Soil and water conservation effects on soil properties

International Soil and Water Conservation Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎

HOSTED BY

Contents lists available at ScienceDirect

International Soil and Water Conservation Research journal homepage: www.elsevier.com/locate/iswcr

Original Research Article

Soil and water conservation effects on soil properties in the Middle Silluh Valley, northern Ethiopia Solomon Hishe a,b,n, James Lyimo b, Woldeamlak Bewket c a

Department of Geography and Environmental Studies, Mekelle University, Mekelle, Ethiopia Institute of Resources Assessment, University of Dar es Salaam, Tanzania c Department of Geography and Environmental Studies, Addis Ababa University, Addis Ababa, Ethiopia b

art ic l e i nf o

a b s t r a c t

Article history: Received 16 March 2017 Received in revised form 22 June 2017 Accepted 29 June 2017

Community-based Soil and Water Conservation (SWC) practices have been adopted in the Tigray region since 1991 for restoration of the degraded landscape. The effects of those conservation measures on physico-chemical properties of soil were limitedly studied. Thus, this study evaluated the effects of SWC on selected soil properties in the Middle Silluh Valley, Tigray region, Northern Ethiopia. The study considered conserved landscapes (terraced hillside, terraced farmland and exclosure area) and nonconserved landscapes (non-terraced hillside, non-terraced farmland and open grazing land) for comparison using a one-way analysis of variance (ANOVA). A total of 24 samples were collected from each landscape at a depth of 10–30 cm. The results indicated that mean bulk density (BD) was low on terraced hillside, non-terraced hillside and exclosure area. Sand and clay content were significantly different at P o0.05 for the six landscape categories. Higher mean organic matter was observed in the conserved landscape, as compared with the corresponding non-conserved landscape. Pearson's correlation between Soil Organic Matter (SOM) and clay content, SOM and Total Nitrogen (TN) showed strong positive relationships. Overall, the results show that SWC had significantly positive effects on soil's physical and chemical properties in the study area. & 2017 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. Production and Hosting by Elsevier B.V. This is an open access article under the CC BY-NCND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Land degradation Soil and water conservation Soil properties Middle Silluh Valley Ethiopia

1. Introduction Land degradation is a major problem in Ethiopia. It has a negative impact on agricultural economy and the natural environment Taddese (2001) clearly explained that the major causes of land degradation in Ethiopia are the rapid population increase, soil erosion, deforestation, low vegetative cover and unbalanced crop and livestock production. Similar idea was also reported by Bishaw (2001), Negusse, Yazew, and Tadesse (2013) that the rapid population growth, improper land resource management and utilization are the principal causes of increased runoff and soil erosion in the country which resulted in declining agricultural productivity, water scarcity and continuing food insecurity. The fertility of soil could be diminished through time due to land degradation. Moreover, Damene, n Corresponding author at: Department of Geography and Environmental Studies, Mekelle University, P.O. Box 231, Mekelle, Ethiopia. E-mail address: [email protected] (S. Hishe). Peer review under responsibility of International Research and Training Center on Erosion and Sedimentation and China Water and Power Press.

Tamene, and Vlek (2013) addressed that the inappropriate agricultural practices and conversion of marginal land into cultivation and grazing land have led to severe land degradation in the Ethiopian highlands. Land degradation increases vulnerability of people to the adverse effects of climate variability and change, by reducing Soil Organic Carbon (SOC) concentration and water holding capacity, which in turn reduces agricultural productivity and local resource assets (Mengistu, Bewket,& Lal, 2015; Damene et al., 2013; Pender, Ringler, Magalhaes, & Place, 2012). In order to solve such degradation problem, the Regional Government of Tigray in collaboration with some other non-governmental organizations like Gesellschaft Für Internationale Zusammenarbeit (GIZ), World Food Pprogramme (WFP), Relief Society of Tigray (ReST), Adigrat Diocesan Catholic Secretariat (ADCS) have developed strategies to work hand in hand with local communities on many SWC measures such as, construction of soil bund, stone bund, runoff control, and water harvesting structures, setting aside exclosure areas and nutrient management. It has been addressed by many researchers such as Gebreegziabher et al. (2009), Gebremichael et al. (2005), Nyssen et al.

http://dx.doi.org/10.1016/j.iswcr.2017.06.005 2095-6339/& 2017 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. Production and Hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Please cite this article as: Hishe, S., et al. International Soil and Water Conservation Research (2017), http://dx.doi.org/10.1016/j. iswcr.2017.06.005i

S. Hishe et al. / International Soil and Water Conservation Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎

2

(2007) that in order to minimize land degradation and restore degraded landscapes, a lot of efforts have been done in Ethiopia through SWC measures. It has been addressed by Bewket and Stroosnijder (2003) that local level investigation is essential to design area-specific and appropriate rehabilitation and management interventions. Within a broader context of understanding land degradation and SWC, the specific objectives of the present research paper are: (1) to evaluate the physico-chemical properties of soil; (2) to compare the two situations of conserved and non-conserved landscapes impacted by SWC measures. Hence, the effectiveness of such intervention on improving the fertility of soil biophysical and chemical properties shall be studied for better recommendation to policy makers.

2. Materials and methods 2.1. Study area description The study was carried out in the Middle Silluh Valley (MSV), northern highlands of Ethiopia with an area coverage of 490 km2. According to the local agro-ecological classification system which mainly relies on altitude and temperature, the study area is characterized by Woynadega (midland) and Dega (highland) (Mengistu, 2006). The River Sulluh flows in the middle of the study area in a north-south direction. The Middle Silluh Valley has an altitudinal range of 1818–2744 m.a.s.l. Within the study area, 28 lower administrative units, locally called “Tabia” were situated from Kilte_Awulaelo, Saesie Tsaeda Emba and Hawzen districts. Out of the 28 tabias, only 15 tabias are fully situated within the basin and the remaining have 50% or more of their territory. Mean annual rainfall from three stations for the period 2006–2015 is 536 mm and the minimum and maximum mean annual temperature are is 10.7 °C and 26.6 °C respectively. The dominant soils are Cambisols (moderately developed soils); Luvisols (evidence with accumulation of clay/organic matter); and Leptosols (highly calcareous material). The slope gradient of the study area also ranges from flat (o 0.2%) to very steep (460%). The study area is characterized by semi-arid environment where farmers dominantly produce wheat, barely, kerkaeta (mixed of barley and wheat), Eragrostis tef, millet and beans. The predominant economic activity of the inhabitant is subsistence agriculture. Monthly rainfall is high in the months of July and August in all the three stations. On the other hand, January and February are driest months. May and June are the hottest months (Fig. 2). 2.2. Soil Sampling and data collection Soil samples were collected from 24 sample sites in August 2016 (Fig. 1). Different soil sampling method have their own advantages and drawbacks Landon (1984). suggests judgment sampling for selection of typical sites is feasible to represent large areas. Accordingly, we used judgment sampling to take representative soil samples from conserved and non-conserved sites. The sites were four each from terraced hillside, non-terraced hillside, terraced farmland, non-terraced farmland, open grazing land and exclosure area. After removing the first 10 cm topsoil to exclude the presence of nematodes. Soil samples were taken using augur from 10 to 30 cm depth. One kg of soil from each sample site was packed in a plastic bag for laboratory analysis. In order to determine soil moisture content later in the lab, 200 g soils were collected from each sample site and measured on scale in-situ. Moreover, for determination of bulk density, 24 undisturbed soil samples were collected using core samplers. In characterizing the sample sites, we followed a similar approach as in Abegaz, Winowiecki, Vågen, Langan, and Smith (2016); Winowiecki (2015)

