Descriptive statistics regarding the general characteristics of the study area soils are presented in Table 2. The results of the analysis of variance for soil depth and land use factors and their interactions are shown in Table 3. Furthermore, the results of Pearson's correlation analysis showing the relationships between soil properties are presented in Table 4.
Table 2
Some descriptive statistics of general soil properties in the study site
Soil property | N | Minimum | Maximum | Mean | Standard deviation |
SOC % | 309 | 0.09 | 7.41 | 2.00 | 1.65 |
Carbon stock t/ha | 309 | 0.18 | 69.81 | 21.17 | 16.77 |
Bulk density g/cm3 | 309 | 0.22 | 2.54 | 1.26 | 0.36 |
pH | 268 | 7.51 | 9.51 | 8.48 | 0.46 |
Electrical conductivity µS/cm | 268 | 105.00 | 16170.00 | 2143.31 | 2597.30 |
Aggregate stability % | 268 | 0.52 | 100.00 | 29.81 | 18.49 |
Dispersion ratio % | 268 | 5.20 | 122.83 | 43.10 | 17.22 |
Clay % | 268 | 1.08 | 100.00 | 34.40 | 23.86 |
Silt % | 268 | 0.00 | 81.23 | 30.43 | 17.18 |
Sand % | 268 | 0.00 | 87.79 | 35.16 | 18.48 |
Table 3
ANOVA results for testing land use, soil depth and their interactions on selected soil properties
Source of variation | | SOC | CS | BD | pH | EC | AS | DR | Clay | Silt | Sand |
Land use | P | 0.000 | 0.000 | 0.023 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
F values | 10.134 | 12.078 | 2.870 | 42.401 | 28.206 | 6.424 | 32.341 | 65.575 | 13.211 | 33.688 |
Soil depth | P | 0.000 | 0.000 | 0.000 | 0.015 | 0.699 | 0.908 | 0.008 | 0.003 | 0.270 | 0.025 |
F values | 7.264 | 10.431 | 13.877 | 5.952 | 0.150 | 0.013 | 7.177 | 9.131 | 1.222 | 5.105 |
Land usexSoil depth | P | 0.454 | 0.909 | 0.833 | 0.010 | 0.005 | 0.419 | 0.387 | 0.592 | 0.288 | 0.045 |
F values | 0.998 | 0.525 | 0.624 | 3.365 | 3.870 | 0.979 | 1.040 | 0.700 | 1.255 | 2.478 |
SOC:Soil organic carbon, CS: Carbon stock, BD:Bulk density, EC:Electrical conductivity, AS: Aggregate stability DR:Dispersion ratio |
Table 4
Correlations between selected soil properties
| SOC | CS. | BD | pH | EC | AS. | Clay | Silt | Sand | DR |
SOC | 1 | | | | | | | | | |
CS | 0.840** | 1 | | | | | | | | |
BD | -0.454** | -0.083 | 1 | | | | | | | |
pH | -0.188** | -0.143 | 0.179** | 1 | | | | | | |
EC | -0.025 | 0.010 | 0.136* | 0.270** | 1 | | | | | |
AS | 0.202** | 0.143* | -0.114 | -0.077 | 0.019 | 1 | | | | |
Clay | 0.166** | 0.166** | 0.022 | 0.085 | -0.046 | 0.174** | 1 | | | |
Silt | -0.117 | -0.105 | 0.121* | 0.066 | 0.399** | -0.100 | -0.638** | 1 | | |
Sand | -0.106 | -0.116 | -0.141* | -0.171** | -0.311** | -0.132* | -0.698** | -0.106 | 1 | |
DR | -0.125* | -0.100 | 0.097 | 0.297** | 0.569** | 0.028 | 0.013 | 0.208** | -0.210** | 1 |
** Correlation is significant at the 0.01 level (2-tailed). |
* Correlation is significant at the 0.05 level (2-tailed). |
SOC:Soil organic carbon, CS: Carbon stock, BD:Bulk density, EC:Electrical conductivity, AS: Aggregate stability DR:Dispersion ratio |
3.1. Soil organic carbon
The SOC in the study area varied between 0.09-7.41% (Table 2). According to different land use types, the average SOC can be listed in descending order as rangeland>marshland>shrubland>cropland>dry-lake area (Fig. 5). The average SOC content of the study area was statistically significantly affected by the land use change (P<0.05) (Table 3). While the organic carbon content of rangeland and marshland soils was statistically similar, it was different from other land use types. The SOC in the dry-lake area was lower and statistically different from other land uses. The SOC in the shrubland and cropland also showed statistical similarity (Fig. 5). The SOC content in rangeland, marshland, and shrubland areas was found to be higher than other land uses.Similar to our study, Tangen and Bansal (2020) found approximately 6% SOC in inner natural marshland soil at 0-15 cm depth The high SOC content in the rangeland, marshland and shrubland areas could be explained by the continuous input of organic material from their aboveground plant biomass than the other land uses. The amount of organic carbon, nitrogen, and phosphorus in wetland soils depends on organic matter accumulation (Frolking et al. 2001; Avnimelech et al. 2001). Plants in the growth process affect organic carbon by changing the environment of the soil (Santin et al. 2008). In the study conducted by Compton and Boone (2000), high productivity and perennial flooding in the two marshes indicated the high rate of carbon and nutrient accumulation in wetland soils, leading to the formation of large amounts of organic residues in the soil and slow decomposition of soil organic matter. According to the results of this study, the draining of the wetland and converting it to agriculture affected the SOC adversely. It is thought that the low SOC in the dry-lake area may be due to the decomposition of the organic matter in that region and the absence of new organic matter input in its place.
