Abstract
Land-use change significantly alters soil physicochemical properties, threatening agricultural productivity and environmental sustainability in the Ethiopian highlands. Although the effects of land use on soil properties have been examined at broader scales in Ethiopia, empirical, site-specific evidence from Dandi District is lacking, despite widespread deforestation and unsustainable management practices that have resulted in substantial but unmeasured soil degradation. This study evaluated the effects of three dominant land-use types: forest, cultivated, and grazing lands on selected soil parameters in Boda Basaka kebele. Using a randomized complete block design across three elevation classes, we analyzed 27 composite topsoil samples collected in February 2021. Standard procedures were used to assess physical and chemical properties. Results showed that forest land maintained significantly superior soil quality, with higher pH (6.29), EC (0.28 dS/m), TN (0.31%), OC (5.57%), OM (9.59%), and CEC (25.86 cmol/kg). In stark contrast, cultivated land suffered the most severe degradation, with the highest bulk density (0.89 g/cm3) due to compaction and notable nutrient depletion. Grazing land showed an intermediate level of deterioration. The conversion of natural forest to agricultural uses in Dandi has profoundly degraded soils, compromising their productive capacity. These empirical, location-specific findings provide crucial scientific evidence to guide targeted sustainable land management interventions, such as agroforestry integration, controlled grazing regimes, and site-specific nutrient replenishment, to restore soil health and enhance resilience in this vulnerable highland landscape.
Keywords: Highland agroecosystem, Land-use change, Nutrient depletion, Soil degradation, Sustainable land management
Subject terms: Ecology, Ecology, Environmental sciences
Introduction
Human activities have profoundly transformed Earth’s surface, with land-use change representing a primary driver of soil degradation worldwide. Forest conversion to agriculture and grazing has been shown to reduce soil organic matter, alter nutrient cycling, increase susceptibility to erosion, and diminish moisture retention capacity, ultimately threatening long-term agricultural productivity and ecosystem sustainability1,2,3. These changes are particularly acute in tropical and subtropical highland regions where steep topography and intensive cultivation exacerbate soil loss. Ethiopia faces severe soil degradation, with an estimated average annual soil loss of 42 tons/hectare/year, resulting in 1–2% crop productivity loss annually4. The economic impact is substantial, costing approximately 1 billion USD annually from on-site and off-site effects5. Rapid population growth has accelerated the conversion of natural grasslands and forests to cropland, particularly in the central highlands, where mixed farming systems dominate6,7,8,9,10. Traditional agriculture has a dual impact: Intensive methods harm the environment, while time-tested practices protect it. For instance, Taddese11, stated that, traditional agricultural practices, combined with inadequate soil conservation measures, have led to the depletion of macro- and micronutrients, threatening food security and rural livelihoods.
Recent studies in Ethiopia have demonstrated that land use significantly influences soil physicochemical properties; however, much of this work has been conducted at broad regional or basin-wide scales. For instance, Tiruneh et al. (2022, 2023)38,39 applied spectroradiometric approaches to model soil organic carbon and fertility across the Nile Basin, while Mulualem et al. (2023) 40 assessed soil nutrient balances under varying land management practices.
Despite their contributions, such large-scale studies often rely on indirect measurements with limited ground-based validation and fail to capture local variability. Consequently, they do not provide the site-specific empirical evidence needed to assess the impacts of distinct land use types on soil physicochemical properties or to support informed land management and policy decisions at the district level such as in Dandi District.Dandi District in West Shewa Zone exemplifies these challenges. The district has experienced substantial forest degradation due to firewood extraction, persistent cultivation, and overgrazing, with natural forest and shrubland covering only 8.5% of the 109,729 ha area12. The remaining landscape comprises 57% agricultural land and 17% grazing land, where soil compaction and nutrient depletion are evident. Despite these pressing issues, no systematic study has quantified how these dominant land-use types differentially impact soil physicochemical properties across topographic gradients in Dandi District. This knowledge gap limits the development of evidence-based soil management strategies tailored to the district’s specific agroecological conditions.
This study was designed to address these gaps by investigating the effects of three dominant land-use types (forest, cultivated, and grazing lands) on selected soil physicochemical properties (texture, bulk density, moisture content, pH, EC, TN, OC, OM, available P, exchangeable cations, and CEC) in Boda Basaka kebele, Dandi District. The specific objectives were to: (1) quantify differences in soil physical properties among land-use types and slope positions; (2) assess variations in soil chemical properties across land-use types; and (3) provide scientifically proven recommendations for sustainable soil management in the district.
