The effects of land use changes on some
Environ Monit Assess (2008) 136:101–119
DOI 10.1007/s10661-007-9668-4
The effects of land use changes on some soil properties
in İndağı Mountain Pass – Çankırı, Turkey
M. Başaran & G. Erpul & A. E. Tercan &
M. R. Çanga
Received: 29 May 2006 / Accepted: 23 February 2007 / Published online: 12 June 2007
# Springer Science + Business Media B.V. 2007
Abstract Understanding spatial variability of dynamic soil attributes provides information for suitably
using land and avoiding environmental degradation.
In this paper, we examined five neighboring land use
types in Indagi Mountain Pass – Cankiri, Turkey to
spatially predict variability of the soil organic carbon
(SOC), bulk density (BD), textural composition, and
soil reaction (pH) as affected by land use changes.
Plantation, recreational land, and cropland were the
lands converted from the woodland and grassland
which were original lands in the study area. Total of
578 disturbed and undisturbed soil samples were
taken with irregular intervals from five sites and
represented the depths of 0–10 and 10–20 cm. Soil
pH and BD had the lower coefficient of variations
(CV) while SOC had the highest value for topsoil.
Clay content showed greater CV than silt and sand
M. Başaran (*)
Seyrani Faculty of Agriculture, Erciyes University,
Develi, Kayseri, Turkey
e-mail: [email protected]
G. Erpul : M. R. Çanga
Faculty of Agriculture, Department of Soil Science,
Ankara University,
Diskapi, Ankara 06110, Turkey
A. E. Tercan
Department of Mining Engineering, Hacettepe University,
Beytepe, Ankara, Turkey
contents. The geostatistics indicated that the soil
properties examined were spatially dependent to the
different degrees and interpolations using kriging
showed the dynamic relationships between soil
properties and land use types. The topsoil spatial
distribution of SOC highly reflected the changes in
the land use types, and kriging anticipated significant
decreases of SOC in the recreational land and
cropland. Accordingly, BD varied depending on the
land use types, and also, the topsoil spatial distribution of BD differed significantly from that of the
subsoil. Generally, BD greatly decreased in places
where the SOC was relatively higher except in the
grassland where overgrazing was the more important
factor than SOC to determine BD. The topsoil spatial
distributions of clay, silt, and sand contents were
rather similar to those of the subsoil. The cropland
and grassland were located on the very fine textured
soils whereas the woodland and plantation were on
the coarse textured soils. Although it was observed a
clear pattern for the spatial distributions of the clay
and sand changing with land uses, this was not the
case for the silt content, which was attributed to the
differences of dynamic erosional processes in the
area. The spatial distribution of the soil pH agreed
with that of the clay content. Soils of the cropland and
grassland with higher amounts of clay characteristically binding more cations and having higher buffering capacities had the greater pH values when
compared to the soils of other land uses with higher
102
amounts of sand naturally inclined to be washed from
the base cations by the rainwater.
Keywords Spatial variability . Land use changes .
Organic carbon . Bulk density . Textural composition .
Soil reaction
Introduction
Spatial variability of soil properties affected soil performance and therefore the crop yield (Warrick and
Gardner 1983). Understanding changes of soil properties in the field scale guided plant nutrient applications (Robert et al. 1993) and optimized irrigation
budget in salinity management (Russo 1984). Therefore, there is a great need to spatially investigate the
variability of dynamic soil attributes to refine the agricultural management practices, from which expected
is less environmental degradation.
Spatial changes in soil properties can result from soil
formation factors. Mineral composition and textural
class of soil considerably determine the manner in which
it can be used. Based on clay content, which affects most
of the agriculturally significant soil properties such as
water holding capacity, permeability to water, aeration,
plasticity and nutrient-supplying ability and cation
exchange capacity (Mapa and Kumaragamage 1996),
some generalizations can be made about soil behavior
(Uehara and Gillman 1981). Similarly, the soil reaction
(pH) is another significant soil property to predict
nutrient availability and determine soil ability to benefit
from fertilizer and amendments. Dhillion et al. (1994)
used pH as an indicator of soil fertility in strategies
based on spatial analysis of plant nutrients. Bauer and
Black (1994) quantified the effects of organic matter
content on soil productivity.
