The Impact of Land Use Types on Soil Physicochemical Properties and Agricultural Productivity: a Case of Gojera Kebele, Dinsho District, South Eastern Ethiopia

doi:10.21203/rs.3.rs-3624549/v1

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The Impact of Land Use Types on Soil Physicochemical Properties and Agricultural Productivity: a Case of Gojera Kebele, Dinsho District, South Eastern Ethiopia

https://doi.org/10.21203/rs.3.rs-3624549/v1

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Understanding the effects of different land use types on certain soil Physiochemical properties (PCPs) is essential to the sustainable use of soil resources. Therefore, this study was conducted to evaluate the effects of land use types on selected soil PCPs and Productivity in Dinsho district, Ethiopia. A total of 64 soil samples were collected from forest, farm, grazing, and grasslands at two soil depths (0–20 cm and 20–40 cm) with three replications. The mean differences in the physical and chemical parameters of the soil were investigated using the two-way analysis of variance. The highest mean values of sand and clay were recorded in farm and grassland areas, respectively. The mean bulk density of the soils ranged between 1.14 and 1.37 g/cm^-3, and the mean total porosity ranged from 42.02 to 51.5%, which indicated higher than the desirable range. The SOM ranged from 3.17% to 5.05%, while the mean values of pH ranged from 6.06 to 7.25. However, the mean values of total N ranged from 0.18 to 0.25%. The mean value of available P ranged from 2.03 to 5.2 mg kg¹, which implies a high shortage of available P in the study area. The exchangeable basic cations, CEC, and PBS values were within high to very high ranges in all land use types. Particularly severe overgrazing and improperly land use, including deforestation, have detrimental effects on soil qualities. The productivity of the land and the condition of the soil must therefore be maintained by suitable land use policies and adequate land rebuilding management.

Environmental Chemistry

Soil quality

Land use types

Environmental remediation

Soil physicochemical analysis

Agricultural productivity

Improperly land use has a major impact on the soil PCPs.
Poor land management significantly declined soil properties.
Impact of soil PCPs disability on Sustainable agricultural productivity.

The term "use of land" often refers to the arrangements, activities, and inputs people make in a particular kind of land use to produce, alter, or sustain it (Ufot et al., 2016). Kiflu and Beyene (2013) claim that excessive farming, leaching, and soil erosion can cause soil to rapidly lose both its quality and quantity. Because of this, managing agriculture necessitates a basic comprehension of sustainable use and land preservation (Takele et al., 2014). For effective soil management to preserve the soil's quality throughout time, one must comprehend how the soil responds to agricultural operations (Duguma et al., 2010). But as it promotes higher crop output and is a necessary component of sustainable agriculture, maintaining good soil quality is the cornerstone of sustainable agricultural growth (Liu et al., 2010). Food and fiber production, as well as the improvement of local, regional, and global environmental quality, have benefited greatly from soil resources (Bore and Bedadi, 2015).However, the areas most affected by the growing human population are the regions in central Ethiopia, where there is a high population density and a significant dependency on land resources. This is the horrifying problem of depleting soil resources, which raises concerns about the sustainability of the land and leads to degradation (Yimer and Abdulkadir, 2011). Overgrazing and deforestation, farming on steep terrain, and unpredictable and high rainfall patterns are the main causes of land degradation, the depletion of natural resources, and environmental degradation in Ethiopia (Aytenew and Kibret, 2016).

Additionally, because of the interaction between slope and agricultural practices, the topography of the land has a significant impact on both soil quality and soil depth (Pavlu et al., 2007). Thus, the countries of tropical Africa face significant problems in decreasing resource degradation, raising the productivity of agriculture, decreasing poverty, and achieving food security (Qadir et al., 2014). Therefore, the upkeep of the physical, biological, and socioeconomic should receive all available attention. An economic setting for the sustainable use of natural resources to produce food crops, cattle, wood, and other goods (Adeyemo and Agele, 2010).As the population of both humans and livestock has grown, the rapid expansion of agriculture and grazing areas has started affecting the characteristics of the soil (Mustapha, 2007). This resulted from the growth of land use utilization, which is based on converting forest areas that already exist into pasture and agricultural land (Chemada et al., 2017). In nations like Ethiopia, where the percentage of land covered by forests has dropped from 40% to less than 3% and the population is growing rapidly, the frequent and ongoing exploitation of the available land has persisted even after the limit on intensification was reached (MOFED, 2007).

On the other hand, current research revealed that plantation systems and afforestation are increasing the amount of forest cover by 15% (FAO, 1998). In order to determine how different land use patterns affect the physical and chemical characteristics of Ethiopian soil, a number of research have been carried out (Lemenih et al., 2005; Lemma et al., 2006; Yimer et al., 2008). According to Lemma et al. (2006), the topsoil layer had higher levels of total nitrogen (N), exchangeable potassium (K), and exchangeable calcium (Ca) after cropland was replanted with a variety of specious trees than the subsurface soil layer. When farmland, forest lands, and grazing grounds were evaluated, (Yimer et al., 2008) discovered that total nitrogen and soil organic carbon (OC) decreased in agriculture relative to forest lands. The study area's forest land has currently undergone significant degradation due to the production of firewood, lumber, and the extension of farming and grazing areas. These factors could affect agricultural productivity and cause soil fertility to diminish, both of which have an impact on the livelihood of the surrounding communities. In the research area, the grassland has also been transformed into grazing lands. This is due to the increase of livestock which removes palatable bushes and bush trees and causes soil compaction. This also exposes the upper layer of soil to erosion concerns. In order to put the proper recommendations for sustainable utilizations of soil resources and improve crop productivity, the information about effects of land use types on soil physical and chemical properties are essential. Therefore, the objective of this study was to evaluate effects of land use types on selected soil physical and chemical properties and agricultural productivity on Gojjera kebele, Dinsho district.