and recorded information about land use, average gradient, human influence and types of SWC structures. 2.3. Laboratory analysis The soil samples were air dried, crushed and sieved through a 2 mm mesh sieve for analysis. The soil properties considered in this study were Soil Organic carbon (SOC), Soil Organic matter (SOM), total nitrogen (TN), pH, texture, bulk density, exchangeable bases (Ca2 þ , Mg2 þ , Na þ and K þ ), available phosphorus (av. P), percentage base saturation (PBS), and cation exchange capacity (CEC). The analysis for exchangeable cations, CEC and avail. P were done at Department of Earth Sciences whereas the remaining parameters were analyzed at the Department of Land Resources and Environmental Protection (LaRMEP) soil laboratory unit, both at Mekelle University. Bulk density was determined using the Walkley and Black method (Black, 1965) method. Soil pH and texture were determined using the glass electrode and hydrometer method as suggested by Van Reeuwijk (2002), Haldar and Sakar (2005), respectively. Soil Organic Matter (SOM) was calculated by multiplying SOC with a factor of 1.724 after determining the organic carbon using Walkley-Black rapid titration method as described in Haldar and Sakar (2005). Total Nitrogen (TN) was determined by the Micro Kjeldhal process as described in Landon (1984). The determination of available Phosphorus (P) was made using the Oslen et al. (1954) method as described in Van Reeuwijk (2002). The measurement of individual exchangeable cations (Na þ , K þ Ca þ þ , and Mg þ þ ) and Cation Exchange Capacity (CEC) was done by adding 1 M ammonium ethanoate (acetate) solution at pH 7 as suggested by Haldar and Sakar (2005), Rowell (1994). 2.4. Data analysis The different physical and chemical properties of soil samples mentioned as a dependent variables and landscape category as independent variable were statistically tested. From each six landscape function, four samples were taken for the computation. Analysis of variance (ANOVA) using the Statistical Package for Social Scientists (SPSS 20) to evaluate whether significant difference exists among the landscape categories or not as the data contains more than two factors. Therefore, the ANOVA test using Post Hoc Test of Least Significance Difference (LSD) at alpha value of 5% was applied in the analysis. The mean difference is calculated by subtracting the mean of one landscape category from the mean of other respective landscape categories under a given dependent variable.

3. Results and discussion 3.1. Soil physical properties The soil physical properties were different under different landscape categories (Table 1). Mean bulk density (BD) was low in the terraced hillside, non-terraced hillside and exclosure area. SMC, BD, sand, silt and clay contents were significantly different under different landscape categories. A one-way analysis of variance (ANOVA) was conducted to explore the impact of different landscape category (conserved and non-conserved types) on soil physical property parameters (Bulk density fertility, soil moisture content, sand, silt and clay content) status. For the sand content, there is statistically significance difference at P o0.05 level for the six landscape groups: F(5, 23) ¼ 4.179, Po 0.05. Similarly, for the clay content, there is statistically significance difference at P o0.05 level for the six landscape



3

Fig. 1. Soil sample sites, geographical location and geological map of Middle Silluh Valley.

Fig. 2. Monthly average rainfall (mm) and monthly maximum, minimum and average temperature (°C). (a) ¼ At Freweyni metrological station, (b) ¼ At Wukro metrological station; and, (c) ¼ At Hawuzen metrological station; for the period 2006–2015 (EMA, Mekelle Branch, 2016).

categories: F(5, 23) ¼ 4.193, Po0.05, highest in NTHS (35.5%) and lowest in NTFL and GL (20%). For the remaining bulk density, soil moisture and silt content there was no statistically significance difference at P o0.05. (Table 1b) 3.1.1. Bulk density The highest mean bulk density (BD) was recorded in the nonterraced farmland followed by terraced farmland and grazing land 1.65 g/cm³, 1.60 g/cm³ and 1.60 g/cm³ respectively (Table 1, a). For the bulk density dependent variable using the LSD test, there is

only statistically significant difference at P o0.05 (Table 2) for the comparison between non-terraced farmland with terraced hillside landscape which is more by 0.19 of the mean. The non-conserved landscape (NTHS, NTFL and GL) were found significantly higher mean value of BD than the conserved landscapes of THS, TFL and ExA (Table 2). This could be due to the presence of significantly higher OM resulted from conservation measures and decay of plant residues. In line to this, similar result was reported by G.Selassie et al. (2013), Demelash and Stahr (2010), Selassie et al. (2015), Abay, Abdu, and Tefera (2016). Terraced farmland was



4

Table 1 Effects of changes in landscape on some selected physical properties in the Middle Silluh Valley, Northern Ethiopia, and ANOVA results. (a) Landscape

Mean of selected soil physical properties SMC (cm³/cm³)

THS NTHS TFL NTFL ExA GL (b) F Mean (n ¼24) P

BD (gm/cm³)

17.21 1.46 18.81 1.50 19.20 1.60 25.14 1.65 15.00 1.51 11.09 1.60 F, mean and ANOVA statistics 1.346 1.513 17.738 1.526 0.290 0.325

Sand (%)

Silt (%)

Clay (%)

36.00 39.50 62.00 70.00 51.00 60.50

31.00 25.00 13.50 9.50 24.00 19.00

33.00 35.50 26.50 20.50 25.00 20.50

4.179 53.17 0.011*

2.283 20.33 0.90

4.193 26.50 0.011*

THS-Terraced Hillside; NTHS-Non-Terraced Hillside; TFL-Terraced Farmland; NTFLNon-terraced farmland; ExA-Exclosure area; GL-Grazing land. * Significant level at p o 0.05 & & each landscape categories contain four sample sites and Values are average of 24 samples.