On the other hand, spatial variations in soil properties
can also stem from soil management factors or can be in
relation to land use at different scales. Soils of the
natural ecosystems have been characterized by natural
soil intrinsic factors such as climate, topography, aspect,
bedrock, and vegetation. And, land use changes could
also have characterizing effects on soils due to the
extrinsic factors such as fertilization, cultivation, over
grazing and management. In recent years, there has been
a great need for estimating variations in soil quality
especially by human pressure, aiming at an improvement in the agricultural management practices and
Environ Monit Assess (2008) 136:101–119
decreases in environmental damage. Wali et al. (1999)
and Mahtab and Karim (1992) reported that expanding
cropland at the expense of woodland and grassland was
one of the main reasons of degrading soil properties.
Changes in land use can have a marked effect on
soil organic carbon content by means of humification,
decomposition and mineralization of soil organic
matter. The alteration of forest and pastureland into
arable agriculture is one of the main causes of degrading soil organic matter. Cultivation of pastures
led to 25–50% decrease in soil organic carbon (Elliott
1986; Grupta and Germida 1988). In China, when
Alpine grassland soils were converted into arable land
for 8, 16, and 41 years, it was indicated by Wu and
Tiessen (2002) that the organic matter content of soils
decreased by 25, 39, and 55%, respectively. Celik
(2005) has recently reported that relative to soil organic matter of the forest and pasture soils in a southern Mediterranean highland of Turkey, soil organic
matter of the cultivated soils decreased by 44 and
48% for the 0–10 cm layer and 48 and 50% for the
10–20 cm layer over 12 years, respectively.
Land degradation and loss of soil organic matter is
closely linked to the deterioration of such significant
soil physical properties as pore size distribution, bulk
density, aggregation and aggregate stability (Tisdall and
Oades 1982; Elliott 1986). Hajabbasi et al. (1997)
found that deforestation and successive tillage practices
caused nearly 20% increase in bulk density and a 50%
decrease in soil organic matter for a soil depth of 0–
30 cm over 20 years in the central Zagrous mountain
in Iran. Shukla et al. (2004) documented that the bulk
density was the most discriminating soil attribute or the
dynamic soil quality indicator for ascertaining temporal
changes in soil properties in relation to land use and
management. Cultivated soils had higher bulk density
than adjacent soils under forests and pastures for the 0–
10 and 10–20 cm layers in a southern Mediterranean
highland of Turkey (Celik 2005).
In recent years soil scientists focused on predicting
spatial variability of soil properties using geostatistics
and different kriging methods to better understand the
influence of land use changes on soil properties over
small to large spatial scale (Yost et al. 1982; Trangmar
et al. 1987; Miller et al. 1988; Voltz and Webster
1990; Chien et al. 1997; Tsegaye and Hill 1998; Lark
2002; Bo et al. 2003).
Atalay (1997) gives details of highlands of Turkey.
He reports that ecosystems at elevations of 1,500 m
Environ Monit Assess (2008) 136:101–119
and higher with the slope range of 15–40% still
account about 26 and 34% of the total area of
759,978 km 2 , respectively, although important
changes have occurred in rural ecosystems over the
past five decades in a large part of Turkey. Cropland
of Turkey increased approximately 18 Mha from
1952 to 2000 (Anonymous 2000), and overgrazing,
deforestation, and increase in agricultural activity
have intensified pressures on high-altitude fragile
ecosystems (Evrendilek et al. 2004). The objective
of this study is to geostatistically examine the effect
of land use changes on carbon content, bulk density,
reaction and texture of soils of Indagi Mountain Pass
of Cankiri, Turkey, where woodland is an important
source of vegetation and soil organic carbon, and
woodland of the Mountain Pass has been already
strongly affected by agricultural expansion due to the
population growth and socio-economical conditions
in the region. It is expected by this research that
explaining any variation in soil properties affected by
land use changes would provide information for
optimization of land use distribution and improvement of ecological soil functions.