2.1. Description of the study area

Gojera Kebele, Dinsho District, Southeast Bale Zone, Oromia National Regional State, Ethiopia was the study's location. It is 400 kilometers away from Addis Ababa. Its geographic coordinates are around 39°38′0''E longitude and 6°53′30''N latitude, with an altitudinal range of 2532 to 4047 meters above sea level (masl) (DWAO, 2022).

2.2 Climate of study area

According to statistics on temperature and rainfall obtained from the Bale Robe meteorological station, the subject of study area experiences annual rainfall of up to 1060–1150 mm during some peak years, and the mean monthly maximum temperature is 15°C, while its mean monthly lowest temperature is 12.5°C. There is little variation in the average annual temperature of 12.5°C from year to year. The seasonal distribution of rainfall shows that it is least in December and February, peaks in July then declines in November and December (DWAO, 2022).

2.3 Soils, vegetation and topography

Verti soils are the most common type of soil in the research area. "Biyyee Gurraacha" is the local term for it, and it refers to the predominantly clayey black soil. The three main agroclimatic zones of high land, semi-high land, and low land define the topography of the Woreda. The district's variety of vegetation is typified by trees, shrubs, and scrubs. (DWAO, 2022) reports that there is a shortage of natural forest in the study area across several land use categories. Deforestation has been a major problem in the study area, as it is in the majority of Ethiopia. To produce lumber, firewood, and building materials, and to develop cultivated areas, vegetation has been cleared. As a result, the fertile soils have been gone and the wild creatures have been endangered.

2.4 Farming system (Agriculture)

A mixed farming system is used in the study area to produce livestock and plant a range of crops in an effort to improve the standard of living and income of the residents. In the region, mixed farming is a common practice that mostly entails cultivating crops and rearing animals. In addition to the pulse crops field pea, house bean, chickpea, and lentil, the main crops grown are wheat, barley, maize, and sorghum. One of the main ways that residents in the study area support their families is by rearing livestock. Dinsho district's livestock population is diverse, including horses, donkeys, sheep, goats, chickens, and beekeepers for honey production (DWAO, 2022).

2.5 Site Selection

For this study, Gojera kebele was purposively selected from Dinsho district because higher land degradation and soil erosion problems are commonly observed in this area which has harmful impact on soil physical and chemical properties under different land use types. Prior to the collection of soil samples, discussions was made with the woreda agricultural office expertise in order to get the prehistory and current information about the utilization of land use types and lifestyle of the local community in the study area. Throughout the visual observation of the study area its geographic coordination (latitudes and longitudes) and elevation were recorded by global positioning system (GPS). Then after, for addressing the intended objective, the treatments were stratified in to four land use types viz: farm, grazing, forest and grasslands.

2.6 Soil Sampling

Three replications for every of the four land use types—farm, grazing, forest, and grasslands—soil samples were taken at two different soil depths: 0–20 cm and 20–40 cm. Every component was positioned on different geological, slope, and topographic factors. and slope features. Undistributed soil samples were collected using a core sampler to determine the bulk density of the soil, whereas disturbed soil samples were collected using an auger to determine the specific physical and chemical properties of the soil. Dead plants, old manures, areas close to trees, and compost pits were excluded from the soil sample collection in order to reduce any differences that might arise from the dilution of soil organic matter as a result of cultivation and other causes.

Then, the samples were taken from five points of the plot by measuring 100m x 20m,150mx30,180mx30, and 170mx25 for forest, farm, grass and grazing respectively, quadrant one at the center and other four at the corners of the quadrants. These collected samples were mixed to form a composite in order to reduce variability with in the quadrants. Therefore, composite sample methods were used for soil collection in order to obtain an accurate estimate of the population mean, reduce cost and analytical time, and achieve these goals (Jackson 1958). A total of 32 soil samples with a replication of three were taken from the selected four land use type’s site. In addition, a total of 32 soil core samples were also collected for soil bulk density (BD) analysis for each of the land use types. Lastly, the collected soil samples were combined, labeled, mixed, and packaged thoroughly in plastic bags and 500g of soil sample of each type of soil depth and land use was obtained for analysis.

For physicochemical investigation, the soil samples were passed through a 2 mm filter (sieve) after being air dried. However, in order to analyze specific soil physical and chemical features, the analyses of organic carbon (OC) and total nitrogen (N) were first ground to pass a 0.5 mm size screen.

2.7 Analysis of soil physical and chemical properties

Soil texture was analyzed by the Bouyoucous hydrometer method (Bouyoucous, 1962), after OM was destroyed or burned by using hydrogen peroxide (H₂O₂), soil particles dispersed and disintegrated by sodium carbonate (Na₂CO₃) and sodium hexametaphosphate (NaPO₃) in distilled water and finally using amyl alcohol to destroy the soil solution foam. After the particle size distributions were determined in percent, the textural class of the soil could obtained by using USDA soil textural triangle classification system (USDA, 2008).

The bulk density (BD) of the soil was measured from undisturbed soil samples collected using a core sampler after drying the core samples in an oven at 105°C (Black, 1965). The total porosity of soil samples was estimated from the values of bulk density (BD) and particle density (PD) (assuming an average particle density of mineral soil is 2.65 g cm-3). Then the total porosity (TP) was calculated as, TP (%) = (1-Bulk density/Particle density) * (100).

The pH of the soils was measured in water (H₂O) suspension in a 1:2.5 (soil: liquid) by pH meter, whereas electrical conductivity was measured by a conductivity meter (Van Reeuwijk, 1992). Calcium carbonate content of the soil was determined by an acid neutralization method in, which the soil carbonate was neutralize by standard 0.1M HCl solution and back titrated with standard NaOH (Van Reeuwijk, 1992).

To determine organic carbon, the Walkley and Black (1934) method was used in which the carbon was oxidized under standard conditions with potassium dichromate (K₂Cr₂O₇) in sulfuric acid solution. Finally, the organic matter content of the soil was calculated by multiplying the organic carbon percentage by 1.724 following the assumptions that OM is composed of 58% carbon. The total nitrogen content in soils was determined using the Kjeldahl digestion, distillation and titration method by oxidizing the OM in concentrated sulfuric acid solution (0.1 N H₂SO₄) as described by Black (1965). Then after, C:N was calculated by dividing organic carbon to total nitrogen. The available P was calculated by the Olsen method using sodium bicarbonate (0.5 M NaHCO₃) as an extraction solution (Olsen et al., 1954).

