Exploring the Influence of Land Use Types on Soil Properties at Arjo-Dhidhessa Sugar Estate, Western Ethiopia

Abstract

This study examined the influence of land use types and soil depth on soil’s physicochemical properties in the Sugar Estate of Arjo-Dhidhessa, western Ethiopia. This study aimed to provide baseline data for future investigations in the study area by exploring significant soil quality indicators across various land use types and soil depths. Fifteen composite soil samples were collected from selected land use types, including fallow land, cropland, irrigated land, forest land, and shrubland, at three different soil depths (0–30, 30–60, and 60–90 cm). Particle size distribution; bulk density (ρb); total porosity (Tp); pH; organic soil matter; and available texture and phosphorus. The exchangeable acidity (EA), cation exchange capacity, and exchangeable bases (EBs) were found to be influenced by land use changes and soil depth. The results revealed that the bulk density (1.43 g/cm²) is highest in the cropland subsurface, whereas forest lands tend to have a relatively high clay content (67%), moisture content (25.74%), and Tp (54.28%). While the pH of irrigated land was 5.17, that of fallow land, cropland, and forest land varied from 5.47 to 5.84. Compared with the other land uses, the forest and shrubland areas presented higher levels of soil organic matter (SOM) (2.49%) and total nitrogen (TN) (0.126%). Forest land presented relatively high SOM (2.45%), TN (0.126%), available phosphorus (AvP) (1.36%), and exchangeable calcium (Ca²⁺) levels (16.82 cmol/kg), whereas irrigated land had presented the lowest amounts (5.22 mg/kg), Ca²⁺ (3.97 cmol/kg), and exchangeable magnesium (Mg²⁺) (0.99 cmol/kg). In contrast, agricultural activities were found to significantly reduce soil quality, as evidenced by higher bulk densities in cropland and irrigated land as well as lower levels of nutrients, including AvP and EBs, primarily due to erosion and crop harvesting. To maintain and improve soil pH and AvP levels, it is essential to adopt sustainable land management practices that contribute to maintaining higher phosphorus levels and improving overall soil fertility.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Summary

➢ Land use types arise from various human activities that potentially influence soil properties.

➢ This study aims to explore significant soil quality indicators under various land use changes and soil depths.

➢ These findings indicate that forest lands tend to have higher clay content, pH, moisture, total porosity (Tp), organic matter (OM), total nitrogen (TN), and AvP than irrigated lands and croplands.

➢ A collaborative study that addresses this critical decline in soil quality status is recommended.

➢ Reducing continuous mechanized agricultural activities and the use of inorganic fertilizers could restore degraded soil quality for sustainable agricultural production.

1. Introduction

Land use refers to human decisions and activities that modify, create, or preserve specific land use types [1]. Land cover encompasses both natural and artificial components of the Earth’s surface, including soil, water, plants, and man-made structures [2]. The rapid growth of the global population and the excessive exploitation of natural resources significantly contribute to changes in land use [3–5]. In particular, natural forests have been extensively cleared to expand agricultural areas to meet the rising global food demand [6].

In Ethiopia, significant land changes are driven primarily by the conversion of forest land and plantations into cultivated land [7–9]. These changes have varied in severity across different regions of Ethiopia [7, 10]. The highland areas have faced severe soil degradation due to deforestation and continuous farming, with losses of an average of 35 tons of soil per hectare across all land use classes and up to 130 tons per hectare for cultivated fields, which is considered among the highest in Africa [11–14]. Consequently, a significant portion of forest land has been converted into agricultural croplands to meet the needs of densely populated regions [15].

The sustainability of agricultural production in Ethiopia is seriously threatened by soil nutrient loss, reduced carbon content, and soil erosion [16, 17]. Effective soil resource management is vital for successful agriculture, as soil can rapidly lose both quantity and quality for various reasons [18, 19]. One major factor contributing to soil degradation is the rapid expansion of cropland and grazing activities, which severely impact native forest ecosystems [20–22]. Improper agricultural practices and land cover changes can lead to significant declines in soil health by decreasing soil’s physicochemical parameters and biological activity [23, 24].

The physical and chemical properties of soil and agricultural productivity are significantly affected by changes in land use [25–27]. Land degradation and pollution are caused by changes in land management methods, such as converting forests and fields into farms [28]. The change from forest to crop significantly reduces soil OM (SOM), adversely influencing overall soil quality [29]. Soil degradation can lead to compaction and erosion, negatively affecting soil penetration, density, carbon content, permeability, and stability [30].

Several studies have been carried out in Ethiopia to assess the effects of various land use modifications on the physicochemical properties of soil [14, 29, 31]. According to previous studies, contaminants and deteriorating conditions reduce the fertility of highland agricultural soils [32]. Specifically, according to Bore and Bedadi [33], on cultivated land, OM, TN, and cation exchange capacity (CEC) have declined by approximately 76%, 61%, and 39%, respectively, in Ethiopian highlands. Compared to cultivated land, Tesfahunegn [34] reported that forest land had higher levels of SOM, pH, TN, accessible phosphate, and clay. In contrast to forest land and grazing fields, Adugna and Abegaz [35] reported that cultivated land had the lowest levels of OM, TN, CEC, pH, and exchangeable calcium (Ca²⁺) and magnesium (Mg²⁺). The main cause of Ethiopia’s declining soil productivity is the transfer of managed agricultural systems to natural ecologies [24].

Effective soil management and the preservation of soil quality depend on an understanding of how soil responds to farming practices throughout time [36]. In certain parts of Ethiopia, the development of the Sugar Factory Estate has significantly contributed to the degradation of soil [37]. Large-scale irrigation was introduced in the Dhidhessa Basin by the Arjo-Dhidhessa sugar factory in 2009 [38]. Regretfully, an inadequate study has yet to be performed to assess how changes in the utilization of land use types caused by the expansion underlying extensive irrigation of the Arjo-Dhidhessa Sugar Estate influence the physical and chemical characteristics of the soil. However, few studies have been conducted on the Arjo-Dhidhessa Sugar Estate in terms of the irrigation potential of the Dhidhessa River Basin in Ethiopia [39]. Duguma [40] focused on understanding the hydrological system of the Dhidhessa Basin, particularly, the effects of land use and soil depth on soil properties, as this study area lacks spatially relevant data.

Therefore, it is important to assess the physicochemical characteristics of the soil at different soil depths for each land use type to ensure responsible land resource management and improve sustainable crop productivity in the study area. Therefore, the main objective of this study was to examine the physical and chemical properties of soil influenced by land use type and soil depth at Arjo-Dhidhessa Sugar Estate, western Ethiopia.