Materials and methods
Site description
Study site is located in the Indagi Mountain Pass of
Cankiri at an altitude of 1,450 m above sea level and
approximately 131 km north of Ankara, Turkey
(Fig. 1). The whole region has terrestrial climate with
annual precipitation of 500–800 mm with actual
amounts determined by elevation, and average temperature is 21.1°C in summer and −0.5°C in winter.
There are no significant climatic differences in the
study area to the extent that climate could alone have
an effect in changing soil properties regardless of the
land use changes. Uniform local climate exists in the
five bordering land use types chosen as the research
site. However, micro-climatic conditions resulted
from topographical discrepancies in the study area
might be expected to have an influence on varying
soil properties.
The geological strata in the study area belong to
Pliocene Ilgaz formation and Miocene Mamak formation. While the former mainly contains sandstone,
claystone, conglomerate, breccia, and marn, the latter
103
is composed of magmatic rocks like serpentine, andesite, and basalt. Sandstone, conglomerate, and
breccia of the Ilgaz formation are calcium carbonateand iron oxide-cemented rocks. In situ observations
showed that serpentines of the Mamak formation
greatly underwent the carbonization by hydrothermal
alteration. The soil forming factors relief, parent material, climate, organisms, and time control the spatial
variation of soil properties within landscapes. A large
heterogeneity in terms of the soil formation may
occur at greater depths and this study did not aim to
cover the soil property change with the soil depth at
which geology changed. Therefore, notwithstanding
the underlying geology, the more homogenous soil
properties found close to the soil surface were considered in this study.
Selected site for this research contains five adjacent
land use types, cropland, grassland, woodland, plantation, and recreational land. Of these land uses,
cropland, plantation, and recreational land have been
converted from the grassland or woodland which
were original land uses in the ecosystem of Indagi
Mountain Pass. The woodland comprises of Pinus
nigra Arn. and Quercus pubescens Willd. Principal
tree species of the plantation, which was replaced by
the original woodland 40 years ago, is Pinus nigra
Arn., which is also principal tree species of the
recreational land in the site. The observations also
showed that there were remnants of quite old Pinus
nigra Arn. and Quercus pubescens Willd. in the
cropland, grassland, and recreational land either in
isolation or in groups. Age determination indicated
these remnant trees were 155 years old. Forests of
Pinus nigra Arn. are protected in the mid of the
treeless plains and floristically in very poor conditions
in the central Turkey (Akman 1995). Aytug (1970)
reported the fact that such species as Quercus
pubescens Willd., Quercus cerris L., Pyrus elaeagnifolia Pall., and Cistus larifolius L. exists in the
Anatolia could be proof of existence of Pinus nigra
Arn. since it descended from them, and that Pinus
nigra Arn. vanished in time. These old remnant trees
found in the cropland, grassland, and recreational land
in addition to those present in the woodland and
plantation indicated that original land use over the
whole study area was natural forest.
Dominant grass species in the grassland are
Achillea biebersteinii Afan., Bellis perrennis L.,
Centaurea depressa Bieb, Tanacetum armeneus
104
Environ Monit Assess (2008) 136:101–119
Fig. 1 Study area
(D.C) Schultz Bip., Salvie virgata Jacq., Trifolium
campestre Schreb., Verbascum glomeratum Boiss.,
and Dactylis glomerate L. Agricultural crops are
mostly wheat (Tritucum aestivum L.) and barley
(Hordeum vulgare L.).
Using conventional methods outlined in the manual by the Soil Survey Staff (1993), soil horizons of
the 13 soil pits were sampled and described according
to Soil Taxonomy (Soil Survey Staff 1999). The
method required both pedon-level data and horizonlevel data for soil classification. The former contained
site-level data such as soil series name and geographic
location and the latter contained the physical and
chemical characterization data for individual soil
horizons. Lithic Exerorthents, Lithic Haploxererts,
Typic Haploxererts, Lithic Haploxerepts, and Typic
Haploxerepts are the dominant soils of the area. Time,
topography and climate were major factors controlling soil formation. Soils especially formed on the
gently and steeply sloping areas were characterized
with shallow soil profiles and did not have distinct
pedogenic horizons. These soils were classified as
Entisols. Inceptisols were characterized with Cambic
and Calcic horizons while Vertisols were characterized with deep-wide cracks and slickensides. Most of
the soils were placed in Lithic Subgroup because of
the limited soil depth.