Exchangeable bases (Na, K, and Ca) were determined after extracting the soil samples by ammonium acetate (1N NH₄OAc) at pH 7.0. Exchangeable Na, K and Ca were analyzed by flame photometer described by Rowell (1994). Cation exchange capacity was estimated titrimetrically by distillation of ammonium that could be displaced by sodium from NaCl solution (Chapman, 1965). Percent base saturation was calculated by dividing the sum of the charge equivalents of the base forming cations (Na, K, and Ca) by the CEC of the soil and multiplying by 100.

2.8 Statistical data Analysis

To evaluate for variations in soil physical and chemical parameters between land use types and soil depths, a two-way analysis of variance (ANOVA) was employed. The treatment means were analyzed and the means for statistically different parameters were separated using the least significant difference (LSD) at 0.05 levels of significance (For K. A. Gomez and A. A. 1984). The data analysis was conducted using the SPSS software (version 20.0) software.

3.1. Selected soil physical properties under different land use types

3.1.1. Soil texture

The results of the analysis of variance (ANOVA) revealed that neither the interactions between the land use categories, the different soil depths, nor the sand particle size varied significantly. However, Table 1 shows that the types of land use had a significant (P < 0.05) effect on silt and clay particles. There was a numerical variance in the distribution of soils and particles among land use types, despite the fact that there was no statistically significant difference.

The surface soil layers of farm and forest lands showed the highest and lowest levels of sand (36.3%) and (23.5%), respectively, as a result of the interaction between soil depth and land use types. The soil layer under the surface (20–40 cm) in both the farm and forest land had the highest percentage of clay (52.2%) and lowest percentage (38.6%), respectively (Table 1). Regarding soil depth, the top soil layer (0–20 cm) had the highest sand content, while the subsurface (20–40 cm) soil layer had the highest silt and clay content (Table 2). Typically speaking, the subsurface layer of farm land had more clay than the nearby grass, forest, and grazing grounds. The cause may be related to clay migration, which is the preferential removal of clay particles and their downward migration into the subsurface soil layer.

Similarly, Chemada et al. (2017) reported that the longer farming seasons caused the clay content of cultivated land to increase from the top soil layer to the bottom soil layer. Gebrelibanos and Assen (2013) additionally noticed that agricultural land had higher clay content in the subsurface layer and lower clay content in the surface layer relative to the other neighboring natural forests, plantation forests, and grazing areas. According to Abbasi et al. (2007), the variations in soil texture between land use types generally suggest that different land use types' use and management practices are what cause their effects on soil properties.

Table 1: Interaction effects of land use types and soil depth on selected soil physical properties on Gojjera Kebele

	Sand (%)		Silt (%)		Clay (%)		BD gm./ cm^-3		TP (%)
	Soil depth(cm)		Soil depth (cm)		Soil depth (cm)		Soil depth		Soil depth(cm)
Land use types	0-20	20-40	0-20	20-40	0-20	20-40	0-20	20-40	0-20	20-40
Forest land	23.5	27.35	33.8	39.5^m	47.0	38.6ⁿ	1.23^b	1.26^d	45.42^b	46.54ⁿ
Farm land	36.3	28.35	24.7	23.8ⁿ	40.1	52.2ⁿ	1.39ⁿ	1.35^m	51.45^a	50.94^a
Grazing land	28.5	26.1	29.7	31.6^mn	42.7	43.5^mn	1.37ⁿ	1.34ⁿ	50.97^c	49.57^a
Grass land	26.0	24.7	27.0	26.0ⁿ	50.0	51.3ⁿ	1.08^m	1.20^a	39.75^a	44.28^b
Mean	28.58	26.63	28.8	30.2	44.95	46.3	1.27	1.29	46.90	47.83
SD	5.55	4.86	5.92	4.84	7.7	5.76	0.0073	0.0085	0.29	0.28
CV (%)	19.3	18.25	20.6	16.0	17.1	12.45	0.578	0.65	0.605	0.58
P-Values	ns	Ns	Ns	*	ns	*	***	***	***	***

Relations means with in a columns followed by the different letter or letters are significantly different from each other at P ≤ 0.05; *= significant at P ≤ 0.05; *** = significant at P ≤ 0.001; BD = Bulk density; TP = Total porosity; CV= coefficient of variations; ns= not Significant.

Table 2: Main effect of land use types and soil depth on selected physical properties of soil on study area

Main effect means within a columns followed by the different letter(s) are significantly different from each other at P ≤ 0.05; ns=not significant * = significant at P ≤ 0.05; ** = significant at P ≤ 0.01; *** = significant at P ≤ 0.001.

3.1.2. Bulk density

Land use and their interactions had a significant (P ≤ 0.001) impact on the soil bulk density value, whereas soil depth had a significant (P ≤ 0.01) impact (Tables 2 and Table 3). After analyzing the primary effects, farmland had the highest mean bulk density (1.37 gcm^-3) and grassland had the lowest (1.14 g cm^-3) mean values (Table 2). The higher clay content and less disturbance of the soil under grassland may be the cause of the grassland's lowest soil bulk density.

The higher bulk density of soil in farm land might be due to the practice of ploughing in farm soil, which tends to lower the quantity of OM of that soil through animal operating and expose the soil surface to direct strike by rain drops. High bulk density is an indicator of low soil porosity which may cause poor movement of air and water through the soil.

For mineral agricultural soils, a bulk density of 1.3 to 1.4gcm^-3 is adequate (Bohn et al., 2001). The study's average soil bulk density was within this range. The variations in clay concentration, organic matter, and total porosity could be the cause of the variety in land use types. As a result of the higher pore rates associated with high OM and clay, land use types with high clay and organic matter contents have lower bulk densities than those with low OM and clay contents. One of the key physical factors considered when assessing the physical fertility of soils is bulk density.