2. Materials and Methods

2.1. Description of the Study Area

2.1.1. Location of the Study Area

Arjo-Dhidhessa Sugar Estate is located in the East Wallaga Zone, Oromia region, 395 km from Addis Ababa, and 18 km from Jimma Arjo district (Figure 1). The estate shares boundaries with specific areas of the Buno, Bedele, and Jimma Zones, which are located in the west of Ethiopia. Geographically, it lies between latitudes of 7°36′00″ and 9°36′00″ north and longitudes of 35°32′00″ and 37°34′00″ east. The area spans elevations varying from 620 to 3203 m overhead sea level, with some mountains exceeding 3500 m. It covers an estimated 800 km² area. The slope distribution in the region shows that approximately 67.2% of the area has slopes greater than 8%, whereas the remaining 32.8% ranges from mild to less severe (< 8%) [5]. The study area experiences an average annual rainfall of 1400 mm, with a peak occurring from May to October.

[figure(s) omitted; refer to PDF]

2.1.2. Topography

Topographically, the subbasin is thought to be 27,800 km², and the elevation varies from 620 to 3203 m above sea level, excluding mountains with heights greater than 35,000 m [41]. When the general slope spread is categorized by slope class, it makes up a sizable portion of the area (67.2%), with a general slope above 8% and 32% of the area covered by slopes that vary from quite moderate to less steep (< 8%) [42].

2.1.3. Climate

The mean rainfall, which is based on 39 years of data (1983–2022), is approximately 2221 mm. The lowest amount of rain fell on average in January (16.98 mm), whereas the highest was recorded in July (428.3 mm) (Figure 2). The figure depicts the unimodal rain trend in the study area, with monthly precipitation progressively increasing from April to a peak in July and then progressively decreasing through December. The study area experiences temperatures ranging from 11.2°C to 38.5°C, with an average yearly temperature of approximately 23.7°C, according to temperature readings for the years 1983–2022. According to Figure 2, the average monthly lowest temperature falls between 11.2°C and 17.1°C, and the average monthly high temperature fluctuates between 29°C and 38.5°C.

[figure(s) omitted; refer to PDF]

2.1.4. Land Use Types and Farming Systems

The area was distinguished in a mixed farming system that included agriculture, raising cattle, and growing sugarcane. Arjo-Dhidhessa has a variety of soil types that are related to the local geography. The majority of the research area is made up of Precambrian basement rocks from the algae group, which are high-grade genetic and pretectonic granites [5].

Tadese et al. [43] reported that the predominant soil type is black, with red and brown soils appearing occasionally. Shallow to very deep, well-drained, clay loam to clay-textured soils are found on uplands that are somewhat stream-dissected and have flat to mild undulations [44]. The major primary land use types are natural forest land, shrublands, fallow lands, croplands, and irrigated lands. The total concession area of the Arjo-Dhidhessa Sugar Estate factory was 80,000 ha, with 8 command areas. The total command area, including buildings and residential areas, is 28,092 ha, the total area of irrigated land being planted is 20,000 ha, and 4047 ha of sugarcane plantations are harvested for sugar milli (raw sugar) [45].

2.2. Methodology

2.2.1. Sampling Design, Soil Sample Collection, and Soil Sample Preparation

To obtain a basic idea of the variances in the study area, an image-based survey was first carried out. To choose sampling sites that are typical of the land use system in Arjo-Dhidhessa Sugar Estate, western Ethiopia, consideration was given to the available land use types. Five main land use types and vegetation categories, cropland, forest land, irrigated land, fallow land, and shrubland, were identified in the study area on the basis of the available land use type histories. The soil was randomly sampled via a soil auger for each land use type. The GPS coordinates of the sampling locations are shown in Figure 3. There were five typical (20 m × 20 m) plots for each form of land use type next to the forest, with a maximum distance of 200 m between them. Subsamples from each of the three depths of soil samples were used to produce a single composite sample, which was then taken from each plot via a basic random technique for each land use type. Each sampling location was cleared of gravel debris, tree roots, and nearby regions before the collection of the soil samples.

[figure(s) omitted; refer to PDF]

For all types of land use, three soil depths were used to collect samples of both disturbed and undisturbed soil. Thus, a total of 15 undisturbed and 15 composite soil samples were collected at three different soil depths (0–30, 30–60, and 60–90 cm).

To determine the bulk density (ρb) and soil moisture content (SMC), undisturbed soil samples were collected from the pits at three distinct depths via a core sampler. Except for TN and organic carbon (OC), which were run through a 0.5 mm sieve, packed in a labeled polyethylene bag, authorized, and delivered to the soil testing laboratories of Finchaa Sugar Estate and the central soil laboratory of Haramaya University, the collected combined soil samples were dried in the air, carefully mixed, smashed, and passed through a 2 mm sieve for each parameter examined.

2.2.2. Analyzing the Soil’s Physicochemical Properties

The USDA textural triangle, a classification scheme described by Bouyoucos [46], was used to evaluate the soil texture, whereas the hydrometric method was used to establish the soil structure. The core technique was used to determine the ρb and Tp of the soil (equations (1) and (3)), whereas the gravimetric approach was used to determine the soil water content.$$\begin{array}{}\text{(1)}& \mathrm{\rho }\mathrm{b}=\frac{\text{dry}\text{mass}\text{of}\text{soil}\text{sample}DM}{\text{volume}\text{of}\text{the}\text{core}\text{sampler}{\text{cm}}^3},\end{array}$$where ρb is expressed in g/cm³, DM is the dry mass in grams, and Vis is the volume of the core sampler in cm³.

A pH potentiometer (model-4070) was used to measure the soil pH (1:2.5) [47]. The Walkley and Black method by dichromate oxidation techniques was used to measure the soil organic carbon (SOC) [48] and the OM in the soil (SOM) was obtained by multiplying the SOC values by 1.724 (OM = 1.724 × % carbon).

The Kjeldahl digestion, distillation, and titration methods [49] were used to quantify total nitrogen (TN), whereas the Bray II method [50] was used to determine available phosphorus (AvP). Using ascorbic acid as a reluctant and UV–visible spectrophotometer set to 882 nm, the phosphorus content of the soil solution was calorimetrically measured via the Riley and Murphy method [51].

The total exchangeable acidity (EA) was determined by saturating the soil samples with an exchangeable potassium (K⁺) chloride solution and titrating them with exchangeable sodium (Na⁺) hydroxide, as described previously [52]. After the ammonium that Na⁺ replaced in a NaCl solution was condensed, the CEC was calculated titrimetrically [53]. An atomic absorption spectrophotometer (AAS, 210/211 Vamp Buck Scientific) was used to measure the concentrations of interchangeable bases, while the lifetimes of the interchangeable bases (Na⁺, K⁺, Ca²⁺, and Mg²⁺) were measured via flame photometry following their removal via ammonium acetate buffered at pH 7 [53].