Generally, soil texture is clay loam (CL) in both
cropland and grassland, and sandy loam (SL) in
woodland, plantation, and recreational land.
Soil sampling and analyses
An area of 1,200×4,200 m was selected within the
Indagi Mountain Pass in August 2004, covering all
land use types. With irregular intervals, soil samples
were taken from 0–10 and 10–20 cm soil depth. The
mean sampling intervals were 43, 50, 64, 78, 85 m for
woodland, plantation, grassland, recreation, cropland,
respectively, and was 64 m for whole area. Figure 1
shows 289 locations of soil sampling, and total of 578
disturbed and undisturbed samples by 100 cm3 steel
Environ Monit Assess (2008) 136:101–119
105
cores were analyzed for clay, silt, and sand contents
by hydrometer method (Gee and Bauder 1986), for
soil organic matter (SOM) content by the method of
Nelson and Sommers (1982), and SOM was converted to SOC, based on SOC = 0.58 SOM, for pH
with glass electrode in a 1:2.5 soil/water suspension
(Page et al. 1982), and for soil bulk density (BD) by
Blake and Hartge (1986).
of influence for the spherical model (Samra et.al.
1988). The range a for the Gaussian model is described
as practical range at which the semivariogram reaches
95% of its sill value (Pannatier 1996). The model
parameters are estimated visually as suggested by
Vieira et al. (1983) and Cuenca and Amegee (1987).
Kriged estimate z*(x0) and error estimation variance
σk2(x0) at any point x0 were, respectively, calculated
as follows:
Statistical analysis
Descriptive statistics were used to express the overall
variability within the study area. Spatial variability in
soil properties was defined using geostatistical methods. Experimental semivariograms were developed to
determine the spatial dependence of soil properties
using the following equation given by Journal and
Huijbregts (1978) and reviewed Trangmar et al.
(1987):
N ðhÞ
g ðhÞ ¼
1 X
½zðxi Þ
2N ðhÞ i¼1
zðxi þ hÞ2
ð1Þ
where γ(h) is the semivariance; N(h) is the number of
experimental pairs separated by a distance h; z(xi) is
the measured sample value at point xi; and z(xi +h) is
the measured sample value at point xi +h.
The spherical and the gaussian models are the most
commonly used theoretical models and these models
are, respectively, described by:
g ðhÞ ¼ 0
h¼0
ð2Þ
"
h
g ðhÞ ¼ C0 þ C 1:5
a
3 #
h
0:5
ha
a
g ðhÞ ¼ C0 þ Ch > a
ð3Þ
ð4Þ
and
g ðhÞ ¼ 0
h¼0
ð5Þ
3ðh=aÞ2
h
g ðhÞ ¼ C0 þ C 1
e
g ðhÞ ¼ C0 þ C
h>a
i
ha
ð6Þ
ð7Þ
where, C0 is the nugget variance, C; partial sill value,
and C0 +C; sill value, respectively; and a is the range
z ð x0 Þ ¼
n
X
li zðxi Þ
ð8Þ
i¼1
s 2k ðx0 Þ ¼ m þ
n
X
li g ð x 0
xi Þ
ð9Þ
i¼1
where, li are the weights; μ is the lagrange constant;
and γ(x0 −xi) is the semivariogram value corresponding to the distance between x0 and xi (Vauclin
et.al. 1983; Agrawal et. al. 1995). In addition to the
geostatistics, analysis of variance (ANOVA) was performed to compare the effects of land use types on the
soil properties for two depths of 0–10 and 10–20 cm
individually.
Results and discussion
Variation of soil properties among different land uses
Table 1 shows analysis of variance to compare the
effects of different land use types on SOC, BD, pH,
and textural composition of soils for two soil depths
of 0–10 and 10–20 cm. In Table 1, while upper case
letters indicate statistically significant differences
among soil properties affected by the different land
uses, lower case letters show those between soil
depths for the cases that there were interactions between land use type and depth. Additionally, if there
was no significant difference in the soil properties
with the soil depth for each land use type, the comparisons were made for the mean of both depths
among different land uses. Means superscripted by
the same upper case or lower case letters are not
significant at p
DOI 10.1007/s10661-007-9668-4
The effects of land use changes on some soil properties
in İndağı Mountain Pass – Çankırı, Turkey
M. Başaran & G. Erpul & A. E. Tercan &
M. R. Çanga
Received: 29 May 2006 / Accepted: 23 February 2007 / Published online: 12 June 2007
# Springer Science + Business Media B.V. 2007
Abstract Understanding spatial variability of dynamic soil attributes provides information for suitably
using land and avoiding environmental degradation.