more by 26.0 and 22.5 of the mean in comparison to terraced hillside and non-terraced hillside respectively. According to Landon (1984) classification, the soils with mean 1.53 g/cm3 bulk density ranges with soils showing root restriction which reduces the plants ability to exploit the plants environment. A strong negative significant correlation was found (r ¼ 0.75) between CEC and bulk density of soil samples (Fig. 3(b)). This was evidenced by Schnitzer and Khan (1978), that the increased aggregation of CEC due to clay content may lower bulk density. 3.1.2. Soil moisture content (SMC) The soil samples were collected during the rainy season in the month of August 2016, and the distribution of rainfall throughout the study areas was almost homogeneous. SMC is generally reported as the ratio of the mass of water present in a soil sample to the mass of the sample after it has been dried at 105 °C to a constant weight (Haldar & Sakar, 2005; Van Reeuwijk, 2002). The lowest mean soil moisture content was observed in the grazing lands (11.09%) which characterized with less vegetation cover and slope ranges between 2% and 17%. This could facilitate to loose water without infiltrating into the soil and increased the evaporation rate to the atmosphere. On the contrary, the highest mean value of SMC was observed in the terraced and non-terraced

farmlands respectively where more textural soil was dominant (Table 3). This could probably be due to the combination of factors such as continuous cultivation leading to high soil porosity and the dominancy of course soil textural class (Table 4). For soil moisture content as dependent variable using the Least Significance Difference (LSD) test, there is just measurably critical distinction at P o0.05 for the comparison between non-terraced farmland with grazing land (Table 3). 3.1.3. Soil texture 3.1.3.1. Sand content. The soil textures of the study area was assessed based on proportion of three mineral particles, sand, silt and clay in a soil. The sand texture was relatively highest mean value in the non-conserved area (NTHS, NTFL and GL) than the conserved once (TSL, TFL and ExA) (Table 1a). The non-terraced farmland had shown the highest mean sand fraction (70%) in comparison to the terraced farmland (62%). On the contrary, the lowest sand content was observed in the terraced hillside (36%) which is the effect of conservation practices to accumulate better organic matter and clay materials. The study area was mostly characterized by Enticho sandstone and Adigrat sandstone parent material (Fig. 1). Other reason may be trampling by grazing animals could facilitate the export of finer clay and silt particles through wind and water erosion. 3.1.3.2. Silt content. The silt content was higher in the conserved landscape (THS, TFL and ExA) than in the non-conserved landscape (NTHS, NTFL and GL). This result was in concurrence with Bezabih, Aticho, Mossisa, and Dume (2016) who found higher mean silt proportion in woodland and fallow land than cultivated land without soil bunds. However, the results of the silt content in this study was not in line with Demelash and Stahr (2010), Mengistu et al. (2015); who found that the silt content was high in non-conserved rather than conserved land which is characterized with basaltic Trap series of volcanic eruptions parent material. On the other hand, the smallest proportion of silt content (9.5%) was recorded in the non-terraced farmland (Table 1a). A statistically significance difference was observed at P o0.05 for terraced hillside contrasted with terraced farmland and non-terraced farm land. 3.1.3.3. Clay content. The proportion of clay content in both the conserved and non-conserved landscapes was below 50%. The clay

Table 2 One Way ANOVA multiple comparison for different soil physical properties among landscape categories in the Middle Silluh Valley, Northern Ethiopia. Dependent Variable

Bulk Density (gm/Cm3) Soil Moisture (%) Sand Content (%)

Silt Content (%) Clay Content (%)

Landscape Category (I)

NTFL NTFL TFL TFL NTFL NTFL GL GL THS THS THS THS NTHS NTHS NTHS NTHS

Landscape Category (J)

THS GL THS NTHS THS NTHS THS NTHS TFL NTFL NTFL GL TFL NTFL ExA GL

Mean difference (I-J)

0.188* 14.047* 26.000* 22.500* 34.000* 30.500* 24.500* 21.000* 17.500* 21.500* 12.500* 12.500* 11.000* 15.000* 10.500* 15.000*

Sig.

0.039 0.024 0.012 0.026 0.002 0.004 0.017 0.036 0.030 0.010 0.011 0.011 0.022 0.003 0.028 0.003

95% confidence interval Lower bound

Upper bound

0.365 2.030 6.49 2.99 14.49 10.99 4.99 1.49 1.90 5.90 3.29 3.29 1.79 5.79 1.29 5.79

0.01 26.06 45.51 42.01 53.51 50.01 44.01 40.51 33.10 37.10 21.71 21.71 20.21 24.21 19.71 24.21

THS-Terraced Hillside; NTHS-Non-Terraced Hillside; TFL-Terraced Farmland; NTFL-Non-terraced farmland; ExA-Exclosure area; GL-Grazing land. *

The mean difference is significant at the 0.05 level.



5

Fig. 3. Scatter plot regression of selected soil chemical properties in the Middle Silluh Valley, Northern Ethiopia.

content was slightly higher in the non-terraced and terraced hillside (35.5% and 33% respectively) where better vegetation cover exists. This can be basically the direct result of the chemical weathering of silicate minerals from the prevalence sedimentary rocks in the study area and the vegetation cover protects from washing away. The lowest proportion of clay was observed equally (20.5%) in the non-terraced farm land and grazing land. This is true that clay materials are fine particles that can be easily transported to other areas, unless different conservation measures are applied. The mean values of clay content in the conserved landscape (TFL and ExA) was higher than the comparing non-conserved landscape (NTFL & GL). Similar result was reported by Mengistu et al. (2015) indicating that in all landscape position with conservation practice at Minchet sub watershed shown higher clay content than

non-conserved at Zikrie sub watershed. The one way ANOVA Post Hoc Test of LSD revealed that clay content on a terraced hillside showed statistically significant difference at P o0.05 with non-terraced farm land and grazing land. The clay content of the terraced hillside shows in a higher mean difference of 12.5 in relation to both the non-terraced farm land and grazing land (Table 2). 3.1.4. Soil textural classes The major textural classes for the study sample sites are provided in Table 3. Each of the textural classes listed in Table 3 are according to the different landscape category considered in the study objective. In the terraced hillside, 75% of the textural classes are in the loamy clay with the slope range 9–39% make up finely



6

Table 3 Effects of changes in landscape on soil textural classes in the Middle Silluh Valley, Northern Ethiopia. Landscape Category

Average Textural classes of landscape categories (%) Clay Clay Loam

THS NTHS TFL NTFL ExA GL

– 25 25 – –

75 25 – – –

Loam Sandy Clay Sandy Clay Loam

Sandy loam

– – – – 25 25

– – – 50 50 50

– 25 – – –

25 25 75 50 25 25

Slope (%)

9–39 9–19 5–10 4–10 5–29 2–17

THS-Terraced Hillside; NTHS-Non-Terraced Hillside; TFL-Terraced Farmland; NTFLNon-terraced farmland; ExA-Exclosure area; GL-Grazing land. *Significant level at p o0.05 & each Values are average of 4 samples. Table 4 Mean and significance level of selected soil chemical properties in the Middle Silluh Valley, Northern Ethiopia.