2.2.3. Statistical Data Analysis

All the statistical analyses were carried out via Microsoft Excel and R software (Version 1.1.463). Two-way analysis of variance (ANOVA) (p < 0.05) was employed to examine the effects of different land use/cover types on particular soil physicochemical parameters at three soil levels independently via the general linear model (GLM) approach. A significance test was used for mean separation when an ANOVA revealed a statistically significant difference (p < 0.05), and the means were compared via the least significant difference (LSD) test at p < 0.05.

3. Results and Discussion

3.1. Influence of Land Use Type and Soil Depth on Soil Physical Properties

3.1.1. Particle Size Distributions (Clay, Silt, and Sand)

The particle size distribution (clay, silt, and sand) varies significantly (p ≤ 0.01) and is affected by the interaction of land use and soil depth (Table 1). Compared to fallow and irrigated land, the surface layer of forest land had the highest percentages of sand (27.28%) and silt (20.6%) due to the interaction effects of land use and soil depth. Conversely, the bottom surface layer of the cropland had the maximum amount of clay (72.16%), whereas the top layer of fallow land had the minimum amount of clay (54.56%) (Table 1).

Table 1

Influences of land use types and soil depth on selected soil physical properties.

			Main effects of land use and soil depth
Land use type		Soil particle distribution			Texture	ρb	Moc	Tp	ρs
		Sand %	Silt %	Clay %	Class	${\mathbf{\text{gm}}}^{-\mathbf{3}}$	(%)	(%)	${\mathbf{\text{gcm}}}^{-\mathbf{3}}$
Fallow land		19.41a	17.24b	63.35ab	Clay	1.3b	15.44b	50.94b	2.24b
Cropland		23.61a	17.05d	59.34ab	Clay	1.39a	10.07a	46.28c	2.41a
Forest land		19.65a	13.35d	67a	Clay	1.18c	19.09a	54.46a	2.2b
Irrigated land		24.43a	19.91a	56.1b	Clay	1.36a	17.11a	46.65c	2.36a
Shrubland		20.05a	15.68c	64.27ab	Clay	1.29b	14.89a	51.95c	2.28b
LSD (0.05)		3.56	1.21	4.36		0.83	3.91	2.9	0.83
SEM (±)		1.25	0.32	1.53		0.02	1.37	0.992	0.029
CV (%)		17.7	2.04	7.3		15.60	18.3	6.1	17.9
P value		${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$		NS	${}^{\mathrm{\ast }\mathrm{\ast }}$	NS	${}^{\mathrm{\ast }\mathrm{\ast }}$
Depth (cm)
0–30		27.07b	16.43a	56.5a	Clay	1.23a	10.94a	53.35a	2.21b
30–60		21.3a	16.38b	62.8b	Clay	1.32b	14.7b	49.81b	2.3a
60–90		17.41c	15.99c	67.08c	Clay	1.36c	17.9c	47.01c	2.39c
LSD (0.05)		1.74	1.87	2.1		1.15	2.69	2.56	0.63
SEM (±)		0.54	0.29	0.51		0.23	0.74	0.34	0.23
CV (%)		11.1	16	4.5		14.08	15.2	6.97	37
P value		${}^{\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$		NS	${}^{\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$
Depth (cm)	LUT		Interaction effects of land use type and soil depth
0–30	FaL	27.36a	18.08 cd	54.56h	Clay	1.2a	10.45hi	54.72b	2.13a
	CL	20.08c	15.44fgh	58.48fg	Clay	1.35a	7.97j	47.92d	2.36a
	FoL	27.28a	13.24ijk	59.48f	Clay	1.1a	13.19fg	58.49a	2.1a
	IL	22.28b	20.16a	52.56g	Clay	1.3a	11.4h	50.9c	2.25a
	ShL	26.36a	16.08efg	57.47de	Clay	1.2a	11.69gh	54.72b	2.2a
30–60	FaL	20.32c	17.2cde	63.48de	Clay	1.3a	10.32hj	50.94c	2.24a
	CL	23.4 b	14.12hij	62.38c	Clay	1.38a	14.6ef	46.79de	2.4a
	FoL	19.04cd	14.4hi	66.23c	Clay	1.2a	16.36bcd	54.72b	2.2a
	IL	20.36c	19.8bc	59.84de	Clay	1.38a	17.16bc	45.66ef	2.42a
	ShL	23.44b	14.48ghi	62.08e	Clay	1.32a	15.21de	50.94c	2.23a
60–90	FaL	17.56de	16.44ghi	66c	Clay	1.4a	9.45ij	47.17de	2.36a
	CL	15.36f	12.48def	72.16a	Clay	1.43a	22.74a	44.15fg	2.46a
	FoL	17.44de	12.48jk	70.16b	Clay	1.23a	25.74cde	50.18c	2.3a
	IL	17.32e	18.44bc	62.91de	Clay	1.41a	23.77a	43.38g	2.42a
	ShL	19.36c	16.48def	64.16d	Clay	1.34a	17.78b	50.94c	2.4a
SEM (±)		0.57	0.42	0.36		0.63	0.57	0.57	0.58
LSD (0.05)		1.67	0.96	1.05		0.96	1.67	1.67	1.67
CV (%)		4.73	6.3	1.74		16.76	6.9	2	16.8
P value		${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$		${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	NS

Note: The means of the rows and columns denoted by distinct letters are ${}^{\mathrm{\ast }}$significant at p ≤ 0.05, ${}^{\mathrm{\ast }\mathrm{\ast }}$significant at p ≤ 0.01, and ${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$significant at p ≤ 0.001.

Abbreviations: CL, cropland; CV, coefficient of variance; FaL, fallow land; FoL, forest land; IL, irrigated land; LSD, least significant difference; LUT, land use type; NS, not significant; SEM, standard mean error; ShL, shrubs land.

The higher sand and silt contents in forest land under the surface layer could be attributed to factors such as OM decomposition, leaf litter, and root growth, which can enhance the soil structure and increase sand and silt accumulation. On the other hand, the higher clay content in the subsurface layer of cropland may be due to tillage practices, which can mix and redistribute soil particles, leading to a higher clay content at greater depths [54–56]. The current results are in line with those of Masha et al. [57], who noted that because the soil selectively removes clay fractions from the surface, croplands have lower clay fractions and higher sand fractions. The accumulation of OM and vegetation cover under forest land is what causes the highest amount of clay, although significant rainfall in the area may be the cause of the highest sand content [56]. While the sand and silt contents reduce the soil depth in the soil profile from the surface to the subsurface, the clay content increases under all land use types [57–59].