In this paper, we examined five neighboring land use
types in Indagi Mountain Pass – Cankiri, Turkey to
spatially predict variability of the soil organic carbon
(SOC), bulk density (BD), textural composition, and
soil reaction (pH) as affected by land use changes.
Plantation, recreational land, and cropland were the
lands converted from the woodland and grassland
which were original lands in the study area. Total of
578 disturbed and undisturbed soil samples were
taken with irregular intervals from five sites and
represented the depths of 0–10 and 10–20 cm. Soil
pH and BD had the lower coefficient of variations
(CV) while SOC had the highest value for topsoil.
Clay content showed greater CV than silt and sand
M. Başaran (*)
Seyrani Faculty of Agriculture, Erciyes University,
Develi, Kayseri, Turkey
e-mail: [email protected]
G. Erpul : M. R. Çanga
Faculty of Agriculture, Department of Soil Science,
Ankara University,
Diskapi, Ankara 06110, Turkey
A. E. Tercan
Department of Mining Engineering, Hacettepe University,
Beytepe, Ankara, Turkey
contents. The geostatistics indicated that the soil
properties examined were spatially dependent to the
different degrees and interpolations using kriging
showed the dynamic relationships between soil
properties and land use types. The topsoil spatial
distribution of SOC highly reflected the changes in
the land use types, and kriging anticipated significant
decreases of SOC in the recreational land and
cropland. Accordingly, BD varied depending on the
land use types, and also, the topsoil spatial distribution of BD differed significantly from that of the
subsoil. Generally, BD greatly decreased in places
where the SOC was relatively higher except in the
grassland where overgrazing was the more important
factor than SOC to determine BD. The topsoil spatial
distributions of clay, silt, and sand contents were
rather similar to those of the subsoil. The cropland
and grassland were located on the very fine textured
soils whereas the woodland and plantation were on
the coarse textured soils. Although it was observed a
clear pattern for the spatial distributions of the clay
and sand changing with land uses, this was not the
case for the silt content, which was attributed to the
differences of dynamic erosional processes in the
area. The spatial distribution of the soil pH agreed
with that of the clay content. Soils of the cropland and
grassland with higher amounts of clay characteristically binding more cations and having higher buffering capacities had the greater pH values when
compared to the soils of other land uses with higher
102
amounts of sand naturally inclined to be washed from
the base cations by the rainwater.
Keywords Spatial variability . Land use changes .
Organic carbon . Bulk density . Textural composition .
Soil reaction
Introduction
Spatial variability of soil properties affected soil performance and therefore the crop yield (Warrick and
Gardner 1983). Understanding changes of soil properties in the field scale guided plant nutrient applications (Robert et al. 1993) and optimized irrigation
budget in salinity management (Russo 1984). Therefore, there is a great need to spatially investigate the
variability of dynamic soil attributes to refine the agricultural management practices, from which expected
is less environmental degradation.
Spatial changes in soil properties can result from soil
formation factors. Mineral composition and textural
class of soil considerably determine the manner in which
it can be used. Based on clay content, which affects most
of the agriculturally significant soil properties such as
water holding capacity, permeability to water, aeration,
plasticity and nutrient-supplying ability and cation
exchange capacity (Mapa and Kumaragamage 1996),
some generalizations can be made about soil behavior
(Uehara and Gillman 1981). Similarly, the soil reaction
(pH) is another significant soil property to predict
nutrient availability and determine soil ability to benefit
from fertilizer and amendments. Dhillion et al. (1994)
used pH as an indicator of soil fertility in strategies
based on spatial analysis of plant nutrients. Bauer and
Black (1994) quantified the effects of organic matter
content on soil productivity.