Materials and methods
Study area description
Geographic and environmental setting
Dandi District is located in West Shewa Zone, Oromia Regional State, Ethiopia, approximately 78 km from Addis Ababa and 36 km from Ambo town. The study was conducted in Boda Basaka kebele (99 km from Addis Ababa), situated between 8º43’N-9º17’N latitude and 37º47’E-38º20’E longitude, at elevations ranging from 2,200-3,090 m above sea level (Figure 1).
Fig. 1.
Location map of the study area.
The district’s topography is undulating, with soils predominantly loam (50%) and clay (15%), featuring black soils in valley bottoms and red, grainy soils on upper slopes12.
Climate and vegetation
The district experiences a tropical highland climate with bimodal but erratic rainfall (900-1,400 mm annually). The study area falls within the Dega agroecological zone (highland >2,500 m), with mean annual temperatures ranging from 9.6 to 23.3°C. Natural vegetation is under severe pressure from agricultural expansion, with remnants dominated by Juniperus procera and Olea europaea subspecies cuspidata.
Land use distribution
According to the 2013 land use classification, agricultural land dominates (73,360 ha, 57%), followed by grazing land (18,745 ha, 17%) and natural forest/shrubland (9,506 ha, 8.5%) (Table 1). The remaining area comprises settlements, degraded land, and water bodies.
Table 1.
Land use classification in Dandi District.
| S/n | Land use A | Area in ha. | In % |
|---|---|---|---|
| 1 | Agricultural land | 73360 | 57 |
| 2 | Grazing land | 18745 | 17 |
| 3 | Settlement | 10536 | 9.6 |
| 4 | Natural forest and shrubland | 9506 | 8.5 |
| 5 | Degraded land | 5583 | 5.1 |
| 6 | Swamp and marshy land | 1094 | 1 |
| 7 | Urban land | 821 | 0.75 |
| 8 | The land occupied by a lake | 820 | 0.75 |
| 9 | Total | 109729 | 100 |
Source: Dandi District Agricultural Office, 2013.
Soil sampling design
Sampling framework
A randomized complete block design (RCBD) was employed using three elevation classes (upper, middle, and lower slopes) as blocks to control for topographic effects on soil properties. Within each block, three dominant land-use types were selected: Forest Land (FL), Cultivated Land (CL), and Grazing Land (GL). This design accounted for the anticipated influence of slope position on soil erosion and nutrient redistribution.
Sample collection
Soil samples were collected during the dry season (February 2021) to minimize seasonal moisture variation effects. At each land-use type within each elevation class, three replicate plots (20 m × 20 m) were established, resulting in 27 composite samples (3 land uses × 3 elevations × 3 replicates).
Due to the destructive and time-intensive nature of the core method, bulk density was measured on one undisturbed core per land-use type per elevation class (9 cores total), while composite samples were used for other analyses.
Composite sampling protocol
Within each plot, five subsamples were collected using a soil auger in a Z-pattern (four corners + center) at 0-30 cm depth and thoroughly mixed to create one composite sample per plot. This standard composite approach ensures representativeness while reducing micro-scale variability.
Justification for topsoil sampling
The 0–30 cm layer was targeted because it is: (1) the primary zone of nutrient cycling and root activity for most crops; (2) most directly affected by land management practices; and (3) most vulnerable to erosion and organic matter loss. Deeper profile sampling was beyond the scope of this study but is recommended for future research.
Laboratory analysis
The initial soil preparation was conducted following standard protocols, with samples being air-dried, gently crushed, and passed through a 2 mm sieve at Ambo University Chemistry Laboratory. Subsequent physical property analyses adhered to established methods: texture was determined using the Bouyoucos13 hydrometer method with sodium hexametaphosphate dispersion, bulk density was measured from oven-dried cores as per Blake & Hartge (1986) 37, and moisture content was found via the gravimetric drying technique described by Sertsu & Bekele14.
For the chemical analysis, specific standard methodologies were employed. Soil pH and electrical conductivity (EC) were measured in a 1:5 soil-water suspension15. Organic carbon (OC) was determined using the Walkley-Black wet digestion method16,17 with organic matter (OM) calculated as OC × 1.724. Total nitrogen (TN) was analyzed via the Kjeldahl digestion method18,19 and available phosphorus was extracted using the Olsen method20. Exchangeable cations (Ca2⁺, Mg2⁺, K⁺, Na⁺) were extracted with 1 M ammonium acetate and quantified via atomic absorption spectrophotometry21. Finally, cation exchange capacity (CEC) was determined by the sodium acetate saturation method at pH 8.222.
