Evaluation of Relationship Between Soil Quality Index and Organic Carbon Changes as a Function of Different Land Uses (Case Study: Sahand Region of East Azerbaijan Province)

جغرافیا و مخاطرات محیطی

Article 13, Volume 14, Issue 1 - Serial Number 53, March 2025, Pages 275-298   

Document Type: Research Article

DOI: 10.22067/geoeh.2023.81986.1354

Authors

Solmaz Bidast^{* 1}; Ahmad Golchin²

¹Postgraduate Researcher in Soil Sciencein Soil science, University of Zanjan, Zanjan, Iran

²Professor in Soil science, University of Zanjan, Zanjan, Iran

Abstract

Rangeland soils have always been of interest due to their high organic content, but the change of land use influences the amount of organic carbon, which plays a key role in soil quality. In this research, the quantification of soil quality in the Sahand rangeland, East Azerbaijan Province, and its possible relationship with soil organic carbon were investigated. One hundred and twenty soil samples were taken from two undisturbed and wheat-cultivated rangelands at one sampling depth (0–30 cm) in October 2022. Thirteen soil physical and chemical parameters were measured and screened through principal component analysis (PCA). The minimum data set obtained by PCA was scored by a non-linear scoring function, and then integrated into a soil quality index. Finally, stepwise multiple linear regression was employed to determine the relationship patterns between soil organic carbon and soil attributes. The results showed that the value of the soil quality index in the undisturbed rangeland (0.78) was significantly higher than in the cultivated rangeland (0.63). The highest score value used to estimate the soil quality index was related to the organic carbon indicator (0.73). The mean weight diameter (0.72), clay percentage (0.93), bulk density (0.24), and saturated water content (0.04) in the undisturbed rangeland soil, and acidity (-0.13) and electrical conductivity (-0.48) in the cultivated rangeland soil showed a significant effect on soil organic carbon (as indicated by the highest standardized regression coefficient). It can be concluded that different land use systems play an important role in changing soil quality by affecting the soil attributes, and thus changing the input and preservation of organic carbon in the soil.
Extended Abstract
Introduction
Grassland ecosystems cover about 40% of the Earth's surface and 11 million hectares in Iran. They are essential for biodiversity, livestock forage, soil erosion control, and carbon storage. However, their ability to provide these services depends on proper land management. Soil quality, defined as the capacity to maintain productivity, environmental health, and plant growth, can be negatively affected by land-use changes, such as converting grasslands to agricultural land. Organic carbon is a key indicator of soil quality, especially in arid and semi-arid regions, and can be improved through land management practices, impacting carbon sequestration and reducing atmospheric CO₂. The study focuses on comparing soil quality and organic carbon levels between natural grassland and wheat fields in the Sahand region of East Azerbaijan, and investigating their correlation with soil physical and chemical properties.
Material and Methods
The study was conducted in the Sahand rangelands, located 50 km southeast of Tabriz, where annual rainfall ranges from 300 to 500 mm. The rangeland, rather than forest, is due to the region's topography and short growing season. Two sites with different land uses (natural rangeland and rain-fed wheat) were selected, both with similar environmental conditions (18% slope, northern aspect, and 2,632 meters elevation). Soil samples were collected in October 2022 using a linear transect method. Two transects of 50 meters were established per site, with 10 random 1×1 meter plots for sampling from a 0–30 cm depth. A total of 120 samples (60 per site) were analyzed for various soil properties in the lab. The Soil Quality Index (SQI) was calculated by identifying key indicators through Principal Component Analysis (PCA), scoring them, and aggregating the results. A stepwise regression model was used to relate soil organic carbon to other soil properties, with validation based on adjusted R² and the standard error of the estimate.
Results and Discussion
The comparison of mean physical and chemical properties of soil using an independent t-test at a 5% significance level showed significant differences between the soil properties under the two land-use systems. The cation exchange capacity (cmolc kg⁻¹ 15.65), organic carbon (% 1.62), total nitrogen (% 0.15), clay (% 23.58), saturation moisture (% 41.16), and mean weight diameter of soil aggregates (mm 2.32) were significantly higher in the pasture land-use compared to the agricultural land. On the other hand, acidity (pH 7.34), electrical conductivity (dS m⁻¹ 0.39), sand (% 55.65), calcium carbonate equivalent (% 7.43), and bulk density (g cm⁻³ 1.16) were significantly higher in the agricultural land-use. The land-use change from pasture to agricultural land resulted in reductions of 13.54% for cation exchange capacity, 18.51% for organic carbon, 26.66% for total nitrogen, 4.79% for clay, 19.16% for saturation moisture, 56.03% for the mean weight diameter of soil aggregates, and 2.29% for silt. Conversely, acidity, electrical conductivity, sand, calcium carbonate, and bulk density increased by 6.99%, 25.80%, 0.05%, 23.62%, and 33.33%, respectively. Increased tillage activities in agricultural lands boost microbial activities, leading to a greater breakdown of organic matter and a consequent decrease in soil organic content. Furthermore, the absence of vegetation on the soil surface increases soil erosion and further depletes organic matter and fine soil particles (clay and silt) from agricultural soils. Land-use change causes significant alterations in soil properties, including a decrease in soil quality, rendering it more prone to erosion.
The effects of land-use type on soil quality were evaluated using the Soil Quality Index (SQI). Principal Component Analysis (PCA) of twelve soil physical and chemical properties identified three main components that explained most of the variance. The first component, primarily characterized by organic carbon, explained 58.79% of the total variance and was selected as a key indicator for the Minimum Data Set (MDS). The second component, represented by cation exchange capacity and electrical conductivity, explained 26.15% of the variance and was also selected for MDS. The third component, which correlated with silt and acidity, was similarly included in the MDS. In total, five variables—organic carbon, cation exchange capacity, acidity, electrical conductivity, and clay—were chosen as indicators for the MDS. Non-linear scoring functions for each of the selected indicators were compared using a t-test, revealing significant differences between the two land-use types. Organic carbon, clay, and cation exchange capacity had the highest scores in pasture soils, while in agricultural soils, the highest scores were recorded for organic carbon, acidity, electrical conductivity, clay, and cation exchange capacity. The soil quality index for the pasture land-use (0.78) was significantly higher than that of the agricultural land-use (0.63), indicating a better soil quality in the pasture. Based on a four-tier quality classification, the pasture soil was categorized as high-quality soil (Grade II), while the agricultural soil fell into the moderate-quality category (Grade III).
Conclusion
This study found significant differences in most soil properties between undisturbed rangeland and agricultural soils, with five key indicators (organic carbon, clay percentage, cation exchange capacity, pH, and electrical conductivity) affecting soil quality. Converting rangeland into agricultural land led to a decline in soil quality, primarily due to reduced organic carbon input. The study highlighted that organic carbon played a major role in maintaining higher soil quality in rangelands. Seasonal vegetation removal in agricultural soils increased acidity and electrical conductivity, further decreasing organic carbon and soil quality. Overall, MDS indicators influence soil quality both directly and indirectly through organic carbon levels.
 

Keywords

Non-Linear Scoring Functions; Organic Carbon; Rangeland; Soil Quality

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