3.1.3. Total porosity

The results of the analysis of variance (ANOVA) showed that the relationships between different land use types and the total porosity of the soil were significantly (P ≤ 0.001) impacted. Yet, at (P≤0.01), the depth of the soil had a significant influence (Table 1 and Table 2). Considering the interaction of land use types with soil depth, the highest (51.45%) and
the lowest (47.6%) values of total porosity was recorded on the surface soil layer of farm and grass lands, respectively (Table 1).

The higher value of soil total porosity in farm land was implied that the high bulk density of grass land in the area. The mean total porosity of forest, farm, grazing, and grass areas was 45.98, 51.20, 50.27, and 42.02%, respectively, in terms of the mean values under various land use types (Table 2). The subsurface soil layer had the larger total porosity value in the case of the two soil depths.

Total porosity across adjacent land use categories was higher and lower, which corresponded to lower and higher bulk density values for that soil. Contrarily, according to FAO (2006c), which classified total porosity values as very low (2%), low (>5%), medium (>5%), high (15–40%), and very high (>40%), the percent of total porosity of all land use groups was very high. Each land use type's total porosity in my study's results is higher than the desirable range (Table 2).

3.2. Specific Soil chemical characteristics in relation to various land use types

3.2.1. Calcium carbonate, pH, and Electrical Conductivity

The results of the analysis of variance demonstrated that land use categories, soil depth, and their interactions significantly (P≤0.01) affected soil pH. Under the forest land and the farm land, respectively, the greatest mean value (7.1) and the lowest (5.82) soil pH values were found (Table 3).

Low levels of soil management, including serious overgrazing, continuous cropping, soil erosion, soil deterioration, and poor soil management, may be to blame for the low soil pH values. The subsurface (20–40 cm) soil layers of forest and agriculture fields, respectively, presented the greatest (7.1) and lowest (5.82) values of soil reaction (Table 3). The subsurface soil layer's greater pH value compared to the top soil layer was confirmed.

Table 3: Relations effects of land use types and soil depth on soil, EC, pH and CaCO₃ on study area

Land use system	P^H		EC (S/m)		CaCO₃ (ppm)
	Soil depth(cm)		Soil depth(cm)		Soil depth(cm)
	0-20	20-40	0-20	20-40	0-20	20-40
Forest land	7.1^a	7.2^m	0.59ⁿ	0.47^b	10.8^a	9.09^m
Farm land	5.82^b	6.3^ab	0.34^m	0.35^ac	6.5^c	7.1^a
Grazing land	6.8^c	7.0ⁿ	0.32^m	0.36^ac	5.2^d	5.65^c
Grass land	6.9^d	7.1^m	0.31^m	0.35^c	7.82^b	9.1^m
Mean	6.7	6.9	0.39	0.28	7.56	7.74
St. Deviation	0.28	0.30	0.08	0.07	0.40	0.33
CV (%)	4.2	4.4	20.50	25.0	5.3	4.3
P Values	**	*	**	*	***	***

Relations means within a columns followed by the different letters are significantly different from each other at P ≤ 0.05; ** = significant at P ≤ 0.01; *** = significant at P ≤ 0.001; * = significant at P≤0.05; EC=Electrical conductivity; CaCO₃=Calcium Carbonate; ns=not significant.

In comparison to the other proximate land use types, farmland had the lowest mean value of soil reaction. This might be brought on by crop collecting's lowering of basic cations. Similar findings were made by (Bore and Bedadi, 2015) who discovered that farmland experiences less soil reactivity than the nearby grazing and grass land areas.

The findings of (Takele et al. 2014), who suggested that the soil reaction was lower under farm land compared to forest and grazing fields at a soil depth of 0-20 cm and 20-40 cm, are also supported by the findings of my current investigation. According to Tekalign (1991) classification of soil pH, the research area's grass and forest lands were rated as having a relatively alkaline pH, whereas the agricultural and grazing fields had a pH that was closer to slightly alkaline. The presence of less calcareous soil, which is distinguished by high calcium carbonate (CaCO₃) compound contents, which utilized the exchangeable compound site, was demonstrated by the study area's low pH values of the soil.

Land use types significantly (P ≤ 0.01) changed the electrical conductivity (EC) values of soils, although soil depths and their interaction had no significant impact (Tables 3 and Table 5). The maximum (0.59 S/m) and lowest (0.31 S/m) EC of the soils were gained in the forest and the grasslands, respectively, when the primary influences of land use types were taken into account (Table 3). Due to the grassland's low bulk density and increased total porosity, the lowest EC value under it may have been caused by the loss of base-forming cations due to high water separation.

Also, this conclusion is consistent with findings from (Mesele et al., 2006), who discovered that grassland has poorer electrical conductivity than nearby croplands, bush lands, and bushed-grasslands at soil depths between 0 and 20 cm. Except in forest land, where it declined from surface (0.59 S/m) to subsurface layer, the EC of soil increased with depth, that is, from the surface (0-20 cm) layer to the subsurface (20-40 cm) layer (0.47 S/m).

Land use types and their interactions with soil depths had a significant (P≤ 0.001) impact on soil calcium carbonate (CaCO₃), while soil depths had no significant (P ≤ 0.001) impact (Tables 3 and Table 5). The surface (0–20 cm) soil layer of forest and grazing, respectively, had the greatest (10.8 ppm) and lowest (5.2 ppm) CaCO₃ values when the interaction of land use types with soil depths was taken into account.

In accordance with (Landon, 1991) categorization, soil is considered calcareous when its CaCO₃ level is 0.5% or above and no calcareous when it is less than 0.5%. According to this classification, my results were distinguished by high CaCO₃ content across all land use classes, which suggests that calcareous soil is present in the research area. This leads to phosphorus precipitation in the form of Ca-phosphate, which in turn reduces the amount of P that is available in the soil.