On the other hand, spatial variations in soil properties
can also stem from soil management factors or can be in
relation to land use at different scales. Soils of the
natural ecosystems have been characterized by natural
soil intrinsic factors such as climate, topography, aspect,
bedrock, and vegetation. And, land use changes could
also have characterizing effects on soils due to the
extrinsic factors such as fertilization, cultivation, over
grazing and management. In recent years, there has been
a great need for estimating variations in soil quality
especially by human pressure, aiming at an improvement in the agricultural management practices and
Environ Monit Assess (2008) 136:101–119
decreases in environmental damage. Wali et al. (1999)
and Mahtab and Karim (1992) reported that expanding
cropland at the expense of woodland and grassland was
one of the main reasons of degrading soil properties.
Changes in land use can have a marked effect on
soil organic carbon content by means of humification,
decomposition and mineralization of soil organic
matter. The alteration of forest and pastureland into
arable agriculture is one of the main causes of degrading soil organic matter. Cultivation of pastures
led to 25–50% decrease in soil organic carbon (Elliott
1986; Grupta and Germida 1988). In China, when
Alpine grassland soils were converted into arable land
for 8, 16, and 41 years, it was indicated by Wu and
Tiessen (2002) that the organic matter content of soils
decreased by 25, 39, and 55%, respectively. Celik
(2005) has recently reported that relative to soil organic matter of the forest and pasture soils in a southern Mediterranean highland of Turkey, soil organic
matter of the cultivated soils decreased by 44 and
48% for the 0–10 cm layer and 48 and 50% for the
10–20 cm layer over 12 years, respectively.
Land degradation and loss of soil organic matter is
closely linked to the deterioration of such significant
soil physical properties as pore size distribution, bulk
density, aggregation and aggregate stability (Tisdall and
Oades 1982; Elliott 1986). Hajabbasi et al. (1997)
found that deforestation and successive tillage practices
caused nearly 20% increase in bulk density and a 50%
decrease in soil organic matter for a soil depth of 0–
30 cm over 20 years in the central Zagrous mountain
in Iran. Shukla et al. (2004) documented that the bulk
density was the most discriminating soil attribute or the
dynamic soil quality indicator for ascertaining temporal
changes in soil properties in relation to land use and
management. Cultivated soils had higher bulk density
than adjacent soils under forests and pastures for the 0–
10 and 10–20 cm layers in a southern Mediterranean
highland of Turkey (Celik 2005).
In recent years soil scientists focused on predicting
spatial variability of soil properties using geostatistics
and different kriging methods to better understand the
influence of land use changes on soil properties over
small to large spatial scale (Yost et al. 1982; Trangmar
et al. 1987; Miller et al. 1988; Voltz and Webster
1990; Chien et al. 1997; Tsegaye and Hill 1998; Lark
2002; Bo et al. 2003).
Atalay (1997) gives details of highlands of Turkey.
He reports that ecosystems at elevations of 1,500 m
Environ Monit Assess (2008) 136:101–119
and higher with the slope range of 15–40% still
account about 26 and 34% of the total area of
759,978 km 2 , respectively, although important
changes have occurred in rural ecosystems over the
past five decades in a large part of Turkey. Cropland
of Turkey increased approximately 18 Mha from
1952 to 2000 (Anonymous 2000), and overgrazing,
deforestation, and increase in agricultural activity
have intensified pressures on high-altitude fragile
ecosystems (Evrendilek et al. 2004). The objective
of this study is to geostatistically examine the effect
of land use changes on carbon content, bulk density,
reaction and texture of soils of Indagi Mountain Pass
of Cankiri, Turkey, where woodland is an important
source of vegetation and soil organic carbon, and
woodland of the Mountain Pass has been already
strongly affected by agricultural expansion due to the
population growth and socio-economical conditions
in the region. It is expected by this research that
explaining any variation in soil properties affected by
land use changes would provide information for
optimization of land use distribution and improvement of ecological soil functions.
Materials and methods
Site description
Study site is located in the Indagi Mountain Pass of
Cankiri at an altitude of 1,450 m above sea level and
approximately 131 km north of Ankara, Turkey
(Fig. 1). The whole region has terrestrial climate with
annual precipitation of 500–800 mm with actual
amounts determined by elevation, and average temperature is 21.1°C in summer and −0.5°C in winter.