The statistical analysis results according to the soil depth factor showed that the average SOC was affected by the change in soil depth (P<0.05) (Table 3). As the soil depth increased, SOC decreased. The SOC contents at the 1st and 2nd depth levels were 2.62% and 2.05%, respectively, and statistically similar, higher, and different from other depths (Fig. 5). The SOC at the 2nd, 3rd, and 4th depth levels was statistically similar. The SOC at the 5th depth layer was both the lowest and different from the other depths (Fig. 5).
As in this study, Luo et al. (2011) determined the highest SOC values at the depth level of 0-10 cm. It was recorded that the SOC decreased considerably at depths below 20 cm. The distribution of plant roots in our sampling plots decreased with the increasing soil depth. This distribution explains the high amount of organic matter from plant biomass and belowground biomass in the topsoil (Dong et al. 2010). Again, Zhu et al. (2021) stated that the organic matter was the highest in soybean fields at 20-40 cm and 40-60 cm depth and at 0-20 cm in the drained wetland. They found that organic matter varied significantly depending on the depth in only natural wetlands and drained wetlands. In addition, Xia et. al. (2021) reported that SOC decreased with increasing soil depth.
In our study, the SOC content was lower in croplands compared to rangelands and marshlands. Wetland losses for agricultural purposes reduce SOC and carbon sequestration (Wang et al. 2010; Liu et al. 2019). Tillage activities disrupt the underlying ecosystem and expose it to aerobic aeration, increase the organic matter decomposition rate, and cause a decrease in the organic matter content of the soils (Reicosky and Lindstrom 1993; Gesch et al. 2007). The reason for the higher organic carbon content in the cropland compared to the northern marshland, even a little, may be the use of animal manure. Indeed, fertilization and tillage affect soil chemical properties (Gesch et al. 2007; Wright et al. 2007). Changes in water conditions in wetlands due to drainage activities may affect the accumulation of organic matter in the wetland. Wetland drainage decreases wetland productivity and accelerates the decomposition of more organic matter by ensuring its contact with air (Page and Dalal 2011). In a study conducted in Northeast Germany, it was stated that the organic carbon loss in a peat field drained 40 years ago was 37% (Kluge et al. 2008). Again, in a study in the Sanjiang Plateau in China, it was stated that deterioration in water-temperature conditions could accelerate decomposition, agricultural production activities might also cause a sharp decrease in the amount of organic matter returned to the soil, and this might cause a significant loss in SOC and nutrients in the cultivated areas (Song et al. 2004).
The SOC was positively correlated with aggregate stability, clay and carbon stock and negatively correlated with pH, DR, and bulk density (Table 4). Likewise, Luo et al. (2011) and Xia et al. (2021) noted that bulk density affected the organic carbon accumulation of the soil. Low bulk density makes the soil looser and ensures better permeability and better water holding capacity. This creates the desired environment in terms of organic carbon accumulation (Sakin 2012). Similar to the results of this study, Gebrehiwot et al. (2018) and Adesuyi et al. (2019) also found a negative correlation between soil pH and organic carbon. Likewise, Zhang et al. (2011) noted that the mechanical composition of the soil, bulk density, salinity, and nutritional status could affect the dynamics of soil carbon since it would directly affect the capacity of vegetation.
3.2. Carbon stocks
The carbon stock of the soils varied between 0.18-69.81 ton/ha (Table 2). The average carbon stocks of the soils according to land use patterns were listed in descending order as rangeland>marshland>shrubland>cropland>dry-lake area (Fig. 5). As land use changed, the carbon stocks of the soils also changed statistically significantly (Table 3).