3.1.2. Bulk Density (ρb)

The bulk density (ρb) was substantially (p ≤ 0.001) influenced by the interaction between land use and soil depth (Table 1). Considering both the factors of land use and soil depth, subsurface cropland had the highest ρb (1.43 g/cm³), and the surface layer of forest land had the lowest ρb (1.1 g/cm³) (Table 1). This result is in line with the findings of Regassa et al. [22], Tigist et al. [14], and Haile et al. [58], who reported that the cultivated areas in the western Ethiopian region of Abobo presented the lowest bulk densities in the surface soil layer (0–20 cm). Low OM content, increased soil disturbance, animal trampling, recurrent tillage operations, and compaction may contribute to croplands having the highest ρb by eliminating pore space and degrading SOM [24, 56, 60]. Due to compaction, reduced OM content, less aggregation, and fewer pore spaces in subsurface soil layers, the ρb increases with soil depth under all land use regimes [61, 62].

3.1.3. Soil Moisture Content (SMC)

The SMC was significantly (p < 0.001) affected by land use and soil depth (Table 1). Table 1 shows that the highest soil Moc (25.74%) was found in the bottom layer of forest land, whereas the lowest soil Moc (7.97%) was found in the top layer of cropland. This result is in line with earlier research conducted in several Ethiopian regions by Chemeda et al. [63] and Alsamin et al. [64]. Forest land has the highest moisture level in the soil, as it can hold onto water and has OM, which may increase the level of clay [61, 65–67]. Furthermore, the soil Moc of deeper soil layers is generally relatively high because the increased capacity of the soil to retain water may be related to the fraction of clay that predominates in the subsurface layer of the soil, which also subsidizes the downward growth in the soil Moc [61, 67, 68] in the soil subsurface layer.

3.1.4. Total Porosity (Tp)

The Tp was significantly (p < 0.001) affected by the interaction effects of land use and soil depth (Table 1). Considering the interaction effect of land use and soil depth, the highest Tp (54.28%) observed on the surface of forest land might be due to litter that falls from trees, which increases the accumulation of SOM, lowers ρb, and facilitates greater root penetration, as well as its capacity for water storage and infiltration [69]. The highest Tp under forest land and shrubland may be due to the litter that falls from trees, which increases the accumulation of SOM and deeper root penetration, according to Bufebo and Elias [12].

Continuous tillage and low OM content in irrigated areas may result in increased soil compaction and reduced soil porosity, which may explain why the lowest Tp (43.38%) was recorded under the subsurface of irrigated areas [70, 71]. The overall decrease in porosity may be caused by the weight of the overlying layer of soil and the decrease in SOM with depth [61, 72].

3.1.5. Soil Particle Density (ρs)

The ρs content was significantly (p ≤ 0.01) affected by land use/land cover type and soil depth and not significantly (p ≤ 0.05) affected by the interaction of land use/land cover with soil depth (Table 1). Considering the main effects of land use and soil depth, the highest ρs (2.41%) was observed under cropland, followed by irrigated land, which had the highest ρs (2.36%), likely due to regular plowing and intensive water for irrigation, which exposes the soil to erosion and disrupts soil aggregation [73–75].

The lowest ρs (2.2%) observed under Forest land might be Forest land because of the protective cover provided by forest vegetation and the promotion of SOM accumulation, resulting in greater soil aggregation, especially in the topsoil (0–30 cm), which can lead to greater ρs than the particle densities of various land uses in the 0–30 cm soil layer [76–80].

3.2. Influences of Land Use Type and Soil Depth on Selected Soil Chemical Properties

3.2.1. pH

The soil pH was not significantly (p > 0.05) affected by the interaction of land use and soil depth (Table 2). The soil pH data revealed that most land uses fall within the moderately acidic range, with fallow land (pH 5.47), cropland (pH 5.58), Forest land (pH 5.84), and shrubland (pH 5.80) categorized as moderately acidic. In contrast, irrigated land, with a pH of 5.17, is classified as “strongly acidic.” These pH values can significantly impact nutrient availability and biological activity within the soil, which are essential factors for plant growth. Therefore, it is advisable to consider soil amendments, such as lime, for irrigated land to increase pH levels and improve nutrient availability, whereas other land uses should implement regular monitoring and management practices to maintain optimal pH levels [81]. The application of inorganic fertilizers is responsible for variations in pH [14]. This result corresponds with previous studies conducted in northern Ethiopia [82].

Table 2

Influences of land use type and soil depth on selected soil chemical properties.

Land use type		Main effects of land use and soil depth
		pH	SOM (%)	TN (%)	C: N (%)	AvP (mgkg−1)
Fallow land		5.47a	1.81a	0.119a	9.44ab	7.92b
Cropland		5.58a	1.76a	0.116a	9.08b	7.79b
Forest land		5.84a	2.45a	0.126a	11.61a	11.26a
Irrigated land		5.17a	1.93a	0.115a	8.48b	7.69b
Shrubland		5.8a	2.05a	0.122a	10.27ab	8.03a
SEM (±)		0.057	0.094	0.012	0.21	2.14
LSD (0.05)		0.165	0.273	0.034	0.60	2.03
CV (%)		16	14.14	16.3	13.4	18.1
P value		Ns	Ns	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	Ns	${}^{\mathrm{\ast }\mathrm{\ast }}$
Soil depth (cm)
0–30		5.8a	2.32a	0.127a	11.53a	11.33a
30–60		5.51a	1.08a	0.124a	10.45a	7.86b
60–90		5.41a	1.60a	0.108a	7.37b	6.43c
SEM (±)		0.128	0.211	0.026	0.16	0.26
LSD (0.05)		0.165	0.272	0.034a	0.60	0.74
CV (%)		16	19.3	14.5	17.5	11.64
P value		Ns	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$
Depth(cm)	Land use type	Interaction effects of land use types and soil depth
0–30	Fallow land	5.8a	2.16a	0.123a	11.79abc	10.25b
	Cropland	5.6a	1.94a	0.124a	10.86abc	10.23b
	Forest land	6.2a	2.96a	0.138a	12.48a	14.36a
	Irrigated land	5.3a	2.15a	0.123a	10.49abc	10.2b
	Shrubland	6.1a	2.3a	0.126a	12.04ab	11.36b
30–60	Fallow land	5.3a	2.15a	0.123a	10.49abc	10.5b
	Cropland	5.4a	1.77a	0.123a	9.92cd	6.93cde
	Forest land	5.73a	2.5a	0.127a	11.41abc	11.21b
	Irrigated land	5.1a	1.89a	0.122a	10.25bcd	6.78cde
	Shrubland	5.8a	2.27a	0.125a	10.56abc	7.21cd
60–90	Fallow land	5.11a	1.49a	0.112a	6.44ef	6.37de
	Cropland	5.73a	1.29a	0.101a	6.47ef	6.23de
	Forest land	5.6a	1.89a	0.114a	10.96abc	8.22c
	Irrigated land	5.12a	1.27a	0.102a	4.7f	5.8de
	Shrubland	5.5a	1.58a	0.115a	8.26de	5.85e
SEM (±)		0.576	0.577	0.0059	0.58	0.577
LSD (0.05)		1.63	1.67	0.017	1.67	1.67
CV (%)		17.9	18.3	7.1		13.2
P value		Ns	${}^{\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$

Note: The means of the rows and columns denoted by distinct letters are ${}^{\mathrm{\ast }}$significant at p ≤ 0.05, ${}^{\mathrm{\ast }\mathrm{\ast }}$significant at p ≤ 0.01, and ${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$significant at p ≤ 0.001.