There are no significant climatic differences in the
study area to the extent that climate could alone have
an effect in changing soil properties regardless of the
land use changes. Uniform local climate exists in the
five bordering land use types chosen as the research
site. However, micro-climatic conditions resulted
from topographical discrepancies in the study area
might be expected to have an influence on varying
soil properties.
The geological strata in the study area belong to
Pliocene Ilgaz formation and Miocene Mamak formation. While the former mainly contains sandstone,
claystone, conglomerate, breccia, and marn, the latter
103
is composed of magmatic rocks like serpentine, andesite, and basalt. Sandstone, conglomerate, and
breccia of the Ilgaz formation are calcium carbonateand iron oxide-cemented rocks. In situ observations
showed that serpentines of the Mamak formation
greatly underwent the carbonization by hydrothermal
alteration. The soil forming factors relief, parent material, climate, organisms, and time control the spatial
variation of soil properties within landscapes. A large
heterogeneity in terms of the soil formation may
occur at greater depths and this study did not aim to
cover the soil property change with the soil depth at
which geology changed. Therefore, notwithstanding
the underlying geology, the more homogenous soil
properties found close to the soil surface were considered in this study.
Selected site for this research contains five adjacent
land use types, cropland, grassland, woodland, plantation, and recreational land. Of these land uses,
cropland, plantation, and recreational land have been
converted from the grassland or woodland which
were original land uses in the ecosystem of Indagi
Mountain Pass. The woodland comprises of Pinus
nigra Arn. and Quercus pubescens Willd. Principal
tree species of the plantation, which was replaced by
the original woodland 40 years ago, is Pinus nigra
Arn., which is also principal tree species of the
recreational land in the site. The observations also
showed that there were remnants of quite old Pinus
nigra Arn. and Quercus pubescens Willd. in the
cropland, grassland, and recreational land either in
isolation or in groups. Age determination indicated
these remnant trees were 155 years old. Forests of
Pinus nigra Arn. are protected in the mid of the
treeless plains and floristically in very poor conditions
in the central Turkey (Akman 1995). Aytug (1970)
reported the fact that such species as Quercus
pubescens Willd., Quercus cerris L., Pyrus elaeagnifolia Pall., and Cistus larifolius L. exists in the
Anatolia could be proof of existence of Pinus nigra
Arn. since it descended from them, and that Pinus
nigra Arn. vanished in time. These old remnant trees
found in the cropland, grassland, and recreational land
in addition to those present in the woodland and
plantation indicated that original land use over the
whole study area was natural forest.
Dominant grass species in the grassland are
Achillea biebersteinii Afan., Bellis perrennis L.,
Centaurea depressa Bieb, Tanacetum armeneus
104
Environ Monit Assess (2008) 136:101–119
Fig. 1 Study area
(D.C) Schultz Bip., Salvie virgata Jacq., Trifolium
campestre Schreb., Verbascum glomeratum Boiss.,
and Dactylis glomerate L. Agricultural crops are
mostly wheat (Tritucum aestivum L.) and barley
(Hordeum vulgare L.).
Using conventional methods outlined in the manual by the Soil Survey Staff (1993), soil horizons of
the 13 soil pits were sampled and described according
to Soil Taxonomy (Soil Survey Staff 1999). The
method required both pedon-level data and horizonlevel data for soil classification. The former contained
site-level data such as soil series name and geographic
location and the latter contained the physical and
chemical characterization data for individual soil
horizons. Lithic Exerorthents, Lithic Haploxererts,
Typic Haploxererts, Lithic Haploxerepts, and Typic
Haploxerepts are the dominant soils of the area. Time,
topography and climate were major factors controlling soil formation. Soils especially formed on the
gently and steeply sloping areas were characterized
with shallow soil profiles and did not have distinct
pedogenic horizons. These soils were classified as
Entisols. Inceptisols were characterized with Cambic
and Calcic horizons while Vertisols were characterized with deep-wide cracks and slickensides. Most of
the soils were placed in Lithic Subgroup because of
the limited soil depth.