Statistical analysis
Data were analyzed using GenStat 20th edition software (VSN International, UK). Two-way analysis of variance (ANOVA) was conducted to test the main effects of land-use type, slope position, and their interaction on each soil parameter. Where ANOVA showed significant differences (p < 0.05), Tukey’s honestly significant difference (HSD) test was used for mean separation. Descriptive statistics (mean ± standard error) were calculated for all parameters. Assumptions of normality and homogeneity of variance were tested using Shapiro-Wilk and Levene’s tests, respectively. Data were log-transformed where necessary to meet parametric assumptions.
Results
Soil physical properties
Soil texture
Sand and silt content did not differ significantly among land-use types (p > 0.05) (Table 2). However, clay content varied significantly (p = 0.03), with cultivated land showing the highest clay content (51.0%) in subsurface layers, indicating clay migration from surface horizons due to erosion and tillage.
Table 2.
Soil physical properties across land-use types and slope positions
| Land use type and slope | Sand (%) | Silt (%) | Clay (%) | Bulk density (g/cm3) | Moisture content (%) |
|---|---|---|---|---|---|
| UFL | 28.5 ± 2.1a | 22.3 ± 1.5a | 49.2 ± 1.8ab | 0.82 ± 0.03b | 2.8 ± 0.2b |
| MFL | 30.1 ± 1.8a | 21.5 ± 1.2a | 48.4 ± 1.5ab | 0.84 ± 0.02b | 2.9 ± 0.3b |
| LFL | 29.3 ± 2.0a | 23.1 ± 1.6a | 47.6 ± 1.9ab | 0.88 ± 0.04b | 3.1 ± 0.2b |
| UGL | 31.2 ± 1.9a | 20.8 ± 1.4a | 48.0 ± 2.0ab | 0.86 ± 0.03b | 3.9 ± 0.4a |
| MGL | 32.5 ± 2.2a | 19.5 ± 1.3a | 48.0 ± 2.1ab | 0.87 ± 0.03b | 3.8 ± 0.3a |
| LGL | 30.8 ± 2.0a | 21.2 ± 1.5a | 48.0 ± 1.8ab | 0.88 ± 0.04b | 3.6 ± 0.3ab |
| UCL | 29.5 ± 1.8a | 20.5 ± 1.4a | 50.0 ± 2.2a | 0.91 ± 0.03a | 3.7 ± 0.3a |
| MCL | 28.8 ± 2.1a | 21.8 ± 1.6a | 49.4 ± 2.0a | 0.89 ± 0.04a | 3.5 ± 0.4ab |
| LCL | 30.2 ± 1.9a | 20.2 ± 1.3a | 49.6 ± 2.1a | 0.87 ± 0.03ab | 3.6 ± 0.3ab |
| p-value | 0.45ns | 0.38ns | 0.03* | <0.001*** | <0.001*** |
| CV (%) | 12.5 | 11.8 | 15.2 | 8.9 | 18.5 |
Values are mean ± standard error. Means in a column followed by different superscript letters are significantly different (p < 0.05). ns not significant, * = significant, *** = highly significant.
UFL upper forest land, MFL middle forest land, LFL lower forest land, UGL upper grazing land, MGL middle grazing land, LGL lower grazing land, UCL upper cultivated land, MCL middle cultivated land, LCL lower cultivated land.
Bulk density and moisture content
Bulk density differed significantly among land-use types (p < 0.001). Forest land showed the lowest mean bulk density (0.85 g/cm3), attributed to higher organic matter and fewer disturbances. In contrast, cultivated land exhibited the highest bulk density (0.89 g/cm3) due to livestock trampling and tillage-induced compaction. Moisture content was significantly higher (p < 0.001) in grazing land (3.8%) and cultivated land (3.6%) compared to forest land (2.9%), likely due to differences in vegetation cover and evapotranspiration rates.
Soil chemical properties
Soil pH
Soil pH varied significantly among land-use types (p < 0.001). Forest land had the highest mean pH (6.29), followed by grazing land (6.16) and cultivated land (5.92), which was moderately acidic (Table 3). The lower pH in cultivated land resulted from continuous tillage, inorganic fertilizer application, and organic matter decline.
Table 3.