Abbreviations: CV, coefficient of variance; LSD, least significant difference; NS, not significant; S, significant; SEM, standard mean error.

The slight pH increase with depth could be explained by the migration of cations from the top layer of soil to the bottom surface of the soil [25, 60]. In the subsurface soil layer, the pH of the soil was greater than that in the surface soil layer. Tufa et al. [59] reported that the pH varied between 5.17 and 5.84, which is mildly acidic, in all five land use groups. This result corresponds with the findings of earlier research carried out in northern Ethiopia [82].

3.2.2. Soil Organic Matter (SOM).

The SOM content was substantially (p ≤ 0.01) influenced by the interaction between land use and soil depth (Table 2). The SOM data indicate that fallow land (1.81%), cropland (1.76%), and irrigated land (1.93%) are classified as having low SOM contents, which may limit soil fertility and structure. In contrast, forest land (2.45%) and shrubland (2.05%) fall into the medium category, suggesting a more favorable level of OM that supports improved soil health and nutrient cycling (Table 2). To increase the degree of SOM that is rated as low, it is advisable to implement regular management practices, such as the addition of organic amendments. Similar findings have been reported by He et al. [83], who noted that agricultural practices leading to low SOM levels (below 2%) in croplands negatively affect soil structure and fertility, ultimately impacting crop yields. Conversely, environments such as forests and grasslands, which typically maintain relatively high SOM levels (above 2%), are associated with increased soil health and biodiversity. These findings underscore the importance of managing SOM through practices such as cover cropping and organic amendments to improve soil quality and sustainability in agricultural systems [55, 84, 85].

The decrease in SOM may be related to greater biomass return for the decomposition of plant litter on the surface and a decrease in SOM content with increasing soil depth [86, 87]. This result is in line with other Ethiopian research findings [12, 68]. The higher levels of SOM in the topsoil layer across all land use types can be attributed to the return of biomass, decomposition in the soil surface layer, and deposition of plant remains and animal waste [59, 61]. This result is consistent with that of Bufebo and Elias [12], who reported that SOM decreases with increasing soil depth.

3.2.3. Total Nitrogen (TN)

TN was significantly (p < 0.001) influenced by the interaction between land use and soil depth (Table 2). In terms of the relationship between land use and soil depth, TN was highest (0.138%) in the top layer of forest land, whereas it was lowest (0.101%) in the bottom layer of cropland (Table 2). Owing to the nitrogen released during mineralization and the desirable forest climate conditions that temper soil temperature and thus decrease TN loss through volatilization, the relatively high TN content under forest land may be related to the high SOM content. SOM is the primary source of TN in the soil.

However, the lowest TN content under irrigation and cropland may be caused by ongoing cultivation, vegetation removal for plows that deplete SOM residues and expose the surface layer of irrigated and cropland to direct raindrop generation, loss of residue during crop harvest, and inadequate fertilizer replacement [14, 24, 56, 61, 82, 88–90]. Similarly, according to Chemeda et al. [63], forest land yields a higher TN content than nearby farmed and grazing areas do. According to Fetene and Amera [54], Tufa et al. [59] Abadeye et al. [91], Fentie et al. [61], and Tebekew et al. [87], the decrease in TN from the surface to the subsurface is caused by nitrogen materials, such as SOM on the surface, plant matter, and animal waste.

3.2.4. Carbon-to-Nitrogen (C:N) Ratio

The ratio of C: N was significantly (p < 0.001) affected by the interaction between land use and soil depth (Table 2).Thesurface layer of forest land had the highest C: N ratio (12.48%), whereas the subsurface soil layer of irrigated land had the lowest (4.7%) C: N ratio (Table 2). forest land typically have higher SOM contents and slower decomposition rates, leading to a higher C: N ratio, whereas irrigated lands may have lower SOM contents and greater nitrogen availability from fertilization, resulting in a lower C: N ratio. This suggests that the C: N ratio decreases with increasing soil depth, which may be related to the fact that TN decreases with soil depth at a significantly faster rate than does carbon reduction [14, 92]. This observation corresponds with the results of Chimdi and Gurmessa [69], who reported that in western Oromia, Ethiopia, cultivated land had a lower C: N ratio and a greater forest area. Similarly, Assefa et al. [93] reported that forest land in northern Ethiopia had an improved C: N ratio compared to adjacent cultivation, pastures, and agricultural areas.

3.2.5. Available Phosphorus (AvP)

AvP was substantially (p < 0.01) influenced by the interaction between land use and soil depth (Table 2). The subsurface of irrigated land and the surface of forest land had the lowest and highest AvP contents, at 5.22 mg kg⁻¹ and 14.36 mg kg⁻¹, respectively (Table 2). The reason for the highest AvP under forest land may be the high OM content under forest land, which releases organic phosphorus and increases the AvP under forest land.

The low AvP status observed in most land use types can be attributed to several key factors. First, inherent soil properties, such as high acidity, can immobilize phosphorus, making it less available for plant uptake. Many agricultural soils naturally possess low available phosphorus due to their mineral composition and pH. Second, inadequate management practices, such as insufficient application of phosphorus fertilizer, contribute to nutrient depletion, particularly in cropland and fallow land. Third, the low levels of soil organic matter observed in the data can hinder the mineralization of phosphorus, further reducing its availability. In addition, soil erosion and nutrient leaching are common in intensively farmed areas, exacerbating phosphorus loss. Finally, the high nutrient demand from crops can deplete available phosphorus if not sufficiently replenished through fertilization. A recent study supports these findings; for example, Bizuhoraho et al. [88], Sori et al. [94], and Zhang et al. [95] reported that agricultural practices often lead to low AvP levels due to high soil acidity and inadequate fertilization. Assefa et al. [96] reported that reduced SOM in intensive farming systems restricts phosphorus bioavailability, resulting in crop deficiencies. Furthermore, Kuo et al. [97] emphasized that soil erosion and nutrient leaching significantly underscore the importance of implementing integrated nutrient management practices to increase phosphorus availability and improve soil health.