F Mean P *

pH

SOC (%)

SOM (%)

TN (%)

Av. P (ppm)

0.231 5.95 0.944

3.344 1.21 0.026*

3.344 2.085 0.026*

1.952 0.101 0.135

0.303 0.617 0.905

Significant level at p o 0.05.

textured soils. The non-terraced hillside with the slope range between 9–19% was also characterized 25% by clay and 25% clay loam textural classes which contains a higher proportion of clay and relatively lower amounts of sand and silt. This is relatively good for plant growth than clay since it has more open spaces that encourage aeration and more water holding capacity to be readily available for plants' use. In the terraced farm land, non-terraced farm land, area exclosure and grazing land areas, the soil texture class is dominated by sandy clay loam to sandy loam. As the study area is geologically dominated by Enticho sandstone and Adigrat sandstone, the abundance of more sandy texture in those relatively gentle slope areas was greatly expected. 3.2. Soil chemical properties The effects of independent variables in the study area (area exclosure and grazing land, terraced hillside and non-terraced hillside, terraced farmland and non-terraced farmland) on the considered dependent variable chemical properties of soils were statistically tested. The study area was characterized with heterogeneous landscape and land use types. SWC conservation measures through community mobilization work was applied to reduce soil erosion, increase infiltration and improve the vegetation cover in non-cultivable land and maximize the fertility of soil in general. 3.2.1. Soil organic matter and soil organic carbon The results of the analysis indicates that there was statistically significant (p o 0.05) difference in OM content among the different landscape categories (Table 5). The highest mean organic matter was recorded in the conserved landscape (THS ¼ 4.04%, TFL¼ 1.20% and ExA ¼ 1.84%) as compared to the corresponding non-conserved landscape (NTHS ¼ 2.01%, NTF ¼ 1.09%, and GL ¼ 1.37%). These variations are the results of soil and water conservation schemes applied in the area. For instance, the highest organic matter in situ (6.56%) at village Samuel of Tabia GiraAras in Hawzen district was recorded from the terraced hillside conserved by the local community since 1984. This indicates that the longer

Table 5 Effects of changes in landscape on selected soil chemical properties in the Middle Silluh Valley, Northern Ethiopia. Landscape

THS NTHS TFL NTFL ExA GL

Mean of some soil chemical properties pH

SOC (%)

SOM (%)

TN (%)

Av. P (ppm)

6.0 6.0 6.0 5.5 6.0 6.0

2.34 1.72 0.70 0.63 1.07 0.79

4.04 2.01 1.20 1.09 1.84 1.37

0.19 0.14 0.10 0.05 0.07 0.06

0.72 0.71 0.56 0.45 0.67 0.61

THS-Terraced Hillside; NTHS-Non-Terraced Hillside; TFL-Terraced Farmland; NTFLNon-terraced farmland; ExA-Exclosure area; GL-Grazing land.

the time a landscape is conserved, the higher the effect on organic matter accumulation mainly due to the decay of leaves and litter materials and decomposed in to humus. This result comes to an agreement with findings of Mengistu et al. (2015), Negusse et al. (2013). Results of the preliminary correlation analysis as indicated in Fig. 3(c) and (d) shows that there was very weak positive correlation between CEC and organic matter content (r ¼0.03) and between CEC and clay content (r ¼0.05). This result is in-line with the result found by Montecillo (1983). The results of the analysis indicates that there was statistically significant (p o 0.05) difference in OM content among the different landscape categories (Table 4). Rowell (1994) described that soil organic matter is the central to the maintenance of soil fertility: mineralization of N, P and S, the soils ability to hold nutrient cations, structural ability and water holding capacity are all affected by OM content Schnitzer and Khan (1978). also agreed that organic matter improves infiltration, decrease evaporation, improve drainage in fine textured soils, foster more extensive and deeper root systems. In our study, the soil organic carbon (SOC) in the terraced hillside was noted higher than in the other sampled landscapes. However, a small difference in SOC concentration was found between THS and NTHS landscape, and moderate difference in ExA landscape (Table 5). The lowest mean OC was found in TFL ¼0.7%; NTFL ¼0.63% and GL ¼0.79%. As soil organic carbon does not provide alone any essential nutrient to crops, there is close relationships between SOC and SON over a wide range of soils (Gaiser & Stahr, 2013) and are also strongly correlated. The accumulation of SOC is one of the initial soil forming processes and is determined by physical, chemical, biological and anthropogenic factors with complex interactions (Gaiser & Stahr, 2013) (Table 6). The average mean value of soil organic carbon was arranged by THS 4NTHS 4ExA 4GL 4TFL4 NTFL (Table 5). This shows that a direct relationship with the vegetation cover and conservation measure applications and inversely with intensive human and livestock interference. Similar results were also found by Bezabih Table 6 Critical levels for some soil fertility parameters. Status

Very Low Low Optimum High Very High

Critical Level Soil pH

TN (%)

OM (%)

Av. P (mg/kg)*

K þ (mg/kg)

o 5.5 5.6–6.5 6.6–7.3 7.4–8.4 48.4

o 0.1 0.1–0.15 0.15–0.3 0.3–0.5 40.5

o2.0 2.0–3.0 3.0–7.0 7.0–8.0 48.0

0–15 15–30 30–80 80–150 4150

o 90 90–190 190–600 600–900 4900

Source: Table adopted from Agricultural Transformation Agency (ATA), Addis Ababa, 2014. *

¼ 1 mg/kg is equal to 1 ppm.