Soil chemical properties across land-use types and slope positions
| Land use type and slope | pH | EC (dS/m) | TN (%) | OC (%) | OM (%) | P (mg/kg) |
|---|---|---|---|---|---|---|
| UFL | 5.97 ± 0.03b | 0.06 ± 0.00ab | 0.27 ± 0.01a | 4.95 ± 0.04a | 8.53 ± 0.07a | 8.95 ± 0.05b |
| MFL | 6.35 ± 0.02a | 0.10 ± 0.00ab | 0.38 ± 0.02a | 6.46 ± 0.04a | 11.13 ± 0.07a | 9.89 ± 0.09a |
| LFL | 6.54 ± 0.07a | 0.09 ± 0.00ab | 0.29 ± 0.01a | 5.29 ± 0.08a | 9.11 ± 0.14a | 6.76 ± 0.09c |
| UGL | 6.12 ± 0.01b | 0.06 ± 0.00ab | 0.21 ± 0.01b | 3.99 ± 0.06b | 6.88 ± 0.10b | 8.95 ± 0.05b |
| MGL | 6.08 ± 0.03b | 0.12 ± 0.00a | 0.19 ± 0.01b | 3.73 ± 0.08b | 6.43 ± 0.14b | 8.79 ± 0.05b |
| LGL | 6.29 ± 0.02b | 0.10 ± 0.00ab | 0.17 ± 0.01b | 3.67 ± 0.08b | 5.56 ± 0.14b | 4.35 ± 0.09d |
| UCL | 5.82 ± 0.02c | 0.16 ± 0.00a | 0.15 ± 0.01b | 3.22 ± 0.08b | 5.55 ± 0.14b | 6.94 ± 0.09c |
| MCL | 5.92 ± 0.02c | 0.05 ± 0.00b | 0.14 ± 0.01b | 1.79 ± 0.06c | 3.09 ± 0.11c | 6.81 ± 0.05c |
| LCL | 6.02 ± 0.02bc | 0.10 ± 0.00ab | 0.16 ± 0.01b | 2.09 ± 0.11c | 3.60 ± 0.18c | 7.00 ± 0.09c |
| p-value | <0.001** | 0.01* | <0.001** | <0.001** | <0.001** | <0.001** |
Values are mean ± standard error. Means in a column followed by different superscript letters are significantly different (p < 0.05).
* = significant, *** = highly significant.
Electrical conductivity
EC values were significantly different among land-use types (p = 0.01), ranging from 0.05 to 0.16 dS/m. All values indicate non-saline soils (EC < 2 dS/m), suitable for most crops. The highest EC occurred in upper cultivated land (0.16 dS/m), likely due to fertilizer residues, while the lowest was in middle cultivated land (0.05 dS/m).
Total nitrogen
TN content differed significantly among land-use types (p < 0.001). Forest land had the highest TN (0.31%), significantly greater than grazing land (0.19%) and cultivated land (0.15%). These values reflect low to moderate fertility levels typical of Ethiopian highland soils. The TN depletion in cultivated land resulted from crop residue removal and accelerated mineralization due to tillage.
Available phosphorus
Available P varied significantly (p < 0.001), with highest values in middle forest land (9.89 mg/kg) and grazing land (8.95 mg/kg), and lowest in cultivated land (6.81–7.00 mg/kg). The low P in cultivated land despite fertilizer use suggests fixation by Fe/Al oxides in these acidic soils, a common issue in Ethiopian highlands23.
Soil organic carbon and organic matter
OC and OM differed significantly among land-use types (p < 0.001). Forest land had the highest OC (5.57%) and OM (9.59%), while cultivated land showed the lowest (OC: 2.36%, OM: 4.09%). These values indicate severe SOM depletion due to deforestation and continuous cultivation, consistent with findings of 48.8% SOM loss after forest conversion24. The elevated OM in forest land reflects continuous litter input and reduced decomposition rates.
Exchangeable cations and cation exchange capacity
Exchangeable K and Na differed significantly among land-use types (p = 0.045 and p = 0.001, respectively), while Ca and Mg did not (p > 0.05) (Table 4). CEC was significantly higher in forest land (25.86 cmol/kg) compared to grazing land (16.04 cmol/kg) and cultivated land (17.31 cmol/kg) (p = 0.005). The higher CEC in forest land is attributed to greater organic matter content, which provides more exchange sites than clay particles alone.
Table 4.