The accessible soil available phosphorus may decrease as soil depth increases as a consequence of the higher bottom portion of the soil’s clay composition, which absorbs more phosphorus and causes a decrease in natural materials in the soil as depth increases [87, 91]. This outcome is in line with investigations by Fetene and Amera [70], Fentie et al. [61], Abadeye et al. [91], and Tebekew et al. [87], who reported that high levels of OM accumulation in the top layer of soil in various regions of Ethiopia led to higher AvP values obtained from the soil top layer than from the deeper layer.

3.3. Influences of Land Use and Soil Depth on Exchangeable Bases (EBs), CEC, and EA

3.3.1. Exchangeable Calcium (Ca²⁺)

Ca²⁺ levels were significantly (p ≤ 0.001) influenced by the interaction between soil depth and land use/cover (Table 3). The highest Ca²⁺ (16.82 cmol/kg) was recorded in the subsurface forest land, and the lowest Ca²⁺ (3.97 cmol/kg) was found in the irrigated land of the outermost soil layer (Table 3). The highest Ca²⁺ content in forest soils is due to a well-developed root system and little accumulation of SOM, whereas the influence of continuous cropping and irrigation practices with irrigated land may also contribute to Ca²⁺ leaching beyond the root zone, leading to lower Ca²⁺ levels in the topsoil and crop uptake of basic cations such as Ca²⁺ during crop harvesting [24, 79, 98–100]. This result is consistent with those of studies conducted in several regions of Ethiopia [101–103]. Ca²⁺ is leached downward by water percolation, resulting in a higher concentration of Ca²⁺ in the Earth’s below-ground layer than in its surface soil layer [57, 70, 99, 104, 105].

Table 3

Influences of land use type and soil depth on the cation exchange capacity (CEC), exchangeable base (EB), and exchangeable acid (EA).

Land use type		Main effects of land use type and soil depth
		Ca2+ (cmol/kg)	Mg2+ (cmol/kg)	K+ (cmol/kg)	Na+ (cmol/kg)	EA (cmol/kg)	CEC (cmol/kg)
Fallow land		8.71ab	8.19a	0.41a	0.27a	1.2d	18.77a
Cropland		7.53b	2.73c	0.36a	0.23abc	3.28b	14.14b
Forest land		11.03a	5.04b	0.45a	0.19c	1.12d	17.83a
Irrigated land		7.25a	2.62c	0.29a	0.24ab	2.7c	13.1b
Shrubland		8.96ab	6.31ab	0.31a	0.21bc	1.6d	17.4b
SEM (±)		0.49	0.34	0.044	0.02	0.12	0.54
LSD (0.05)		1.44	12	0.126	0.058	0.35	1.57
CV (%)		9.8	0.995	20.8	15.2	18.32	10.2
P value		${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$
Soil depth (cm)
0–30		11.83	3.06	0.56	0.28	2.22a	11.3c
30–60		8.66	6.61	0.30	0.22	1.28b	20.51a
60–90		5.6	5.27	0.24	0.19	2.43a	16.94b
SEM (±)		0.67	0.44	0.028	0.110	0.093	0.42
LSD (0.05)		0.64	0.45	0.056	0.026	0.27	1.2
CV (%)		9.8	12	20.8	15.2	18.32	9.92
P value		${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }}$
Depth (cm)	LUT	Interaction effects of land use types and soil depth
0–30	FaL	7.58fg	7.2c	0.24efg	0.25a	0.59 d	15.85fgh
	CL	5.69hi	2.3g	0.2g	0.17a	4.13a	12.49i
	FoL	4.77ij	2.86fg	0.26efg	0.15a	1.5c	9.79j
	IL	3.97j	0.99h	0.29efg	0.21a	4.34a	9.54j
	SL	5.98hi	1.96gh	0.21g	0.16a	0.54d	8.84j
30–60	FaL	10.02bc	9.38b	0.75a	0.32a	1.36c	21.83bc
	CL	9.21de	3.58ef	0.55bc	0.24a	1.79c	15.37gh
	FoL	16.82a	5.1d	0.45cd	0.18a	1.41c	25.92ab
	IL	11.01bc	4.04e	0.35de	0.29a	0.47d	16.16efg
	ShL	12.11b	10.99a	0.51c	0.26a	1.37c	23.24a
60–90	FaL	8.54ef	8.01c	0.24efg	0.24a	1.61c	18.63dc
	CL	7.7fg	2.32g	0.34def	0.28a	3.29a	14.56ghi
	FoL	11.51b	7.21c	0.64ab	0.24a	0.43d	20.03cd
	IL	6.77gh	2.84fg	0.22fg	0.22a	3.29b	13.33hi
	SL	8.8def	5.98d	0.23efg	0.21a	2.89b	18.12df
SEM (±)		0.02	0.344	0.044	0.02	0.12	0.931
LSD (0.05)		1.424	0.995	0.126	0.058	0.35	2.67
CV (%)		9.8	12	20.8	15.21	18.32	9.92
P value		${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	Ns	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$	${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$

Note: The means of the rows and columns denoted by distinct letters are ${}^{\mathrm{\ast }}$significant at (p ≤ 0.05), ${}^{\mathrm{\ast }\mathrm{\ast }}$significant at (p ≤ 0.01), and ${}^{\mathrm{\ast }\mathrm{\ast }\mathrm{\ast }}$significant at (p ≤ 0.001).

Abbreviations: CV, coefficient of variance; LSD, least significant difference; LUT, land use type; NS, not significant; SEM, standard mean error.

3.3.2. Exchangeable Magnesium (Mg²⁺)

The Mg²⁺ content was significantly (p ≤ 0.001) affected by the interaction between land use/cover and soil depth (Table 3). According to Table 3, the subsurface soil layer of shrubland had the highest Mg²⁺ concentration (10.99 cmol/kg) and the lowest Mg²⁺ content (0.99 cmol/kg) in the subsurface of irrigated land. The highest Mg²⁺ content was significantly (p ≤ 0.001) affected by the interaction between land use/cover and soil depth (Table 3). As shown in Table 3, the subsurface soil layer of shrubland had the highest Mg²⁺ concentration (10.99 cmol/kg) and the lowest Mg²⁺ content (0.99 cmol/kg) in the subsurface of irrigated land.