The carbon stocks of the soils in the rangeland were similar to the carbon stock measured in the marshland area but were higher and statistically different from the values measured in other land use soils. The carbon stocks of cropland and shrubland soils were statistically similar. Again, the carbon stocks of shrubland and marshland soils were statistically similar (Fig. 5).
The carbon stock of the soils changed at a statistically significant level according to the soil depth (Table 3). In general, as the soil depth increased, the carbon stock of the soils decreased (Fig. 5). The carbon stocks at the 1st, 2nd, and 3rd depths were similar to each other and different from the other depths. Again, the carbon stock at the 3rd and 4th depth levels was statistically similar. The carbon stocks of the 4th and 5th depths were also statistically similar (Fig. 5). The average carbon stock was the highest in the soils at the 1st and 2nd depth layers (25.47 ton/ha, 25.75 ton/ha, respectively) and the lowest at the 5th depth layer (2.80 ton/ha) (Fig. 5).
In the IPCC (2019) report, the default carbon stock values in hot temperate dry climate zones were reported to be 24 ton/ha in high-activity clay soils for a 30-cm soil depth and 74 ton/ha in wetland soils (IPCC 2019). In this study, the total carbon capacity stored in the 40-cm soil column was 115.68 ton/ha in the rangeland, 82.41 ton/ha in the shrubland, 81.52 ton/ha in the marshland, 53.86 ton/ha in the cropland, and 24.74 ton/ha in the dry-lake area. In the Turkey Greenhouse Gas Inventory Report (2020), it was predicted that the soil of a wetland with the carbon stock of 36.37 ton/ha for the Central Anatolian steppe conditions would store 32.14 ton/ha of carbon 20 years after its conversion to cropland.
When a general evaluation was made, the highest carbon stock was found in rangeland, marshland, and shrubland soils. A relatively lower storage capacity was detected in the soils in the cropland and dry-lake area. When the dry-lake area is examined, it can be concluded that the soils here may have lost a large part of the stored carbon after drying. Carbon stock in the cropland is thought to be contributed by fertilization resulting from agricultural activities. The higher carbon stock in rangeland, shrubland, and marshland soils can be explained by the organic matter contribution provided by vegetation. These results show that human activities that do not have continuous vegetation, such as agricultural activities, affect the organic carbon and carbon stocks of the soil. The results of this study revealed the importance of protecting marshlands, rangelands, and shrublands, which are an important sink for the global carbon cycle, against human effects. Yang et al. (2013) reported that total organic carbon values in the topsoil were affected by land use changes. The researchers detected that organic carbon in natural wetlands (Humus wetland (203.5 g/kg) and wet grassland (59.2 g/kg) was higher than other land use patterns. They stated that draining the humus wetland caused a significant decrease in the SOC (52%). The soil organic matter decreased by 45% in the drained wet grassland.
Lands, the use of which was changed after the draining of wetlands, started to store carbon again. It was concluded that the carbon in the dry-lake area, which lost its water lastly, was lost to a significant extent.
The carbon stock of the soils was positively correlated with aggregate stability, clay, and organic carbon content and negatively correlated with pH (Table 4).
3.3 Bulk density
The bulk density of the soils in the study area varied between 0.22-2.54 g/cm3 (Table 2). According to land use patterns, the bulk density of the soils was listed in descending order as shrubland>cropland>dry-lake area>rangeland>marshland (Fig. 6). The average bulk densities of the soils were statistically significantly affected by the change in land use (P<0.05) (Table 3). The average bulk density of the soils taken from the marshland differed statistically from the values determined in other land uses. The average bulk densities of the soils under the other four land uses were statistically similar (Fig. 6).
When examined in terms of soil depth, the bulk densities of the study area soils were statistically significantly affected by the change in soil depth (Table 3). The bulk density of the topsoil was lower and statistically different from the subsoils. In general, as the depth of the soil increased, the bulk density also increased (Fig. 6).
The reason for the low bulk density in marshlands can be explained by the continuous organic material input in these areas and, therefore, the higher amount of organic matter compared to the cropland. The close bulk density to the cropland in the rangeland and shrubland can be explained by the pressure of grazing on these areas. The higher bulk density in the cropland compared to the marshland and rangeland may be due to low organic matter and soil cultivation. Likewise, Tufa et al. (2019), Yitbarek et al. (2013), and Takele et al. (2014) found that the bulk density of agricultural soils in the topsoil was higher than the bulk density in the rangeland and forest areas.