Exchangeable cations and CEC across land-use types and slopes
| Slope of land use | Ca (cmol/kg) | Mg (cmol/kg) | K (cmol/kg) | Na (cmol/kg) | CEC (cmol/kg) |
|---|---|---|---|---|---|
| UFL | 9.98 ± 0.60ᵃ | 1.38 ± 0.60ᵃ | 1.08 ± 0.01ᵃ | 0.13 ± 0.01ᵃ | 21.95 ± 0.32ᵃ |
| MFL | 12.15 ± 0.60ᵃ | 3.47 ± 1.20ᵃᵇ | 1.27 ± 0.01ᵃ | 0.14 ± 0.00ᵃ | 29.57 ± 0.75ᵃ |
| LFL | 10.69 ± 0.60ᵃ | 2.76 ± 0.60ᵃᵇ | 0.96 ± 0.01ᵃᵇ | 0.11 ± 0.00ᵃᵇ | 26.07 ± 0.41ᵃ |
| UGL | 5.18 ± 1.04ᵇ | 4.49 ± 1.58ᵃᵇ | 0.82 ± 0.01ᵇ | 0.11 ± 0.01ᵃᵇ | 17.56 ± 0.67ᵇ |
| MGL | 5.89 ± 0.60ᵇ | 1.39 ± 0.60ᵃ | 0.90 ± 0.01ᵃᵇ | 0.13 ± 0.01ᵃ | 13.66 ± 0.52ᵇ |
| LGL | 7.96 ± 0.60ᵇ | 2.08 ± 1.04ᵃᵇ | 1.07 ± 0.01ᵃ | 0.12 ± 0.03ᵃᵇ | 16.89 ± 1.05ᵇ |
| UCL | 8.16 ± 1.02ᵇ | 2.04 ± 0.00ᵃᵇ | 0.95 ± 0.01ᵃᵇ | 0.07 ± 0.00ᵇ | 18.09 ± 0.62ᵇ |
| MCL | 7.95 ± 2.16ᵇ | 1.73 ± 0.60ᵃᵇ | 0.80 ± 0.00ᵇ | 0.08 ± 0.01ᵇ | 16.39 ± 1.90ᵇ |
| LCL | 7.55 ± 0.59ᵇ | 3.09 ± 1.78ᵃᵇ | 0.79 ± 0.01ᵇ | 0.06 ± 0.01ᵇ | 17.43 ± 4.22ᵇ |
| p-value | 0.423 | 0.231 | 0.045 | 0.001 | 0.005 |
| Significance | ns | ns | * | *** | *** |
| CV (%) | 28.5 | 52.3 | 18.4 | 22.8 | 19.6 |
Values are mean ± standard error. Means in a column followed by different superscript letters are significantly different (p < 0.05).
ns not significant.
* = significant, ** = highly significant.
Principal component analysis
PCA was performed to identify key drivers of soil variability among land-use types. The KMO measure (0.72) and Bartlett’s test (χ2 = 284.6, p < 0.001) confirmed data suitability. Two components explained 68.4% of variance (PC1: 45.2%, PC2: 23.2%) (Table 5).
Table 5.
Rotated component loadings for soil physicochemical properties
| Land use type and slope | Sand (%) | Silt (%) | Clay (%) |
|---|---|---|---|
| UFL | 28.5 ± 2.1a | 22.3 ± 1.5a | 49.2 ± 1.8ab |
| MFL | 30.1 ± 1.8a | 21.5 ± 1.2a | 48.4 ± 1.5ab |
| LFL | 29.3 ± 2.0a | 23.1 ± 1.6a | 47.6 ± 1.9ab |
| UGL | 31.2 ± 1.9a | 20.8 ± 1.4a | 48.0 ± 2.0ab |
| MGL | 32.5 ± 2.2a | 19.5 ± 1.3a | 48.0 ± 2.1ab |
| LGL | 30.8 ± 2.0a | 21.2 ± 1.5a | 48.0 ± 1.8ab |
| UCL | 29.5 ± 1.8a | 20.5 ± 1.4a | 50.0 ± 2.2a |
| MCL | 28.8 ± 2.1a | 21.8 ± 1.6a | 49.4 ± 2.0a |
| LCL | 30.2 ± 1.9a | 20.2 ± 1.3a | 49.6 ± 2.1a |
| p-value | 0.45ns | 0.38ns | 0.03* |
| CV (%) | 12.5 | 11.8 | 15.2 |
Values are mean ± standard error. Means in a column followed by different superscript letters are significantly different (p < 0.05).
ns not significant.
* = significant, ** = highly significant.
PC1 ("soil fertility gradient") was strongly loaded by organic carbon (0.92), total nitrogen (0.89), CEC (0.85), and pH (0.78). PC2 ("soil physical condition") was dominated by bulk density (−0.81) and moisture content (0.76) (Table 5).
Forest land clearly separated from cultivated land along PC1 (fertility axis), with grazing land intermediate. This confirms organic matter and nutrient-related parameters as primary drivers of soil quality differences among land-use types.
Discussion
Soil physical properties degradation
The significantly higher bulk density in cultivated land (0.89 g/cm3) confirms that intensive tillage and livestock-induced compaction degrade soil structure, reducing porosity and water infiltration. This aligns with findings from Dire Dawa, Ethiopia25. A broader review of studies across Ethiopia confirms this trend, showing bulk density is consistently highest in cultivated lands compared to forest and grazing areas26.
In contrast, the lower bulk density in forest land reflects protection from disturbance and higher organic matter promoting aggregation, a benefit also observed in agroforestry systems27. The non-significant difference in sand and silt content suggests parent material homogeneity, while clay redistribution indicates erosion-driven particle sorting, a process also influenced by slope position28.