The high Mg²⁺ content under shrubland might be due to the absence of crop cultivation, which allows natural processes such as weathering and decomposition to contribute to the buildup of Mg²⁺ in the subsurface of the soil by leaching, which is more able to attach to this Mg²⁺ interchangeably, whereas the lowest Mg²⁺ observed may have to contend with the effects of persistent agriculture, which reduces OM and Mg²⁺ absorption by crops during crop harvesting and irrigation process [24, 106–109]. The current results corroborated those of Chemeda et al. [63], who reported that Mg²⁺ was greater under forest land and lower under farms in the Warandhab area, Horo Guduru Wallaga Zone, Oromia, Ethiopia.

The increase in Mg²⁺ that occurs as the soil depth decreases may also be related to the fact that deeper soils have more weathered parent materials and that heavy rainfall can percolate downhill. In addition, there is a chance that the subsurface soil layer has a higher concentration of Mg²⁺ than the surface layer because of a reduction in plant residues [107, 110, 111]. This result is in line with the research carried out in Ethiopia’s Gindeberet district; [57, 57, 94]. According to Desta [112], Assefa et al. [68], and Bayle et al. [57], downward leaching by water percolation in the Antra watershed in Ethiopia’s northwestern highlands is responsible for increasing trends in Mg²⁺ as the soil depth increases.

3.3.3. Exchangeable Potassium (K⁺)

K⁺ content was significantly (p ≤ 0.001) influenced by the interaction between land use and soil depth (Table 3). Table 3 indicates that cropland had the lowest K⁺ content (0.2 cmol/kg), whereas the fallow land subsurface had the highest K⁺ content (0.75 cmol/kg). The maximum amount of K⁺ under fallow land may be linked to dense vegetation cover over an extended period of fallow, which lowers K⁺ leaching and mineral accumulation, as well as a high concentration of clay. Conversely, the lowest amount of K⁺ under cropland was due to continuous farming and inorganic farming practices, which is supported by earlier research showing how weathering intensity, agriculture, and acid-forming inorganic fertilizers have an impact on the dispersion of K⁺ in the soil [69, 102, 113–115]. K⁺ increased with soil depth across all land use categories. This phenomenon may be related to variations in the soil pH, mineral composition, weathering intensity, and particle size distribution, as noted by Chemeda et al. [63], Fetene and Amera [70], Hailemariam et al. [79] and Leul et al. [24], Tilahun et al. [10], and Walche et al. [104].

3.3.4. Exchangeable Sodium (Na⁺)

Na⁺ was significantly (p ≤ 0.001) influenced by the interaction between land use, cover, and soil depth (Table 3). The highest Na⁺ content was observed in the topmost layer of the irrigated land (0.29 cmol/kg). This increase can be attributed to factors such as irrigation practices, water quality, soil salinity management, depletion of OM, compaction, leaching during water irrigation, and extensive agricultural activities. In contrast, forest land presented lower Na⁺ (0.15 cmol/kg) levels (Table 3).

The low value of Na⁺ observed under forest land can be attributed to several interrelated factors, such as the removal of surface vegetation, minimal disturbance, and the absence of active vegetation [22, 57, 58, 69, 111, 116, 117]. Forest ecosystems, which are characterized by diverse vegetation and deep-rooted trees, enhance the soil structure and facilitate the leaching of excess Na⁺. Forest soils often have relatively high OM levels, which improve cation exchangeable capacity (CEC) and drainage, further reducing Na⁺ accumulation. The slightly acidic conditions typical of these soils also contribute to Na⁺ leaching, whereas natural soil processes tend to favor Ca²⁺ and Mg²⁺ over Na⁺. Furthermore, more forest management practices prioritize soil health and minimize disturbance, preventing the accumulation of Na⁺, which can occur in agricultural settings.

In support of this observation, Chemeda et al. [63], Leul et al. [24], and O’Brien et al. [118] demonstrated that forested areas have significantly lower Na⁺ concentrations than agricultural lands, whereas Zhang et al. [119], Jara and Gari [99], and Tebekew et al. [87] reported that forest soils enriched with OM present higher CEC values, effectively reducing Na⁺ levels and promoting essential nutrient availability. Mäder et al. [120] also highlighted the role of natural acidity in forest soils in facilitating Na⁺ leaching, reinforcing the notion that forest soil ecosystems are vital for maintaining balanced soil Na⁺ levels through natural processes and effective land management. The findings of this investigation align with those of Jaleta Negasa [121], who reported that planted forests had lower amounts of Na⁺ than other types of land use. However, Na⁺ improved with increasing soil depth for all land use types [63, 122].

3.3.5. CEC

The soil CEC was significantly (p ≤ 0.001) influenced by the interaction of land use and cover with soil depth (Table 3). The lowest CEC was observed in the topmost layer of the irrigated land (9.54 cmol/kg), whereas the subsurface layer of the forest area had the highest CEC (23.92 cmol/kg) (Table 3). The observed variations in CEC between different land use types and cover types across soil depths suggest that factors such as OM content, soil texture, and management practices can significantly influence the ability of soils to retain and exchange cations. The lower soil CEC in the topmost layer of the irrigated region may be attributed to factors such as lower OM content or greater leaching of cations due to irrigation, whereas the higher soil CEC in the subsurface layer of the forest area could be due to the accumulation of OM and microbial activity. These findings underscore the importance of considering the interactions between land use, cover, and soil depth in understanding soil nutrient dynamics [24, 58, 87, 114, 123, 124]. This research supported the findings of Berhanu Bufore [125], who reported that the agricultural region in Girar Jarso district, North Shewa Zone, Ethiopia, has the lowest average soil CEC value.

The higher soil CEC observed in the subsurface soil layers across various land use changes can be attributed to several factors. These factors may include the accumulation of clay minerals that have a greater capacity to adsorb and exchange cations; leaching processes that lead to the concentration of cations in deeper soil layers; the loss of SOM, which can increase the availability of exchange sites for cations; and the buildup of basic cations from weathering processes [123, 124, 126]. This result is consistent with the studies of Fetene and Amera [70], Molla et al. [73], Haile et al. [58], and Tilahun et al. [10], which demonstrated increasing CEC trends in correlation with decreasing soil depth in several Ethiopian regions.