The bulk density of the soils was positively correlated with pH, EC, and silt content and negatively correlated with sand content and SOC (Table 4). SOC is a property that controls bulk density and porosity. As the organic carbon content of the soil increased, its bulk density decreased.
3.4 pH
The pH of the soils in the study area generally varied between 7.51-9.51 (Table 2). The average pH of the soils according to different land uses was listed in descending order as dry-lake area>shrubland>rangeland>cropland>marshland (Fig. 7). The pH of the soils was statistically significantly affected by changes in land use (P<0.05) (Table 3). The average pH values were similar in the soils taken from dry-lake and shrubland areas and were statistically different from the soils taken from other land use patterns. The average pH of the soils taken from cropland and marshland areas was similar and different from the soils taken from other land use patterns. The decrease in pH in cropland soils could be caused by the washing out or depletion of the basic cations in the soil or by nitrogen fertilization (Chauhan et al. 2014; Tilahun 2007). The average pH of rangeland soils differed statistically from other land use patterns (Fig. 7). It is thought that the low pH in the marshland may have been caused by the high organic carbon content and the humic acids formed in the environment as a result of the decomposition of the vegetative material (Dube and Chitiga 2011). The average pH of the topsoils was 8.43, and that of the subsoils was 8.57, and the pH varied statistically significantly according to the soil depth (Fig. 7, Table 3). The pH can be used as an indicator for the quality of wetland soils under different land uses in terms of assessing the degradation in wetland soils. Zhu et al. (2021) also reported that the pH of 0-20 cm significantly changed between land uses that were converted to natural, drained, soybean agricultural lands and later rice cultivation areas, but there was not a very significant change.
The pH properties of the soils were positively correlated with EC, DR, and bulk density and negatively correlated with sand, organic carbon, and carbon stock (Table 4). Similar to this study, Yang et al. (2013) reported that the pH values of soils were negatively correlated with the total organic carbon.
3.5 Electrical conductivity (EC)
In general, the electrical conductivity (EC) values of the soils taken from the study area were between 105-16170 µS/cm (Table 2). The average EC values of the soils according to different land use patterns were listed in descending order as dry-lake area>shrubland>rangeland>marshland>cropland (Fig. 7). EC was statistically significantly affected by the change in land use (P<0.05) (Table 3). The average EC values were statistically different in the soil samples taken from the rangeland from the EC values of the samples taken from other land use patterns. The average EC of cropland and marshland soils was similar but different from other land uses. Again, the average EC of the soils taken from the dry-lake and shrubland areas was similar, but both values were higher and statistically different from other land uses (Fig. 7). When the evaluation was made by considering only the soil depth factor, the average EC in the topsoils was determined to be 2013 µS/cm and 2083 µS/cm in the subsoils, and it was statistically similar. In other words, the soil depth did not significantly affect EC (P>0.05) (Table 3).
In the study area, the salinity problem was observed, especially in the soils in the rangelands, shrubland, and dry-lake area in the Ovaçiftliği region. During the field studies, salt crystals were found in some places on the soil profile and surface in these regions (Fig. 8). It is thought that this may be related to the groundwater level close to the land surface in these regions. It is considered that irrigated farming practices in cropland soils may have reduced soil salinity by washing the topsoils.
It was determined that EC was positively correlated with pH, silt, DR, and bulk density and negatively correlated with sand content (Table 4).
3.6 Aggregate stability
The aggregate stability values of the soils in the study area varied between 0.52-100% (Table 2). The average aggregate stability of the soils according to different land use patterns was listed in descending order as marshland>dry-lake area>cropland>rangeland>shrubland (Fig. 9). The aggregate stability of the soils was statistically significantly affected by land use changes (P<0.05) (Table 3). The average aggregate stability of the soils taken from the shrubland was different from the aggregate stability of the soils taken from other land use patterns (Fig. 9).
The aggregate stability of the soils taken from the marshland was similar to that of the soils taken from the cropland and dry-lake area and different from other land use patterns. Again, the aggregate stability of the soils taken from the rangeland was similar to the soils taken from cropland and dry-lake area and statistically different from other land uses (Fig. 9). It was observed that the aggregate stability decreased in the areas where agriculture and animal grazing were performed in comparison with the marshland and dry-lake area. Thus, Mainuri et al. (2013) noted that tillage reduced aggregate stability. It is thought that the lower aggregate stability in the shrubland may be due to the higher sand content of the soil. A negative correlation was found between the aggregate stability of the soils and the sand content in the correlation analysis (Table 4).
According to the soil depth, the average aggregate stability of the topsoils (32.62%) was higher compared to the subsoils (31.02%). However, this difference was not statistically significant (Table 3).