Nutrient depletion patterns
The marked superiority of forest land across all measured chemical parameters underscores the indispensable role of continuous vegetation cover in preserving and enriching soil fertility. The substantial 48.8% higher organic matter (OM) content in forest soil, compared to cultivated land, aligns closely with findings from similar agro-ecological zones in southern Ethiopia, confirming the severe OM depletion following land-use conversion29. Concurrently, the critically low levels of available phosphorus (P) in cultivated fields, despite common fertilizer application, expose the acute fixation challenges prevalent in these acid soils (pH < 6.0), necessitating targeted and informed P-management strategies as emphasized in broader national assessments26.
The pronounced decline in total nitrogen (TN) and cation exchange capacity (CEC) in both cultivated and grazing lands is a direct indicator of unsustainable nutrient mining without adequate replenishment. While the overall CEC range (13.66–29.57 cmol/kg) suggests a moderate inherent nutrient retention capacity, the significantly depressed values in anthropogenically managed lands reveal a diminished ability to hold essential cations, thereby accelerating nutrient loss. This initiates a well-documented degradation cascade: the loss of organic matter leads directly to a reduction in CEC, which in turn increases the susceptibility of the remaining nutrients to leaching, ultimately threatening the foundational productivity of the land25,30. Addressing this cycle is paramount for any sustainable land management intervention in the Dandi District.
Implications for sustainable land management
These findings demonstrate that land-use conversion in Dandi District has created a downward spiral of soil degradation, with cultivated lands most severely affected. The results provide quantitative evidence for prioritizing conservation interventions in agricultural areas.
The lack of significant slope effects suggests that land-use pressure overrides topographic influences within this elevation range.
Study limitations
This study was limited to the 0-30 cm topsoil layer during a single dry season; temporal variability and subsoil properties were not assessed. The relatively small sample size (27 composites) limits extrapolation to the entire district. Additionally, specific management practices (fertilizer rates, tillage frequency) were not quantified, representing uncontrolled variables.
Conclusion and recommendations
This study provides the first systematic assessment of land-use impacts on soil physicochemical properties in Dandi District, revealing significant degradation in cultivated and grazing lands compared to forest land. Key findings include: Forest land maintains significantly superior soil quality (higher pH, TN, OC, OM, and CEC), confirming its importance as a soil fertility reservoir. Cultivated land suffers the greatest degradation, with the highest bulk density (0.89 g/cm3), lowest TN (0.15%), and severe OM depletion (4.09%), threatening sustained agricultural productivity. Grazing land shows intermediate degradation, with moderate nutrient depletion likely due to vegetation removal and compaction. Land-use type is a stronger driver of soil properties than slope position within the studied elevation gradient.
Controlled grazing
Implement rotational grazing systems with defined stocking rates to reduce compaction and allow vegetation recovery, particularly in middle and lower slopes. Agroforestry Integration: Promote tree planting in cultivated lands (e.g., Faidherbia albida intercropping) to increase OM input and reduce erosion. Targeted Fertilization: Apply phosphorus fertilizers with organic amendments (compost, manure) to mitigate P fixation in acidic cultivated soils. Soil Conservation: Establish contour bunds and grass strips in cultivated fields to reduce clay particle loss and erosion.
Field-specific nutrient management based on soil test results to address identified P deficiencies. Community-based land use planning to regulate conversion of remaining forest fragments. Integrated watershed management addressing both on-site fertility loss and off-site sedimentation.
Future studies should: (1) examine soil properties at multiple depths (0–20, 20–40, 40–60 cm) to assess profile changes; (2) collect seasonal data to capture temporal variability; (3) quantify specific management practices to control for their effects; and (4) expand sampling across multiple kebeles to increase spatial representativeness. Incorporating spectroradiometric techniques (Tiruneh et al., 2022) 39 could enable rapid soil fertility mapping for precision agriculture.
Acknowledgments
We thank Ambo University for laboratory support and the Dandi District Agricultural Office for providing land use data.
Author contributions
D.T. designed the study and collected data; K.F. analyzed data and wrote the first draft; S.M. supervised data collection, performed statistical analysis, and edited the manuscript. All authors read and approved the final version.
Data availability
The datasets generated during this study are available from the corresponding author upon reasonable request.
Declarations
Competing interests
The authors declare no competing interests.
Ethics approval
Ambo University Institutional Research Ethical Committee (AUIREC/0011/12/2020) approved Data collection. Community consent was obtained before sampling.