3.2.2. Soil organic matter

The findings of the analysis of variance revealed that the types of land use, soil depth, and how those two factors interacted with one another significantly (P ≤ 0.001) affected the soil OM contents (Tables 4 and Table 5).

Overgrazing and the dense soil that animals walk over may be to blame for the low OM content of the soil in grazing areas. This might block the buildup of soil OM at both the surface and under soil layers. Farmland has a relatively greater soil OM at the surface and deeper soil layer than grazing areas. This may be because farming land contains huge, lengthy roots of crops, whereas grazing land has fine, short roots, which can greatly contribute to the improvement of OM and soil microbial function (Gebrelibanos and Assen, 2013).

Table 4: Interaction effects of land use and soil depth on total TN, SOC, SOM, and C: N and Av.P of the soils on study area

	TN (%)		TOC (%)		SOM (%)		C: N (%)		Av. P (%)
	Soil depth (cm)		Soil depth (cm)		Soil depth (cm)		Soil depth (cm)		Soil depth (cm)
Land use system	0-20	20-40	0-20	20-40	0-20	20-40	0-20	20-40	0-20	20-40
Forest land	0.27^ab	0.22^mn	3.21^c	2.70^a	5.7^mn	4.40	11.85	10.80^d	6.80b	3.60^a
Farm land	0.21^b	0.20^mn	2.35^b	1.90^b	3.7^m	3.30	11.75	10.65^c	4.75^c	3.05^mn
Grazing land	0.20^c	0.16^a	2.19^d	1.65^c	3.6^m	2.74	10.5	10.30^b	2.74^a	1.83^m
Grass land	0.25^b	0.20^b	2.87^a	2.19^d	4.6ⁿ	3.60	11.5	10.95^c	3.32^d	2.08ⁿ
Mean	0.23	0.20	2.67	2.11	4.4	3.51	11.52	10.51	3.44	1.94
St. Deviation	0.03	0.02	0.14	0.27	0.24	0.47	0.96	0.91	0.72	0.20
CV (%)	13.0	10	5.24	12.80	5.5	13.39	8.33	8.66	20.9	10.3
P Values	***	**	**	*	***	*	*	Ns	***	*

Interaction means within a columns followed by the different letters are significantly different from each other at P ≤ 0.05;TOC- total organic carbon, TN- total nitrogen, SOM-soil organic matter, C: N- Carbon to nitrogen ratio, Av. P -available phosphorous; * = significant at P ≤ 0.05; *** = significant at P ≤ 0.001; ** = significant at P ≤ 0.01; ns = not significant.

On the other hand, the maximum value of soil OM was accepted to the excess biomass and plant remnants on the surface layer of forest land. The soil OM of the research area declined as soil depth rose, i.e., from the surface soil layer (0–20 cm) to the subsurface soil layer (20–40 cm) (Table 4).

This showed that there was enough soil OM in the top soil layer, which contains both plant and animal remnants, to support a wide variety of soil organisms. In the processes of mineralization, this ingredient goes a long way. As a consequence, the analysis of variance findings support the finding that, with respect to the soil depth of the research area, the soil OM value was greater (4.4%) on the top soil layer than that of the subsurface (3.5%) soil layer (Table 5).

This result is consistent with the findings of other researchers, including (Chibsa and Ta'a ,2009) Duguma et al. (2010) and Takele et al. (2014) who reported that soil organic matter (OM) decreases with increasing soil depth, with higher addition on the upper surface soil layer

3.2.3. Soil organic carbon (SOC)

This result is consistent with the findings of other researchers, such as Chibsa and Ta'a ,2009), Duguma et al. (2010), and Takele et al. (2014) who reported that soil organic matter (OM) decreases with increasing soil depth, with higher addition on the upper surface soil layer.

With significantly higher mean values (3.0%) under forest land and lower mean values (1.92%) under intensively grazing land, the soil organic carbon content was significantly (P ≤ 0.001) influenced by the kind of land used (Table 5). The significant variance can be explained by intensive land usage, which accelerates the oxidation of organic matter and complete clearance of harvest waste for use as animal feed and a source of domestic energy (Elias, 2016).

3.2.4. Total nitrogen (TN)

The different land use categories had a significant (P≤ 0.001) impact on the total nitrogen (TN) level of soils. On the other hand, soil depth had a significant impact at (P≤ 0.01) and the interactions between land use and soil depth had a significant impact at (P≤ 0.05) (Tables 5 and Table 6). As one moves from grazing, farm, grass, and forest lands, the nitrogen content of the soils is typically in the low to medium range and follows the pattern of the organic matter levels.

This conclusion is consistent with those in (Yadda, 2007), which revealed that continuous and intense cultivation accelerated the oxidation of OC and reduced TN. However, the total nitrogen content was higher (0.27) on forest land and lower (0.20) on grazing land. The variations of total N content among different land use types are similar with that of OM content, which is decreasing while soil depth was increased (Table 5).

While the low total N content in grazing land may be caused by the use of animal dung as fuel in homes rather than leaving it in the field, the greater total nitrogen content in soils of forest land may be related to the high OM levels of the soils. Additionally, the removal of vegetation by livestock grazing and exposing the top layer of grazing land to raindrops directly may be generating more surface overflow, which may remove the remains of the animals and plants from the top soil layer and result in a reduction in the amount of nitrogen in the soil overall.

In forest and grazing with a thick layer of natural flora, it returns frequently to the soil, increasing the SOM concentration and, as a result, the overall nitrogen content of these soils. Tekalign, 1991) gave the grassland and forest areas a high rating while giving the total N in the study area's grazing and cultivated lands a middling grade.

3.2.5. Carbon to Nitrogen ratio (C: N)

The analysis of variance revealed that the various land use patterns had a significant (P≤ 0.05) impact on the carbon to nitrogen ratio (C:N) of the soils in the studied area. However, neither the effects of the interactions nor the depth of the soil had a significant effect (Tables 5 and Table 6). When the principal effects of soil depth were taken into consideration, the mean C:N value for the surface (0–20 cm) soil layer was greater (10.5).

