ş.T., Türkkan, M., Akgül, S.,
Şentürk, Ö. (2021) Modelling the site index of
Pinus pinaster plantations in Turkey using eco-
logical variables. Journal of Forestry Research.
32(2), 589-598.
[21] Yılmaz, M. (2005) Studies on Some Site Factors
Affecting the Growth (productivity) of the
Beech in Pure Oriental Beech (Fagus orientalis
Lipsky) Ecosystems in East Karadeniz Region.
PhD Dissertation, Karadeniz Technical Univer-
sity, Trabzon. 188. (In Turkish)
[22] Yılmaz, M. (2019) Effects of soil and environ-
mental factors on the site productivity of pure
Oriental beech forests in Akkuş region of Turkey.
Eurasian Journal of Forest Science. 7(2), 107-
120.
[23] Günlü, A., Bulut, S., Keleş, S., Ercanlı, İ. (2020)
Evaluating different spatial interpolation meth-
ods and modeling techniques for estimating spa-
tial forest site index in pure beech forests: a case
study from Turkey. Environmental Monitoring
and Assessment. 192, 53.
[24] GDMRE. (2021) 1:500,000 Scale Geological
Inventory Map Series of Turkey.
http://www.mta.gov.tr/v3.0/hizmetler/500bas
[accessed 04.01.2021].
[25] IUSS Working Group WRB. (2015) World ref-
erence base for soil resources 2014, update 2015.
International soil classification system for nam-
ing soils and creating legends for soil maps.
World Soil Resources Reports No. 106. FAO,
Rome. 192.
[26] GDM. (2020) Meteorological Data. Turkish
General Directorate of Meteorology. Ankara.
[27] Özyuvacı, N. (1999) Meteorology and Climatol-
ogy. Istanbul University Faculty of Forestry
Press No. 460, Istanbul. 369. (In Turkish).
[28] Akman, Y., Barbero, M., Quezel, P. (1979)
Contribution to the study of the forest vegeta-
tion of Mediterranean Anatolia. Phytocoenolo-
gia. 5(3), 277–346.
[29] Türe, C., Tokur, S., Ketenoğlu, O. (2005) Con-
tribution to the syntaxonomy and ecology of the
forest and shrub vegetation in Bithynia, North-
western Antolia, Turkey. Phyton (Austria). 45,
81–115.
[30] Moisen, G.G., Frescıno, T.S. (2002) Comparing
five modelling techniques for predicting forest
characretistics. Ecological Modelling. 157, 209-
225.
[31] Aertsen, W., Kınt, V., Orshoven, J., Özkan, K.,
Muys, B. (2010) Comparison and ranking of dif-
ferent modelling techniques for prediction of
site index in Mediterranean mountain forests.
Ecological Modelling. 221, 1119-1130.
[32] BS EN ISO 11272. (2014) Soil quality-Determi-
nation of dry bulk density. The British Standards
Institution Press, London.
[33] Kroetsch, D., Wang, C. (2008) Particle Size Dis-
tribution, in section VI. Soil Physical Analysis,
Section Ed. By Angers D.A., Larney, F.J., In:
Carter, M.R., Gregorich, E.G. (Eds.), Soil Sam-
pling and Methods of Analysis 2. Edition, CRC
Press, Boca Raton. 713-725.
[34] TS 8336. (1990) Soils-Determination of organic
matter. Turkish Standards Institution Press, An-
kara. 4. (In Turkish)
[35] TS ISO 10390. (2013) Soil quality-Determina-
tion of pH. Turkish Standards Institution Press,
Ankara. 7. (In Turkish)
[36] TS ISO 11265. (1996) Soil quality - Determina-
tion of electrical conductivity. Turkish Stand-
ards Institution Press, Ankara. 4 (In Turkish)
[37] TS 8335 ISO 10693. (1996) Soil quality-Deter-
mination of carbonate content-Volumetric
method. Turkish Standards Institution Press,
Ankara. 8. (In Turkish)
[38] Carus, S. (1998) Increment and Growth in Even
Aged Beech (Fagus orientalis Lipsky.) Forests.
PhD Dissertation, Istanbul University. 360. İs-
tanbul. (In Turkish)
[39] Stone, M. (1974) Cross-validatory choice and
assessment of statistical predictions. Journal of
the Royal Statistical Society Series B (Method-
ological). 36(2), 111–147.
[40] Drummond, S.T., Sudduth, K.A., Joshi, A.,
Birrell, S.J., Kitchen, N.R. (2003) Statistical and
neural methods for site-specific yield prediction.
Transactions of the ASAE. 46(1), 5–14.
[41] Güner, Ş.T., Yücel, E. (2015) The relationships
between growth of Pinus sylvestris ssp. hamata
forests with ecological factors in Central Anato-
lia. Biological Diversity and Conservation. 8(3),
6-19.
[42] Güner, Ş.T., Çömez, A., Özkan, K., Karataş, R.,
Çelik, N. (2016) Modelling the productivity of
Anatolian black pine plantations in Turkey. For-
estist. 66(1), 159-172. (In Turkish)
[43] Daşdemir, İ. (1992) Relationship between
productivity and site factors for oriental spruce
in Turkey. Forestry Research Institute Press No.
64, Ankara. (In Turkish)
© by PSP Volume 30– No. 06A/2021 pages 6920-6927 Fresenius Environmental Bulletin
6927
[44] Eruz, E. (1984) Relationship between height
growth and some edaphic and physiological at-
tributes for Crimean pine in Balikesir forest En-
terprise. Istanbul University Faculty of Forestry
Press No. 3244/368, İstanbul. 72. (In Turkish)
[45] Özkan, K., Gülsoy, S., Mert, A. (2008) Interre-
lations between height growth and site charac-
teristics of Pinus nigra Arn. ssp. pallasiana
(Lamb.) Holmboe. The Malaysian Forester. 71,
9-16.
[46] Çepel, N., Dündar, M., Günel, A. (1977) Rela-
tionship between edaphic and physiological at-
tributes and growth of Scotch pine in important
forest areas. The Scientific and Technological
Research Council of Turkey Press, Ankara. 165.
(In Turkish)
[47] Gülsoy, S., Suel, H., Çelik, H., Özdemir, S.,
Özkan, K. (2014) Modeling site productivity of
Anatolian black pine stands in response to site
factors in Buldan district, Turkey. Pakistan Jour-
nal of Botany. 46(1), 213-220.
Received: 20.01.2021
Accepted: 05.03.2021
CORRESPONDING AUTHOR
Sukru Teoman Guner
Ulus Vocational School,
Department of Forestry,
Bartın University,
74600 Ulus Bartın – Turkey
e-mail: stguner@gmail.com