Consent for publication
All authors have approved the manuscript for publication.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Abad, M., Nakhli, S. A. & Masoudi, S. Effects of land use changes on soil properties and organic carbon content in different soil depths in Northern Iran. CATENA121, 407–414 (2014). [Google Scholar]
- 2.Johnson, J. A., Jayaprakash, A. R., Divya, P., Madhu, M. & Alka, G. Effect of deforestation on soil properties and productivity in Kanker district of Chhattisgarh, India. Int. J. Agric. Sci.15(1), 275–280 (2023). [Google Scholar]
- 3.Wang, J. & Liu, Y. The impact of deforestation on soil properties and productivity in agroecosystems. Environ. Manag.92(4), 994–1003 (2023). [Google Scholar]
- 4.Hurni, H., Tato, K. & Zeleke, G. The impact of soil erosion on crop yield and land productivity in Ethiopia. Land Degrad. Dev.31(5), 579–593 (2020). [Google Scholar]
- 5.Woldearegay, K., Asfaw, Z. & Tadesse, M. Economic impacts of soil erosion in Ethiopia: A case study of on-site and off-site effects. Ethiop. J. Econ.27(1), 89–105 (2018). [Google Scholar]
- 6.Abile, H., Fituma, K. & Mammo, S. Impact of land use types on selected soil physicochemical parameters in the case of Liben Jawi district, Ethiopia. Sci. Rep.15(1), 27944 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Busa, T., Duressa, B., Regasa, T., Bohnett, E. & Mammo, S. Impacts of soil and water conservation structures on selected soil physicochemical parameters in Wali Micro‐Watershed Ambo District, Central Ethiopia. Scientifica2025(1), 1465657 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Muluneh, A. & Arnalds, O. Land use and soil degradation in Ethiopia: An overview. J. Soil Sci. Environ. Manag.12(4), 123–135 (2021). [Google Scholar]
- 9.Tolesa, A., Mammo, S. & Bohnett, E. Effects of soil and water conservation structures on selected soil physicochemical properties: The case of Ejersa Lafo district, central highlands of Ethiopia. Appl. Environ. Soil Sci.2021(1), 9910237 (2021). [Google Scholar]
- 10.Wayesa, G., Kidane, M., Tolessa, T. & Mammo, S. Impacts of land Use/land cover dynamics on ecosystem services in Jimma Rare District, Western Ethiopia. Sustain. Environ.11(1), 2436231 (2025). [Google Scholar]
- 11.Taddese, G. Traditional agricultural practices and soil fertility in Ethiopia. Afr. J. Agric. Res.17(3), 157–169 (2022). [Google Scholar]
- 12.Dandi District Agricultural Office. (2014).
- 13.Bouyoucos, G. J. The hydrometer method has been improved for making particle size analyses of soils. Agron. J.54(5), 464–465 (1962). [Google Scholar]
- 14.Sertsu, T. & Bekele, T. Organic carbon, nitrogen, and phosphorus levels of some Ethiopian soils as related to altitude and land use. Commun. Soil Sci. Plant Anal.31(3–4), 479–495 (2000). [Google Scholar]
- 15.Baruah, T. C. & Barthakur, H. P. A Textbook of Soil Analysis (Vikas Publishing House Pvt, 1997). [Google Scholar]
- 16.Nelson, D. W. & Sommers, L. E. Total carbon, organic carbon, and organic matter. Method. Soil Anal.: Part 2 Chem. Microbiol. Prop.9, 539–579 (1982). [Google Scholar]
- 17.Nelson, D. W. & Sommers, L. E. Total carbon, organic carbon, and organic matter. In Methods of Soil Analysis. Part 2—Chemical and Microbiological Properties (ed. Page, A. L.) 539–579 (Soil Science Society of America, American Society of Agronomy, 1982).
- 18.Bremner, J. M. Nitrogen—total. In: Methods of Soil Analysis. Part 3—Chemical Methods (ed Sparks, D. L.) 1085–1121 Soil Science Society of America; American Society of Agronomy (1996).
- 19.Bremner, J. M. Nitrogen–total. In: Methods of Soil Analysis. Part 3-chemical methods (ed Sparks, D. L.) 1085-1121 (American Society of Agronomy, 1996).
- 20.Olsen, S. R., Cole, C. V., Watanabe, F. S. & Dean, L. A. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate (United States Department of Agriculture, 1954). [Google Scholar]
- 21.Thomas, G. W. Exchangeable cations. Method. Soil Anal. Part 2—Chem. Microbiol. Prop.9, 159–165 (1982). [Google Scholar]
- 22.Rhoades, J. D. Cation exchange capacity. In: Methods of Soil Analysis. Part 2—Chemical and Microbiological Properties (ed Page, A. L.) 149–157 (Soil Science Society of America; American Society of Agronomy, 1982).