This shows that total N fell with soil depth at a rate that was significantly larger than the pace at which carbon decreased. In particular, the soil's C:N ratio is dropping as soil depth rises. It only very rarely increases with the addition of soil depth, which may be because the deposited soil has a higher C:N ratio in the subsurface soil layer than the surface soil layer as a result of sedimentation processes. The optimal C/N ratios, which offer more nitrogen than is required by microorganisms, are between 10:1 and 12:1 (Negassa, 2001).

The findings of this investigation, however, showed that the C:N ratio declined as soil depth increased. The surface soil layers of the forest and grazing fields, respectively, recorded the greatest (11.85) and lowest (10.5) C:N values when taking interaction effects into account (Table 2). While the lower C:N in the surface soil of grazing and farm lands may be caused by higher microbial activity and more CO₂ growth and its loss to the atmosphere at the surface (0-20 cm) soil layer than in the subsurface (20-40 cm) soil layer, the higher C:N in forest soil indicates the occurrence of optimal biological activities.

The current finding is consistent with findings made by (Gebrelibanos and Assen, 2013) who discovered that forest area has a greater C:N ratio than nearby plantation, grazing, and farmlands. He added that the ideal C:N ratio is between 10:1 and 12:1, which offers nitrogen for extra microbial activity. As a result, it was determined that the C:N of the soil in all land use types within the research area was within the ideal range. This suggests that there are suitable systems in place for soil organisms to mineralize.

Table 5: Main effect of land use types and soil depth on selected chemical properties of soil in the study area

Main effect means within a columns followed by the different letters are significantly different from each other at P ≤ 0.05; **= significant at P ≤ 0.01; ***= significant at P ≤ 0.001; *= significant at P ≤ 0.05; ns=not significant.

The findings of the analysis of variance showed that the different land use types had a significant (P ≤ 0.05) impact on the carbon to nitrogen ratio (C:N) of the soils in the study area. Yet, neither soil depth nor the impacts of the interactions had a significant impact (Table 5 and Table 6). Given the primary influences of soil depth, the surface (0–20 cm) soil layer had the highest (10.7) mean value of C:N.

3.2.6. Available Phosphorus

According to the results of the analysis of variance, the study area's available P was considerably (P ≤ 0.001) influenced by the different types of land uses, the depth of the soil, and how those two factors interacted (Tables 5 and Table 6 ). In comparison to the underlying soil layer, the accessible P was greater in the surface soil layer (Table 6). Broadly speaking, differences in the amount of accessible P in soils may be linked to the rate of soil weathering or disturbance under various land use types. The forest area had the highest accessible P concentration (5.2 mg kg^-1) and the grazing land had the lowest (2.30 mgkg^-1) when looking at the primary consequences of different land use types (Table 6).

The maximum (6.80 mg kg^-1) and lowest (2.74 mg kg^-1) available P concentrations were observed at the surface soil layer of the forest and subsurface soil layer of the grazing areas, respectively, due to the interaction effect of land use types with soil depth (Table 5). Unlike previous studies by (Aytenew and Kibret ,2016) and (Chemada et al.,2017),which revealed that agriculture had higher levels of available phosphorus than the nearby grazing and forest lands, this study found that forest land had higher levels of available P at both the surface and deeper soil layers.

Reasonably, the high level of accessible phosphorus in the forest land may be caused by the high level of soil organic matter (OM), which causes the release of organic phosphorus and therefore raises the level of phosphorus under the forest land. The findings of (Abad et al., 2014) who indicated that the available phosphorus was higher in forest land than in grassland land and farm land at (0–30) cm soil depth are also in agreement with this conclusion.

The Gojjera kebele farmland adjacent to the forest land had a larger amount of available phosphorous, similar to the other land use types there. This might be because the farmlands in the research area employ fertilizers like nitrogen, phosphorous, and sulfur (NPS) and di ammonium phosphate (DAP).

Although the available phosphorus can precipitate in the form of calcium phosphate in calcareous soil, the lack of available phosphorus on the study area is generally assumed to be caused by the high CaCO₃ content of the soil. This outcome is also consistent with that of (Melese et al., 2015) who found that the precipitation of calcium phosphate reduced the amount of accessible phosphorus in calcareous soil.

3.2.7. Cation exchange capacity

The findings of the analysis of variance showed that the different types of land use had a significant (P ≤ 0.05) impact on the cation exchange capacity (CEC) of the soils in the study area. The CEC means values for forest, farm, grazing and grass lands, and were 42.50, 28.74, 34.85, and 38.53 cmolc kg^-1, respectively (Table 8).The higher and lower of CEC in forest and farm land might be due to the presence and absence of soil organic matter or high soil organic matter in forest land but it was less in grazing land. In addition, the quantity and nature of clay particles affect soil CEC depending on the type of land use

Table 6: Interaction effects of land use types and soil depth on Na, K, Ca, CEC and PBS in the study area

Na⁺ K⁺ Ca²⁺ CEC PBS
	c molc kg^-1 %
	Soil depth(cm)		Soil depth(cm)		Soil depth(cm)		Soil depth(cm)		Soil depth(cm)
Land use systems	0-20	20-40	0-20	20-40	0-20	20-40	0-20	20-40	0-20	20-40
Forest land	0.45	0.49	1.62^c	1.3	26.5^b	22.3^a	44.50	40.42^b	67.23^b	78.5^c
Farm land	0.43	0.47	0.74^a	0.85	17.8^c	21.8^ab	34.5	35.20^a	59.0^d	78.6^c
Grazing land	0.43	0.44	0.45^b	0.49	16.2^c	17.4^c	28.12	29.35^c	55.14^c	74.72^a
Grass land	0.44	0.47	0.65^a	0.69	24.3^a	25.70^b	37.43	39.62^b	64.8^b	80.2^c
Mean	0.44	0.47	0.87	0.83	21.2	21.8	36.14	36.08	61.54	78.01
St. deviation	0.08	0.07	0.19	0.11	0.74	1.17	1.28	2.4	1.07	2.3
CV (%)	18.2	14.89	21.80	13.25	3.49	5.37	3.54	6.65	1.7	2.95
P values	Ns	Ns	**	ns	***	*	***	**	***	*

Relations means within a columns followed by the different are significantly different from each other at P ≤ 0.05; * = significant at P ≤ 0.05; *** = significant at P ≤ 0.001; * = significant at P≤0.01; ns=not significant.