S. Hishe et al. / International Soil and Water Conservation Research ∎ (∎∎∎∎) ∎∎∎–∎∎∎ Table 7 One Way ANOVA multiple comparison for different soil fertility among landscape categories using Post Hoc Test of LSD in the Middle Silluh Valley, Northern Ethiopia. Dependent Variable

SOC (%)

SOM (%)

TN (%)

Land Category (I)

THS THS THS THS THS THS THS THS THS THS THS

Land Category (J)

TFL NTFL ExA GL TFL NTFL ExA GL NTFL ExA GL

Mean difference (I-J)

1.65* 1.71* 1.28* 1.55* 2.84* 2.96* 2.20* 2.67* 0.138* 0.123* 0.133*

Sig.

0.006 0.005 0.027 0.009 0.006 0.005 0.027 0.009 0.022 0.038 0.026

95% confidence interval Lower bound

Upper bound

0.53447 0.60217 0.16655 0.43887 0.92143 1.0381 0.28713 0.75662 0.02244 0.00739 0.01789

2.75826 2.82595 2.39033 2.66266 4.75524 4.87194 4.12093 4.59043 0.25266 0.23761 0.24811

THS-Terraced Hillside; TFL-Terraced Farmland; NTFL-Non-terraced farmland; ExAExclosure area; GL-Grazing land. *

The mean difference is significant at the 0.05 level.

et al. (2016), Khan, Hayat, Ahmad, Ramzan, and Shah (2013); that less amount of SOC was detected in farmlands, which could be due to the poor land management and frequent destabilization of the soil. The one-way ANOVA showed that landscapes under different management had a significant effect on soil organic carbon. As indicated in Table 7, a terraced hillside was observed statistically significant difference at P o0.05 with terraced farmland, nonterraced farmland, exclosure area and grazing land. The mean SOC content results of terraced hillside was higher by 1.65 from TFL, by 1.71 from NTFL, by 1.28 from ExA and by 1.55 from GL respectively. However, there was no statistically significance difference shown between terraced hillside and non-terraced hillside due to their vegetation cover was almost similar and the degree of decomposition of plant residue to be the same. A simple regressions were calculated between CEC (me/ 100 g soil) as the dependent variable and clay content (%) and SOC (%) as the independent variable. The Pearson's correlation between SOC and clay content shows strong positive relationship (%Clay¼ 19.35 þ5.91 SOC%, r ¼0.67 (Fig. 3f). This result is in consistent with other studies conducted by Soares and Alleoni (2008) in the areas of native vegetation in State of São Paulo, Brazil, where SOC contents were strongly associated with the clay contents and other by Olorunfemi, Fasinmirin, and Ojo (2016) conducted in Ekiti State, in the forest vegetative zone of Nigeria. On the other hand, a lower positive coefficient was obtained for a correlation of CEC and SOC (CEC ¼ 3.34 þ 0.063 SOC%, r ¼ 0.031) (Fig. 3e). This is in contrast to the findings of Olorunfemi et al. (2016), Rashidi and Seilsepour (2008) who reported higher correlation between CEC and SOC. According to Evans 1996, the results of our finding was classified as very weak positive correlation. 3.2.2. Total nitrogen (TN) The highest mean total nitrogen in the study area was found in the THS, and TFL for 0.19% and 0.10% respectively. The existent of better TN in these two landscape was due to the presence of physical SWC measures in general; and in the TFL farmers have applied manure and commercial fertilizer every year for maximizing their crop production. In the NTHS, higher mean TN content was observed (0.14) and this could be due specifically to the contribution of nitrogen fixing plants. In general, the findings were in agreement with Alemayehu (2007), Amare et al. (2016), Mulugeta and Karl (2010), Selassie et al. (2015) stated that SWC supplemented with rehabilitated vegetation cover had positive impact in improving the total nitrogen of the soil. The Pearson's

7

correlation between TN and SOM content shows strong positive relationship (%TN ¼ -0.0034 þ0.05 SOM%, r ¼0.97) (Fig. 3a). In the one way ANOVA at Po0.5 level of significance, TN was not statistically significant difference among the landscape categories (Table 4). However, the multiple comparison for TN content among landscape categories using Post Hoc Test of LSD was evaluated and the result indicates a terraced hillside was observed statistically significant difference at P o0.05 with non-terraced farm land; exclosure area and grazing land. The mean TN content results of terraced hillside was higher by 0.14, 0.12 and 0.13 of the mean in relation to NTFL, ExA and GL respectively (Table 7). According to some studies, total nitrogen content in the top 15– 20 cm of surface soils ranges from 0.01% (or even less in desert soils) to more than 2.5% in peats (Prasad & Power, 1997). Soil nitrogen is derived primarily from atmospheric nitrogen gas (N2), however soil micro-organisms, both free living and symbiotically associated with plants fix N2 to produce organic nitrogen (Rowell, 1994). When plant residues decompose, much of the nitrogen they contain will undergo several microbial conversions and will eventually end up back as nitrates (Prasad & Power, 1997). Hence, total nitrogen is one of the essential nutrient for plant and animals. 3.2.3. Available phosphorus As indicated in the Table 5, the lowest percent's of available phosphorus (0.45 ppm) was in the pH 5.5 in the non-terraced farmlands. The relatively higher percentage of available phosphorous was also observed in the THS and NTHS landscape categories which have a mean pH 6.0 value uniformly (Table 5). According to ATA (2014) critical level classification for available phosphorus (Table 6), there was very weak status of available phosphorus in all the landscape categories of the soil. According to Landon (1984) also, the available phosphorus in the study area was classified as acutely deficient (o 3 ppm P.). This indicates that there is high deficiency of available phosphorus in the study area. Phosphorus is one the most important element in the soil nutrient required by plant. Plants grow slowly when the levels of available phosphorus in the soil is low. The presence of organic phosphorus content depends upon a number of factors such as climate, vegetation, soil texture, land use pattern, fertilizer practices, drainage, irrigation and moreover the availability of phosphorus in the soil is greatest in the pH range 6.0–6.5 (Prasad & Power, 1997). In general, we can conclude that Middle Silluh Valley was characterized by low available phosphorus and this could be due to the existence of acidic soil (mean pH with 5.5–6.0) throughout and the presence of low organic matter. This result is supported by Tisdale and Nelson (1975) who found available phosphorous decreased with higher acidic soil pH. This is true that nutrients are recycled by decomposition through the soil organic matter and provides more than 90% nitrogen and about 50–60% phosphorus and sulfur (Osman, 2013). At low or acidic pH (o 5.5), phosphorus is combined with Al, Fe, and Mn as their polyphosphates and at high pH (48.0), P is precipitated with Ca (Landon, 1984; Osman, 2013). Both at soil acidity and alkalinity, availability of phosphorus is reduced to deficiency levels. Availability of P is usually higher in the pH range of 6.5 and 7.0 (Osman, 2013). That is why one of the most important benefits of liming acidic soil is improving phosphorus availability. Moreover, the addition of phosphorus through fertilization can improve its availability. 3.2.4. Exchangeable bases Both the conserved and non-conserved landscapes in the study area have shown non-significant difference among the mean values of exchangeable Ca þ þ , K þ , Mg þ þ , Na þ and sum of exchangeable bases. The mean relative abundance of basic cations in the exchange complex for all the landscape categories in the study