- 23.Aytenew, M. & Kibret, K. Land use effects on selected soil physico-chemical properties in three different topographic positions in the Gedeo zone, southern Ethiopia. Cogent Environ. Sci.2(1), 1209294 (2016). [Google Scholar]
- 24.Evrendilek, F., Berberoglu, S., Bolat, I. & Celik, I. Variation in soil organic carbon and total nitrogen with forest conversion to crop and rangelands in North Turkey. Agric. Ecosyst. Environ.103(2), 481–493 (2004). [Google Scholar]
- 25.Getahun, B. & Bobe, B. Effect of land use types on selected soil physical and chemical properties in Dire Dawa, Ethiopia. J. Soil Sci. Environ. Manag.6(5), 90–96 (2015). [Google Scholar]
- 26.Yeshivas, J., Desta, H. & Abebe, G. Soil degradation and its management in Ethiopian highlands: Review. Int. J. Environ. Sci. Natl. Resour.31(2), 1–10 (2022). [Google Scholar]
- 27.Teshome, M. & Ayalew, A. Effect of land use types on selected soil physicochemical properties in Kochore district, Southern Ethiopia. Environ. Syst. Res.12, 24 (2023). [Google Scholar]
- 28.Sisay, D., Mekuriaw, S. & Yibeltal, M. Effects of slope position and land use on soil physicochemical properties in Ageza Watershed, Northwestern Ethiopia. Heliyon9(3), e14352 (2023).37025843 [Google Scholar]
- 29.Tesfaye, M., Woldearegay, K. & Taye, G. Assessment of land use and land cover changes on soil erosion risk in Ethiopia. J. Geogr. Reg. Plan.16(1), 15–25 (2023). [Google Scholar]
- 30.Lemenih, M. & Itanna, F. Soil organic matter depletion and its relationship with soil physical and chemical properties in Ethiopia: A review. East Afr. J. Sci.12(2), 127–142 (2018). [Google Scholar]
- 31.Baruah, T. C. & Bathakur, N. Studies on the chemical properties of soils of Bhagajang Reserve Forest in Assam, India. Indian Forester123(3), 261–267 (1997). [Google Scholar]
- 32.Alene, G. Soil fertility status is affected by different land uses in Horo District, Western Ethiopia. Sky J. Soil Sci. Environ. Manag.8(6), 68–78 (2019). [Google Scholar]
- 33.Kumari, R., Teklu, M. & Berhane, M. Influence of land use change on soil properties in Ethiopia. Afr. J. Environ. Sci. Technol.16(1), 112–125 (2022). [Google Scholar]
- 34.Alemayehu, L. Effects of land use and land cover change on soil quality in the humid agroecological zone of Ethiopia. (Addis Ababa University, Ethiopia, 2010).
- 35.Mesele, S. Effects of land use change on soil properties and soil erosion hazard in the Dano Watershed, Amhara Region, Ethiopia (Bahir Dar University, 2006).
- 36.Solomon, D. Soil organic matter dynamics under various land use systems. In: Proc. 16th Annual Conference of the Ethiopian Society of Soil Science, Addis Ababa, Ethiopia (2002).
- 37.Blake, G.R., & Hartge, K.H. Bulk density. In: Klute, A. (Ed.), Methods of Soil Analysis, Part 1: Physical andMineralogical Methods (2nd ed.). Agronomy Monograph 9. American Society of Agronomy and Soil Science Society of America, Madison, WI, 363–375 (1986).
- 38.Tiruneh, G. A., Meshesha, D. T., Adgo, E., Tsunekawa, A., Haregeweyn, N., Fenta, A. A., Alemayehu, T. Y., Ayana, G.,Reichert, J. M., & Tilahun, K. Geospatial modeling and mapping of soil organic carbon and texture fromspectroradiometric data in Nile basin. Remote Sensing Applications: Society and Environment, 29, 100879.https://doi.org/10.1016/j.rsase.2022.100879 (2023).
- 39.Tiruneh, G. A., Meshesha, D. T., Adgo, E., Tsunekawa, A., Haregeweyn, N., Fenta, A. A., & Reichert, J. M. Exploring crop yield variability under diff erent land management practices with spectral vegetation indices in theEthiopian Blue Nile basin. Geocarto International, 37(27), 15896–15911 (2022).
- 40.Mulualem, T., Adgo, E., Meshesha, D. T., Tsunekawa, A., Haregeweyn, N., Tsubo, M., Berihun, M. L. Examiningsoil nutrient balances and stocks under diff erent land use and management practices in contrasting agro-ecologicalenvironments. Soil Use and Management, 40(1), e13000. https://doi.org/10.1111/sum.13000 (2023).
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated during this study are available from the corresponding author upon reasonable request.