The findings of (Yitbarek et al., 2013), who put forward that the CEC of soil was higher in forest land compared to that of the nearby grazing and farm lands, are supported by this result. The effects of the interactions between the land use categories and the soil depth on the CEC of the soil under the research area were significant (P ≤ 0.05) (Table 6). The surface soil layer (0–20 cm) of forest land had the highest amount of CEC (44.40 cmolc kg^–1), whereas the grazing field's surface soil layer had the lowest value (28.12 cmolc kg^–1).

Considering the soil depth, like that of the interaction of land use types with soil depth, the CEC values of the soil under different land use types were not significantly affected by soil depth. But statistically, the higher CEC value was found in the surface (0-20 cm) soil layer (Table 6). Therefore,( Kiflu and Beyene , 2013) discovered that soil depth at depths of 0-15 cm and 15-30 cm did not significantly affect the soil's CEC under neighboring maize, enset, and grasslands.

Additionally, (Nigussie and Kissi, 2012) indicated that the underlying soil layer under the nearby forest, farmland, and grazing fields had a greater CEC of soil. According to the CEC ratings (Hazelton and Murphy, 2007) suggested, the soil under grass, farm, and grazing land had a high rating, whereas the soil under forest land had a very high rating.

3.2.8. Exchangeable bases

The findings of the analysis of variance revealed that land use types, soil depths, and the interaction between land use types and soil depth all significantly (P ≤ 0.001) impacted the exchangeable Ca (Tables 6 and Table 7 ). Such a large range in exchangeable Ca could result from various management techniques, methods for using the land, and various imbalances related to OM and soil texture. The mean values of exchangeable Ca among forest, farm, grazing, and grass areas were 24.4, 19.8, 16.8, and 25.0 cmolc kg^-1, respectively, considering the primary effect of land use categories (Table 7).

Table 7: Main effects of land use types and soil depth on selected chemical properties of soil in the study area

Main effect means within a columns followed by the different letters are significantly different fromeachotheratP≤0.05; ns=not significant; * = significant at P ≤ 0.05; ** = significant at P ≤ 0.01; *** = significant at P ≤ 0.001.

When comparing the exchangeable Ca at the two soil depths, the surface soil depth had a higher exchangeable Ca than the subsurface soil depth (Table 7). There may be an opportunity because there was more richness in animal and plant remains on the surface of the soil layer than under due to the high exchangeable Ca that was present. Similar findings were made by (Kiflu and Beyene ,2013) who found that biological accumulation from plant residues and biological activity was correlated with higher soil exchangeable Ca levels in the surface soil layer than the subsurface soil layer.

In terms of how different land use types interact with soil depth, the surface soil layers of grazing lands and forests, respectively, had the highest exchangeable Ca concentrations (26.5 cmolc kg^-1) and the lowest (16.2 cmolc kg^-1) (Table 6). According to (FAO, 2006) the soil in the research area had exchangeable Ca concentrations that were rated as high under farm and grazing areas and very high under grass and forest lands. Consequently, from this point, it can be seen that the study area was distinguished by high exchangeable Ca content.

The different land use types had a significant (P ≤ 0.001) impact on the exchangeable K of the soil in the study area. Yet, neither soil depths nor the relationship between different land use types and soil depth had a significant impact on it (Table 6 and Table 7). The mean exchangeable K values for forest, farm, grazing and grass fields were 1.46, 0.80, 0.47, and 0.67 cmolckg^-1, respectively, when considering the major effect of land use categories (Table 7). Given the research area's soil depths, the surface (0–20 cm) soil layer contained the highest exchangeable K levels (Table 7).

On the surface soil layer of forest and grazing lands, respectively, the highest (1.62 cmolc kg^-1) and lowest (0.45 cmolc kg^-1) values of exchangeable K contents were recorded (Table 7). The availability of surface biomass through litter fall and little to no surface soil disturbance by rain drops, surface runoff, and other severe erosion agents may be the causes of the increased exchangeable K on the surface layer of forest land. In the case of grazing land's surface layer, the derivative of this phenomenon is the cause of lower exchangeable K, which is made worse by higher disorder.

The findings of (Yitbarek et al. 2013) and (Duguma et al. 2014), which found that the exchangeable K of soil is higher in the forest land than in farm and grazing lands, are consistent with this result. The exchangeable K contents of the research area's grass and farmlands were classified as high, while those of the grazing and forest areas were evaluated as medium and very high, respectively, by the rate of exchangeable K stated by ( FAO ,2006).

The findings of the analysis of variance showed that the land use types, soil depth, and interactions between the two had no discernible effects on the exchangeable Na of the studied region (Table 6 and Table 7). This conclusion is consistent with that of (Gebrelibanos and Assen, 2013) who said that the exchangeable Na did not show any considerable variation under neighboring diverse land use types or across the soil depth by the time the exchangeable Ca and K, did.

The findings of the analysis of variance showed that the land use types, soil depth, and interactions between the two had a negligible impact on the exchangeable Na of the studied area (Table 6 and Table 7). This conclusion is consistent with that of (Gebrelibanos and Assen,2013), who said that the exchangeable Na did not show any considerable variation under neighboring diverse land use types or across the soil depth by the time the exchangeable Ca and K did.