8

Table 8 Mean, Suggested quantity, and significance level of Exchangeable Bases, CEC, and PBS in the Middle Silluh Valley, Northern Ethiopia. Exchangeable Bases† Measurement

Ca

K

Mg

Na

SEB

F Mean Suggested Quantity♀ P

0.232 1.943 45 0.943

0.110 0.011 40.5 0.989

0.074 0.245 40.5 0.995

1.543 0.0247 o 1.0 0.222

0.227 0.222 – 0.946

CEC†

PBS (%)

0.231 3.43 415 0.945

0.321 54.18 4 50 0.894

† meq. 100 g 1; CEC ¼ Cation Exchange capacity; PBS ¼ Percentage Base Saturation; SEB-Sum of Exchangeable Bases. ♀ ¼ Suggested quantity adapted from Landon (1984). Significance level at P o 0.05.

samples were in the order of Ca þ þ 4 Mg þ þ 4 Na þ 4 K þ (Table 8). The results of this study was in agreement with Amare et al. (2016), Amdemariam, Selassie, Haile, and Yamoh (2011), Lelago, Mamo, and Haile (2016), Hailu, Moges, and Yimer (2012), who found a non-significant variation in exchangeable bases among different soil and water conservation measures. Similarly, the difference in the sum of exchangeable base (SEB) was not statistically significant at P o0.05 among the mean of different landscape categories. 3.2.5. Cation exchange capacity (CEC) The cation exchange capacity (CEC) is a measure of the number of adsorption sites per unit weight of soil at a particular pH. The soil samples collected and analyzed for the study area indicates that there is no statistically significant variation among the mean values for the CEC for different landscape category. The result of this study was in agreement with Hailu et al. (2012), Mulugeta and Karl (2010) who found a non-significant variation in CEC among different soil and water conservation measures. According to Jones (2012), soils with CEC within 1–10 meq/ 100 g range are characterized with high sand content, low organic matter content and low water holding capacity. Hence with an average mean of 3.43 meq/100 g of soil CEC in the study area indicates that there was an existence of physical ramifications associated with high sand content and geologically the study area is dominated with sandstone parent materials (Enticho and Adigrat sandstone). As a result, the soil could be exposed for low capacity of holding plant nutrient elements and loss by leaching from the soil profile. As a recommendation to the terraced and non-terraced farm lands, the application of large amount of fertilizer or lime is required to obtain better crop production. Based on Landon (1984) class rating, the mean CEC of the study area is very low (o5 meq/ 100 g of soil) and such observation of low CEC in a study area indicates the requirement of better management of the land. 3.3. Correlation matrix of physical and chemical soil properties A partial correlation was carried out to explore the relationship between each single property of a soil and the other 16 parameters considered in the analysis of this study. The correlation between total nitrogen (TN) and soil organic matter (SOM) was very strong positive partial correlation, r ¼ 0.928, n ¼24, p o 0.01. Moreover, there was also a positive moderate correlation with clay content (r ¼0.613), however, TN was strong negatively correlated with BD, r ¼ 0.742. This result is directly similar with the findings of Abay et al. (2016) who studied on the central highlands of Ethiopia. Likewise, SOM was strong positive significantly correlated with clay content, and moderate positive significantly correlated with silt content (r ¼ 0.673 and r ¼ 0.426) respectively. On the contrary, there was a strong negative significant correlations between SOM

and BD (r¼ –0.747, n ¼ 24, p o 0.001); SOM and sand content (r¼ –0.614, n ¼ 24, p o 0.01) (Table 9). The SOM has shown strong positive significant correlation with clay content r ¼0.673 and strong negative significant correlation with sand content and BD (r ¼ –0.614 and r ¼ –0.747) at P o0.01 respectively. Very strong correlation was also noted between PBS and, Ca þ þ , Mg þ þ , SEB, and CEC where r ¼ 0.956, 0.916, 0.958 and 0.958 respectively (Table 9). The available phosphorus has also shown negatively moderate significant with Na þ , Ca þ þ , Mg þ þ , SEB, CEC and PBS at r between 0.521 to 0.591 where p o 0.01 (Table 9).

4. Conclusion The government of Ethiopia is trying to reverse the degraded landscape through different land conservation measures with the participation of the local communities. This investigation has also demonstrated on the effects of different methods of soil and water conservations applied on the physical and chemical properties of soil in the Middle Silluh Valley, northern Ethiopia. The conserved landscape categories (TFL and ExA) shown better clay content than the non-conserved landscape categories (TFL and GL). On the other hand the non-conserved landscape (NTHS, NTFL and GL) were observed to have a significantly higher mean value of BD than the conserved landscapes (THS, TFL and ExA). As many studies revealed, the lower BD in the conserved landscape could be due to the presence of significantly higher SOM resulting from conservation measures and decay of plant residues. The SWC measures implemented on the hillside of the study area have also shown great impact on the improvement of the SOM and TN of the soil. This was a good indicator for further application of SWC measures on other degraded hillside landscapes of the region. Both the conserved and non-conserved landscapes in the study area have shown non significance difference among the mean values of exchangeable Ca þ þ , K þ , Mg þ þ , Na þ and sum of exchangeable bases. The sandstone parent material of the study area and acidic nature of the soil exacerbates the deficiency of exchangeable cations, despite the fact that SWC measures are practiced. In general, the effects of SWC intervention at the Middle Silluh River were found to have pronounced positive effects on some selected soil physical and chemical properties. The different conservation measures applied in the area like bench terrace, soil bund, stone bund, check dam, trench, preserving area exclosure, and re-afforestation were significantly important not only to protect soil erosion, but also to maintain soil fertility. In order to achieve the desired target and be sustainable, the different forms of conserved landscapes should be prevented from the interference of human being and livestock for better recovery of natural resources.