3.3.6. Exchangeable Acid (EA)

EA was found to be significantly (p ≤ 0.001) influenced by the interaction of land use and cover with soil depth (Table 3). The interaction effects of land use and soil depth play crucial roles in determining EA levels in the soil. In this case, the highest EA value (4.34 meq/kg) observed under irrigated land highlights the combined impact of intense agricultural practices and potentially acidic inputs, particularly at deeper soil depths, where accumulation over time may occur. Conversely, the lowest EA value (0.41 meq/kg) under forest land reflects the buffering capacity and OM content of forest ecosystems, which can help mitigate acidity levels, especially at shallower soil depths. Understanding how these interactions shape soil properties is essential for implementing targeted management practices that address soil acidity issues, optimize soil health, and support sustainable land use planning [24, 57, 100, 104, 113, 115, 127–131]. According to studies by Chemeda et al. [63], Abure [130], and Kebebew et al. [132], cultivated land has comparatively higher EA levels than other land use types. The results of the present study were consistent with those of Beyene [133] and Yacob Heramo [134], who reported that the EA values were the highest and lowest in the surface layer of cultivated land and the lowest in the subsurface layer of forest land at different locations in Ethiopia.

3.3.7. Selected Physical and Chemical Properties of Soil and Their Correlation

When two correlations have the same degree of significance, the likelihood of chance is low. Higher magnitude correlations are stronger, with high values for SOM and pH indicating a stronger link. The EA, CEC, pH, OM, TN, AvP, Mg²⁺, Ca²⁺, Na⁺, K⁺, clay, and CEC correlation matrix are shown in Table 4. The correlation analysis revealed that TN (r = 0.89^∗∗) and pH (r = 0.93^∗∗) were significantly positively correlated with SOM (Table 4). This suggests that as SOM increases, both pH and nitrogen content tend to increase, indicating a potential linkage between OM and available nutrients.

Table 4

Pearson correlation matrix for selected soil physicochemical parameters in the study area.

	Clay	pH	SOM	TN	AvP	Mg+2	Ca+2	Na+	K+	EA	CEC
Clay	1
pH	0.11	1
SOM	0.001	0.93b	1
TN	0.09	0.90b	0.89b	1
AvP	−0.38a	0.53b	0.59b	0.37a	1
Mg+2	−0.31a	0.23	0.22	0.14	0.44b	1
Ca+2	−0.50b	0.31a	0.40b	0.17	0.86b	0.60b	1
Na+	−0.67b	0.23	0.31a	0.26	0.42b	0.44b	0.49b	1
K+	−0.58b	0.35a	0.39a	0.22	0.77b	0.39b	0.70b	0.65b	1
EA	−0.03	0.12	0.11	0.08	0.22	0.11	0.15	0.05	0.41b	1
CEC	0.36a	0.08	0.09	0.10	−0.24	0.13	−0.17	−0.27	−0.17	0.38b	1

Abbreviations: AvP, available phosphorus; Ca, calcium; EA, exchangeable acid; K, potassium; Mg, magnesium; Na, sodium; SOM, soil organic matter; TN, total nitrogen.

^aSignificant at p ≤ 0.05.

^bSignificant at p ≤ 0.01.

In addition, AvP was strongly correlated with both SOM (r = 0.59^∗∗) and Ca²⁺ (0.86^∗∗) (Table 4). This suggests that relatively high levels of phosphorus availability correspond to relatively high levels of Ca²⁺ and relatively high OM contents. In terms of the other variables, clay is strongly negatively correlated with Na⁺ (r = −0.67^∗∗) and K⁺ (r = −0.58^∗∗) (Table 4). These findings indicate that relatively high clay content corresponds to relatively low levels of Na⁺ and K⁺, which may affect the soil structure and nutrient retention. The negative correlation between clay (r = −0.31^∗) and Mg²⁺ suggests that a relatively high clay content may limit Mg²⁺ availability (Table 4). The moderately positive correlations that exist between Ca²⁺ and SOM, TN, and AvP suggest that these nutrients frequently coexist in the same layer. The weak correlation between pH and Na⁺ (r = 0.23) suggests that soil salinity, or the level of Na⁺ in the soil, may not have a significant effect on soil acidity. Except for a moderate relationship with K⁺ (r = 0.38^∗∗), the correlations between the CEC and many other parameters are often weak (Table 4). This could imply that although CEC helps with nutrient retention, its correlation with other factors is not as significant. The results of this study correspond with those of Mesfin et al. [135], Desta [112], and Teferi et al. [136]. EBs, clay, SOM, pH, TN, and AvP. were found to have strong positive associations with CEC in a study by Guteta and Abegaz [137] and Egeta et al. [98].

4. Conclusion

This study examined the influence of land use type and soil depth on the physicochemical properties of soil in the Arjo-Dhidhessa Sugar Estate in western Ethiopia. The findings suggest that soil texture (sand, silt, and clay), soil moisture, TN, SOM, available phosphorus (AvP), cation exchangeable capacity (CEC), and exchangeable bases(EBs) (Ca, Mg, K, and Na) were significantly influenced by land use and soil depth. The highest amount of clay is found in the subsurface layer of cropland, whereas the lowest amount of sand and silt is found in the surface layer of forest land. According to the study, soil pH, SOM, TN, and available phosphorus (AvP) levels decreased under different land uses, particularly cropland and irrigated land. This decline in soil fertility is caused by a number of factors, such as leaching, erosion, and intensive agricultural practices.

These findings underscore the importance of implementing sustainable land management techniques to protect the organic matter (OM), structure, and nutrient availability of soil. To sustain soil quality, techniques include promoting organic farming practices that improve soil quality and nutrient availability, decreasing continuous mechanized or automated agricultural activities, and lowering dependency on inorganic fertilizers. Particularly in irrigated and cropland areas, the adoption of soil conservation techniques, such as cover crops and reduced tillage, can help protect soil from erosion and nutrient loss. These practices can contribute to maintaining higher soil pH, SOM, and available phosphorus (AvP) levels and improving overall soil fertility.

According to these studies, collaboration among agricultural administrations, farmers, and researchers is necessary to address the significant decline in soil fertility. To understand the importance of soil quality and effective management methods, stakeholders must receive education and training in sustainable practices. These findings suggest that future studies should focus on the long-term effects of different land use patterns on pH and available phosphorus (AvP), including other important soil nutrient dynamics. This could provide farmers and governments with important data that are required for developing effective conservation initiatives.

Consent

The instructions for authors contain a statement on the “Ethical responsibilities of authors,” which all authors have read, understood, and complied with where relevant.

Author Contributions

Workina Geleta Likasa wrote the first draft of the manuscript, worked through data gathering and analysis, and received comments from Fekadu Fufa Feyessa and Abdissa Bekele Sima on the previous version. Workina Geleta Likasa, Fekadu Fufa Feyessa, and Abdissa Bekele Sima participated in the conceptualization and design of the study.

Funding

This research has not received any specific grant from a funding agency.

Acknowledgments

We would like to thank the Administration Office of the Horo Guduru Wollega Zone and the Wallaga University of Shambu Campus Department of Soil Resource and Watershed Management for their ongoing oversight, guidance, and direction for this PhD dissertation research.

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