Generally, soil texture is clay loam (CL) in both
cropland and grassland, and sandy loam (SL) in
woodland, plantation, and recreational land.
Soil sampling and analyses
An area of 1,200×4,200 m was selected within the
Indagi Mountain Pass in August 2004, covering all
land use types. With irregular intervals, soil samples
were taken from 0–10 and 10–20 cm soil depth. The
mean sampling intervals were 43, 50, 64, 78, 85 m for
woodland, plantation, grassland, recreation, cropland,
respectively, and was 64 m for whole area. Figure 1
shows 289 locations of soil sampling, and total of 578
disturbed and undisturbed samples by 100 cm3 steel
Environ Monit Assess (2008) 136:101–119
105
cores were analyzed for clay, silt, and sand contents
by hydrometer method (Gee and Bauder 1986), for
soil organic matter (SOM) content by the method of
Nelson and Sommers (1982), and SOM was converted to SOC, based on SOC = 0.58 SOM, for pH
with glass electrode in a 1:2.5 soil/water suspension
(Page et al. 1982), and for soil bulk density (BD) by
Blake and Hartge (1986).
of influence for the spherical model (Samra et.al.
1988). The range a for the Gaussian model is described
as practical range at which the semivariogram reaches
95% of its sill value (Pannatier 1996). The model
parameters are estimated visually as suggested by
Vieira et al. (1983) and Cuenca and Amegee (1987).
Kriged estimate z*(x0) and error estimation variance
σk2(x0) at any point x0 were, respectively, calculated
as follows:
Statistical analysis
Descriptive statistics were used to express the overall
variability within the study area. Spatial variability in
soil properties was defined using geostatistical methods. Experimental semivariograms were developed to
determine the spatial dependence of soil properties
using the following equation given by Journal and
Huijbregts (1978) and reviewed Trangmar et al.
(1987):
N ðhÞ
g ðhÞ ¼
1 X
½zðxi Þ
2N ðhÞ i¼1
zðxi þ hÞ2
ð1Þ
where γ(h) is the semivariance; N(h) is the number of
experimental pairs separated by a distance h; z(xi) is
the measured sample value at point xi; and z(xi +h) is
the measured sample value at point xi +h.
The spherical and the gaussian models are the most
commonly used theoretical models and these models
are, respectively, described by:
g ðhÞ ¼ 0
h¼0
ð2Þ
"
h
g ðhÞ ¼ C0 þ C 1:5
a
3 #
h
0:5
ha
a
g ðhÞ ¼ C0 þ Ch > a
ð3Þ
ð4Þ
and
g ðhÞ ¼ 0
h¼0
ð5Þ
3ðh=aÞ2
h
g ðhÞ ¼ C0 þ C 1
e
g ðhÞ ¼ C0 þ C
h>a
i
ha
ð6Þ
ð7Þ
where, C0 is the nugget variance, C; partial sill value,
and C0 +C; sill value, respectively; and a is the range
z ð x0 Þ ¼
n
X
li zðxi Þ
ð8Þ
i¼1
s 2k ðx0 Þ ¼ m þ
n
X
li g ð x 0
xi Þ
ð9Þ
i¼1
where, li are the weights; μ is the lagrange constant;
and γ(x0 −xi) is the semivariogram value corresponding to the distance between x0 and xi (Vauclin
et.al. 1983; Agrawal et. al. 1995). In addition to the
geostatistics, analysis of variance (ANOVA) was performed to compare the effects of land use types on the
soil properties for two depths of 0–10 and 10–20 cm
individually.
Results and discussion
Variation of soil properties among different land uses
Table 1 shows analysis of variance to compare the
effects of different land use types on SOC, BD, pH,
and textural composition of soils for two soil depths
of 0–10 and 10–20 cm. In Table 1, while upper case
letters indicate statistically significant differences
among soil properties affected by the different land
uses, lower case letters show those between soil
depths for the cases that there were interactions between land use type and depth. Additionally, if there
was no significant difference in the soil properties
with the soil depth for each land use type, the comparisons were made for the mean of both depths
among different land uses. Means superscripted by
the same upper case or lower case letters are not
significant at p