According to the research area's average values for exchangeable Na, forest, farm, grazing, and grasslands, respectively, had values of 0.46, 0.45, 0.43, and 0.44 cmolckg^-1. The surface soil layer (0–20 cm) showed higher exchangeable Na levels than the deep soil layer (20–40 cm) (Table 7). The maximum exchangeable Na concentration (0.49 cmol kg^-1) was found under the subsurface soil layer of forest land, whereas the lowest concentration (0.43 cmol ckg^-1) was found on the surface soil layer of both farm and grazing lands (Table 6).

The increased exchangeable Na in forest land may be caused by the availability and buildup of plant residues brought on by the abscission of leaf trees and biological processes, though there was no statistical variance in its values. The clearance of crop residues through harvesting activities was responsible for the lower exchangeable Na in agricultural and grazing fields, but livestock grazing may have reduced the lower exchangeable Na on grazing land.

This result is also connected to that of (Chemada et al. 2017), who discovered that agriculture and grazing grounds have lower exchangeable Na than the nearby forest land. The exchangeable Na of the research area, according to a grading by (FAO, 2006), was in the range of a medium rate under all land use patterns.

3.2.8.1. Percent base saturation

The land use categories and their interactions with soil depth had a significant (P ≤ 0.05) impact on the percent base saturation (PBS) of the research area as shown in Tables 6 and Table 7). The surface (0–20 cm) soil layer of forest land and grazing land, respectively, yielded the greatest (67.23%) and lowest (55.14%) values of PBS when considering the interplay of land use types with soil depth. The highest (74.40%) and the lowest (66.80%) values of PBS were reported under the forest and grazing fields, respectively, considering the primary influences of land use categories (Table 7).

Generally speaking, processes that influence the concentration of basic cations also affect the soil's percent base saturation. PBS in the research area was evaluated as high in the grass, farm, and grazing fields, whereas it was classified as extremely high in the forest land, according to the PBS rate reported by (Hazelton and Murphy, 2007). This suggests that the research area's soil contains large levels of exchangeable bases.

The objective of the this study was to evaluate the selected soil physical and chemical properties and Productivity as affected by different land use types on Gojera kebele dinsho district, south eastern of Bale zone, Central Highland of Ethiopia. The study area has low bulk density, which is indicating the higher soil OM and clay soil particles. The soil pH ranged in between 6.06 to 7.25 in farm and forest lands, respectively. The highest mean value EC ranged in between 0.52 to 0.31 S/m.

The higher soil OM and total N were recorded in the forest land while the lower was found in the grazing land. Considering the main effect of soil depths, the higher soil OM was observed on the surface soil layer and it is decreasing with increasing soil depth. The mean values of exchangeable Ca among forest, farm, grazing, and grass areas were 24.4, 19.8, 16.8, and 25.0 cmolc kg^− 1, respectively, considering the primary effect of land use categories (Table 7).

The CEC of soil under the study area was categorized in the high rate in grass, grazing and farm lands, whereas rated as very high in forest land. The highest (74.40%) and the lowest (66.80%) values of PBS were reported under the forest and grazing fields, respectively, considering the primary influences of land use categories (Table 7).

Generally, the study area has high pH, clay particles, total porosity, exchangeable basic cations, CEC and CaCO₃, but has low available P. P was the least abundant nutrient in the study area, possibly because CaCO₃ fixes it. Therefore, the supply of high P fertilizers levels are important, which can increase crop productivity. To minimize the P fixation and increase its availability, band or localized application of P fertilizer is highly recommended in the study area. Severe overgrazing and improper land use, including deforestation, have detrimental effects on soil qualities and must be addressed through suitable land use policies and management.

AVp Available Phosphorus

BD Bulk Density

BZAO Bale zone agricultural office

BMNP Bale mountain National Park

CEC Cation exchange capacity

C/N Carbon to nitrogen Ratio

CSA Central Statistical Agency

CV Coefficients of Variation

DWAO Dinsho woreda agricultural office

EC Electrical Conductivity

FGD Focus Group Discussion

IFPRI International Food Policy Research Institute

ILCA International Livestock Research Center for Africa

ISRIC International Soil Reference and Information Center

MoFED Ministry of Finance and Economic development

NPS Nitrogen phosphorus sulphur

NuMaSS Nutrient Management Support System

PASDEP Plan for Accelerated Sustained Development to End Poverty

PBS Percent Base Saturation

PCPs Physicochemical properties

PD Particle Density

SOC Soil Organic Carbon

TOC Total organic carbon

ACKNOWLEDGMENTS

The authors are thankful to Madda Walabu University, Department of Environmental Science for delivering logistic and materials for field activities, Department of Chemistry and Sinana soil agricultural laboratory for providing laboratory facilities such as instruments and chemicals support during laboratory analysis.

CONFLICT OF INTEREST

There is no conflict of interest regarding to this paper

FUNDING

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

CRediT author’s contribution statement And Agreement

Yohannes Shuka: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Validation, Writing – review & editing

Alemu Niguesse; Conceptualization, Writing – original draft, Conceived and designed the experiments, Collect data, Validation Investigation, and Formal analysis

We are read and agreed to publish this version of the manuscript.

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The Impact of Land Use Types on Soil Physicochemical Properties and Agricultural Productivity: a Case of Gojera Kebele, Dinsho District, South Eastern Ethiopia

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HIGHLIGHTS

1. Introduction

2. Material and Methods

2.1. Description of the study area

2.2 Climate of study area

2.3 Soils, vegetation and topography

2.4 Farming system (Agriculture)

2.5 Site Selection

2.6 Soil Sampling

2.7 Analysis of soil physical and chemical properties

2.8 Statistical data Analysis

3. Results and Discussion

3.2. Specific Soil chemical characteristics in relation to various land use types

3.2.1. Calcium carbonate, pH, and Electrical Conductivity

3.2.4. Total nitrogen (TN)

3.2.6. Available Phosphorus

3.2.7. Cation exchange capacity

3.2.8. Exchangeable bases

3.2.8.1. Percent base saturation

4. Conclusion

Abbreviations

Declarations

References

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