Acknowledgement The authors would like to thank TRECCAfrica II for providing scholarship to the principal investigator to study at the Institute of Resources Assessment, University of Dar es Salaam, Tanzania. The Meteorological agency of Mekelle branch also for supplying climatic data. We thank Mekelle University, Department of Earth Sciences and Department of Land Resources Management and Environmental Protection for their soil analysis. Many thanks to the College of Social Sciences and Languages in Mekelle University for providing vehicle to the fieldwork during soil sample collection. Our appreciation also to Dr. Luca Ongaro for proof reading the


9

manuscript. The authors would like to thank the three anonymous reviewers for their valuable comments and suggestions on the improvement of this manuscript. The first author is also grateful to Mekelle University for granting research fund under registration number CRPO/CSSL/PhD/003/08.

**

Correlation is significant at 0.05 level (2-tailed). Correlation is significant at 0.01 level (2-tailed).

References

*

Na-Sodium, K-Potassium, Ca-Calcium, Mg-Magnesium, SEB-Sum of Exchangeable Bases, PBS-Percentage of Base saturation, Av. P-Available Phosphorus, BD-Bulk Density, SMC-Soil Moisture Content, SOC-Soil Organic Carbon, SOMSoil Organic Matter, and TN-Total Nitrogen.

1 1 0.928** 1 1.000** 0.928** pH Na K Ca Mg SEB CEC PBS Av. P Sand Silt Clay BD SMC SOC SOM TN

1 0.068 0.287 0.399 0.267 0.4 0.4 0.311 0.138 0.315 0.289 0.242 0.302 0.419* 0.31 0.309 0.329

1 0.019 0.742** 0.509* 0.736** 0.736** 0.692** 0.591** 0.163 0.118 0.171 0.2 0.111 0.215 0.215 0.11

1 0.142 0.379 0.149 0.149 0.321 0.156 0.348 0.366 0.198 0.124 0.025 0.118 0.118 0.149

1 0.839** 1.000** 1.000** 0.956** 0.568** 0.068 0.069 0.043 0.044 0.077 0.028 0.028 0.104

1 0.845** 0.845** 0.916** 0.521** 0.24 0.159 0.274 0.096 0.179 0.18 0.18 0.266

1 1.000** 0.958** 0.568** 0.073 0.072 0.047 0.041 0.073 0.031 0.031 0.108

1 0.958** 0.568** 0.073 0.072 0.047 0.041 0.073 0.031 0.031 0.108

1 0.581** 0.097 0.117 0.033 0.053 0.035 0.011 0.011 0.073

1 0.21 0.074 0.335 0.069 0.154 0.105 0.105 0.021

1 0.906** 0.783** 0.392 0.102 0.614** 0.614** 0.516**

1 0.446* 0.315 0.041 0.426* 0.426* 0.326

1 0.366 0.155 0.672** 0.673** 0.613**

1 0.002 0.748** 0.747** 0.742**

1 0.109 0.109 0.007

SOM Sand Av. P PBS CEC SEB Mg Ca K Na pH

Table 9 Pearson correlation coefficient between different physico-chemical properties of soils, in the Middle Silluh Valley, Northern Ethiopia.

Silt

Clay

BD

SMC

SOC

TN


Abay, C., Abdu, A., & Tefera, M. (2016). Effects of graded stone bunds on selected soil properties in the central highlands of Ethiopia. International Journal of Natural Resource Ecology and Management, 1(2), 42–50. http://dx.doi.org/10.11648/j. ijnrem.20160102.15. Abegaz, A., Winowiecki, L. A., Vågen, T.-G., Langan, S., & Smith, J. U. (2016). Spatial and temporal dynamics of soil organic carbon in landscapes of the upper lue Nile Basin of the Ethiopian highlands. Agriculture, Ecosystems & Environment, 218, 190–208. http://dx.doi.org/10.1016/j.agee.2015.11.019. Alemayehu, A. (2007). Impact of Terrace Development and Management on Soil Properties in Anjeni Area, West Gojam. Addis Ababa University. Retrieved from 〈http://s3.amazonaws.com/zanran_storage/www.cde.unibe.ch/ContentPages/ 47642682.pdf〉. Amare, T., Terefe, A., Selassie, Y. G., Yitaferu, B., Wolfgramm, B., & Hurni, H. (2013). Soil Properties and Crop Yields along the Terraces and Toposequece of Anjeni Watershed , Central Highlands of Ethiopia, 5(2), 134–144. https://doi.org/10. 5539/jas.v5n2p134. Amdemariam, T., Selassie, Y. G., Haile, M., & Yamoh, C. (2011). Effect of soil and water conservation measures on selected soil physical and chemical properties and barley (Hordeum spp.) yield. Journal of Environmental Science and Engineering, 5, 1483–1495. ATA, (Agricultural Transformation Agency) (2014). Soil Fertility Status and Fertilizer Recommendation Atlas for Tigray Regional State, Ethiopia. Addis Ababa. http:// www.ata.gov.et/download/soil-fertility-status-fertilizer-recommendation-at las-tigray-regional-state_jul2014/, (accessed on January 21 2017). Bewket, W., & Stroosnijder, L. (2003). Effects of agroecological land use succession on soil properties in Chemoga watershed, Blue Nile basin, Ethiopia. Geoderma, 111(1–2), 85–98. http://dx.doi.org/10.1016/S0016-7061(02)00255-0. Bezabih, B., Aticho, A., Mossisa, T., & Dume, B. (2016). Journal of soil science and environmental management the effect of land management practices on soil physical and chemical properties in Gojeb sub-river Basin of Dedo District. Southwest Ethiopia, 7(10), 154–165. http://dx.doi.org/10.5897/JSSEM2016.0574. Bishaw, B. (2001). Deforestation and Land Degredation in the Ethiopian Highlands: A Strategy for Physical Recovery. Northeast African Studies. Retrieved from 〈https://muse.jhu.edu/article/188323/summary〉. Black C. A. (1965). Methods of soil analysis. Part 1 and 2. Retrieved from 〈http://14. 139.56.90/handle/1/2061845〉. Damene, S., Tamene, L., & Vlek, P. L. G. (2013). Performance of exclosure in restoring soil fertility: A case of Gubalafto district in North Wello Zone, northern highlands of Ethiopia. Catena, 101, 136–142. http://dx.doi.org/10.1016/j. catena.2012.10.010. Gaiser, T., & Stahr, K. (2013). Soil organic carbon, soil formation and soil fertility In: R. Lal, K. Lorenz, R. F. Hüttl, B. U. Schneider, & J. von Braun (Eds.), Ecosystem Services And Carbon Sequestration In The Biosphere. Springer Science þ Business Media Dordrechthttp://dx.doi.org/10.1007/978-94-007-6455-2. Gebreegziabher, T., Nyssen, J., Govaerts, B., Getnet, F., Behailu, M., Haile, M., & Deckers, J. (2009). Contour furrows for in situ soil and water conservation, Tigray, Northern Ethiopia. Soil and Tillage Research, 103(2), 257–264. http://dx.doi. org/10.1016/j.still.2008.05.021. Gebremichael, D., Nyssen, J., Poesen, J., Deckers, J., Haile, M., Govers, G., & Moeyersons, J. (2005). Effectiveness of stone bunds in controlling soil erosion on cropland in the Tigray Highlands, northern Ethiopia. Soil Use and Management, 21(3), 287–297. http://dx.doi.org/10.1079/SUM2005321. Hailu, W., Moges, A., & Yimer, F. (2012). The effects of ‘Fanya juu’o /i 4 soil conservation structure on selected soil physical & chemical properties: The case of Goromti watershed, Western Ethiopia. Resources and Environment, 2(4), 132–140. http://dx.doi.org/10.5923/j.re.20120204.02. Haldar, & Sakar (2005). Physical and chemical method in soil analysis: Fundamental concepts of analytical chemistry and instrumental techniques. New Delhi: New Age International (P) Ltd. Publisher. Jones, J. B. (2012). Manual, plant nutrition and soil fertility manual ((2nd ed.i). Boca Raton: CRC Press, Taylor & Francis Group. Khan, F., Hayat, Z., Ahmad, W., Ramzan, M., & Shah, Z. (2013). Effect of slope position on physico-chemical properties of eroded soil. Soil and Environment, 32 (1), 22–28. Landon, J. (1984). Booker tropical soil manual: A handbook for soil survey and agricultural land evaluation in the tropics and subtropics. New York: John Wiley and Sons. Lelago, A., Mamo, T., & Haile, W. S. H. (2016). Assessment and mapping of status and spatial distribution of soil macronutrients in Kambata Tembaro zone, Southern Ethiopia. Advances in Plants & Agriculture Research, 4(4), 1–14. http://dx.doi.org/ 10.15406/apar.2016.04.00144. Mengistu, D., Bewket, W., & Lal, R. (2015). Conservation Effects on Soil Quality and Climate Change. Land Degradation and Development, (Published online in Wiley Online Library (wileyonlinelibrary.com)). https://doi.org/10.1002/ldr.2376.