The aggregate stability of the soils was positively correlated with clay content, SOC, and carbon stock and negatively correlated with sand content (Table 4). Mainuri et al. (2013) found a positive correlation between aggregate stability and soil organic carbon. Thus, the high values mentioned in the marshland with the high clay and organic carbon content also confirm this. The high sand content and low clay content in the shrubland probably reduced the aggregate stability.
3.7 Dispersion ratio (DR)
The DR values of the soils in the study area varied between 5.20-123% (Table 2). When evaluated in general, the fact that the soils in the study area have DR>15 indicates that they are sensitive to erosion (Balcı, 1996). The DR values of the soils according to different land use patterns were listed in descending order as shrubland>dry-lake area>marshland>rangeland>cropland (Fig. 9). Land use change statistically significantly affected the DR of the soils (P<0.05) (Table 3). The DR values of cropland, dry-lake area, and shrubland soils were different from each other and other land use patterns. The average DR of rangeland and marshland soils was statistically similar (Fig. 9).
Soils that seem to be most sensitive to erosion were identified as shrubland and soils in the dry-lake area (Fig. 9).
When evaluated in terms of the soil depth, it was determined that the DR values (39.67%) of the topsoils in the study area were lower and statistically significantly different than the subsoils (46.53%) (P<0.05) (Fig. 9) (Table 3). The topsoils were more resistant to erosion than the subsoils.
According to the correlation analysis, DR was positively correlated with pH, EC, and silt content and negatively correlated with sand content and SOC (Table 4).
3.8 Particle size distribution
According to the evaluation made according to the International Soil Society triangle (Tommerup 1934), soils in the study area had the loam-clay texture in the cropland and marshland areas, the clay loam texture in the rangeland area, the loam texture in the shrubland area, and the clay texture in the dry-lake area.
3.8.1. Clay
The clay content of the soils varied between 1.08-100% (Table 2). According to the land use patterns, the average clay contents were listed in descending order as dry-lake area>marshland>cropland>rangeland>shrubland (Fig. 10). The clay content of the soils was statistically significantly affected by the change in land use (P<0.05) (Table 3).
The soils taken from cropland and marshland areas were similar in terms of clay content. However, the soils taken from other land uses were different. The clay content of the soils taken from shrubland, rangeland, and dry-lake areas was statistically different (Fig. 10).
According to the soil depth, the clay content of the topsoils (30.55%) was lower and statistically different from the clay content of the subsoils (38.25%) (P<0.05) (Table 3, Fig. 10).
The clay content of the soils was positively correlated with aggregate stability, SOC, and carbon stock and negatively correlated with silt and sand content (Table 4).
3.8.2 Silt
The silt content of the soils generally varied between 0-81.23% (Table 2). According to different land use patterns, the average silt contents of the soils were listed in descending order as shrubland>rangeland>cropland>marshland>dry-lake area (Fig. 10). The silt content of the soils in the study area changed statistically significantly as the land use changed (P<0.05) (Table 3).
The average silt content of the soils in the dry-lake area was lower and statistically different from that determined in other land use patterns. The silt content of the shrubland soils was similar to the values in the rangeland soils, but it was statistically different from the silt content in other land use patterns. Again, the silt content of the marshland soils was statistically similar to the values determined in the cropland area, but it was different from other land use patterns (Fig. 10).
According to the soil depth factor, silt contents did not differ statistically in the topsoil (30.74%) and subsoil (30.12%) (P>0.05) (Table 3).
It was determined that silt content was positively correlated with EC, DR, and bulk density and negatively correlated with clay content (Table 4).
3.8.3 Sand
The sand content of the soils varied between 0-87.79% (Table 2). According to different land use patterns, the average sand contents were listed as shrubland>rangeland>marshland>cropland>dry-lake area (Fig. 10). The average sand content of the soils was statistically significantly affected by the change in land use (P<0.05) (Table 3).
The average sand content of the soils taken from the dry-lake area, cropland, marshland, and shrubland areas differed statistically. The sand content of rangeland soils was statistically similar to that of marshland and shrubland soils and was different from the soils of other land uses (Fig. 10).
When the sand content was examined in terms of soil depth, it was high in the topsoils of the study area (38.70%) and lower (31.62%) in the subsoils. This difference was statistically significant (P<0.05) (Table 3, Fig. 10).
The sand content of the soils was negatively correlated with EC, pH, aggregate stability, clay, DR, and bulk density (Table 4).
Abbasi et al. (2007) emphasized that the differences between the textures of soils in different land use patterns showed the effects of different utilization and management systems on the soil properties of land use patterns.