10


Montecillo, L. C. (1983). Total clay and organic matter in relation to soil cation exchange capacity. The Philippine Journal of Crop Science, 8(1), 41–44. Mulugeta, D., & Karl, S. (2010). Assessment of integrated soil and water conservation measures on key soil properties in assessment of integrated soil and water conservation measures on key soil properties in South Gonder, North-Western highlands of Ethiopia. Journal of Soil Science and Environmental Management, 1 (7), 164–176. Negusse, T., Yazew, E., & Tadesse, N. (2013). Quantification of the impact of integrated soil and water conservation measures on groundwater availability in Mendae catchment, Abraha We-Atsebaha, eastern. Momona Ethiopian Journal of Science. 〈http://www.ajol.info/index.php/mejs/article/view/91495〉. Nyssen, J., Poesen, J., Gebremichael, D., Vancampenhout, K., D’aes, M., Yihdego, G., & Deckers, J. (2007). Interdisciplinary on-site evaluation of stone bunds to control soil erosion on cropland in Northern Ethiopia. Soil and Tillage Research, 94(1), 151–163. http://dx.doi.org/10.1016/j.still.2006.07.011. Olorunfemi, I. E., Fasinmirin, J. T., & Ojo, A. S. (2016). Modeling cation exchange capacity and soil water holding capacity from basic soil properties. Eurasian Journal of Soil Sciences, 5(4), 266–274. http://dx.doi.org/10.18393/ ejss.2016.4.266-274. Osman, K. (2013). Soils: Principles, properties and management. New York: Springer Science þ Bussines Media Dordrecht. Pender, J., Ringler, C., Magalhaes, M., & Place, F. (2012). The role of sustainable land management for climate change adaptation and mitigation in sub-Saharan Africa. Retrieved from 〈http://agris.fao.org/agris-search/search.do? RecordID¼ QB2015103834〉. Prasad, R., & Power, J. F. (1997). Soil fertility management for sustainable agriculture. New York: CRC Lewis Publishers.

Rashidi, M., & Seilsepour, M. (2008). Modeling of soil cation exchange capacity based on soil organic carbon. Journal of Agricultural and Biological Science, 3(4), 41–45. Rowell, D. (1994). Soil science methods and applications ((First ed.). England: Pearson Education Limited. Schnitzer, S., & Khan, S. U. (1978). Soil organic matter. New York, NY 10010, U.S.A: Elsevier Scientific Publishing Company. G.Selassie, Y., Amare, T., Terefe, A., Yitaferu, B., Wolfgramm, B., & Hurni, H. (2013). Soil Properties and Crop Yields along the Terraces and Toposequece of Anjeni Watershed , Central Highlands of Ethiopia. Journal ofAgricultural Science, 5(2), 134–144. https://doi.org/10.5539/jas.v5n2p134. Selassie, Y. G., Anemut, F., Addisu, S., Abera, B., Alemayhu, A., Belayneh, A., & Getachew, A. (2015). The effects of land use types, management practices and slope classes on selected soil physico-chemical properties in Zikre watershed, North-Western Ethiopia. Environmental Systems Research, 4(1), 3. http://dx.doi. org/10.1186/s40068-015-0027-0. Soares, M. R., & Alleoni, L. R. F. (2008). Contribution of soil organic carbon to the ion exchange capacity of tropical soils. Journal of Sustainable Agriculture, 32(3), 439–462. http://dx.doi.org/10.1080/10440040802257348. Taddese, G. (2001). Land degradation: A challenge to Ethiopia. Environmental Management, 27(6), 815–824. http://dx.doi.org/10.1007/s002670010190. Tisdale, S. L., & Nelson, W. L. (1975). Soil fertility and fertilizers ((3rd ed.). . Macmillan. Van Reeuwijk, L. (2002). Procedures for Soil Analysis, Six edition, Technical paper 9. Wageningen, The Netherlands. Winowiecki, L. (2015). Landscape - Scale Assessments of Soil Health: Local Determinants of Soil Organic Carbon in Ethiopia.
