International Soil and Water Conservation Research 5 (2017) 231–240

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International Soil and Water Conservation Research

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

art ic l e i nf o a b s t r a c t

Article history: Community-based Soil and Water Conservation (SWC) practices have been adopted in the Tigray region
Received 16 March 2017 since 1991 for restoration of the degraded landscape. The effects of those conservation measures on
Received in revised form physico-chemical properties of soil were limitedly studied. Thus, this study evaluated the effects of SWC
22 June 2017
on selected soil properties in the Middle Silluh Valley, Tigray region, Northern Ethiopia. The study
Accepted 29 June 2017
considered conserved landscapes (terraced hillside, terraced farmland and exclosure area) and non-
Available online 8 July 2017
conserved landscapes (non-terraced hillside, non-terraced farmland and open grazing land) for com-
Keywords: parison using a one-way analysis of variance (ANOVA). A total of 24 samples were collected from each
Land degradation landscape at a depth of 10–30 cm. The results indicated that mean bulk density (BD) was low on terraced
Soil and water conservation
hillside, non-terraced hillside and exclosure area. Sand and clay content were significantly different at
Soil properties
P o0.05 for the six landscape categories. Higher mean organic matter was observed in the conserved
Middle Silluh Valley
Ethiopia 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 re-
lationships. 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-NC-
ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction Tamene, and Vlek (2013) addressed that the inappropriate agri-
cultural practices and conversion of marginal land into cultivation
Land degradation is a major problem in Ethiopia. It has a ne- and grazing land have led to severe land degradation in the
gative impact on agricultural economy and the natural environ- Ethiopian highlands.
ment Taddese (2001) clearly explained that the major causes of Land degradation increases vulnerability of people to the ad-
land degradation in Ethiopia are the rapid population increase, soil verse effects of climate variability and change, by reducing Soil
erosion, deforestation, low vegetative cover and unbalanced crop Organic Carbon (SOC) concentration and water holding capacity,
and livestock production. which in turn reduces agricultural productivity and local resource
Similar idea was also reported by Bishaw (2001), Negusse, Ya- assets (Mengistu, Bewket,& Lal, 2015; Damene et al., 2013; Pender,
zew, and Tadesse (2013) that the rapid population growth, im- Ringler, Magalhaes, & Place, 2012). In order to solve such de-
proper land resource management and utilization are the principal gradation problem, the Regional Government of Tigray in colla-
causes of increased runoff and soil erosion in the country which boration with some other non-governmental organizations like
resulted in declining agricultural productivity, water scarcity and Gesellschaft Für Internationale Zusammenarbeit (GIZ), World Food
continuing food insecurity. The fertility of soil could be diminished Pprogramme (WFP), Relief Society of Tigray (ReST), Adigrat Dio-
through time due to land degradation. Moreover, Damene, cesan Catholic Secretariat (ADCS) have developed strategies to
work hand in hand with local communities on many SWC mea-
sures such as, construction of soil bund, stone bund, runoff control,
n
Corresponding author at: Department of Geography and Environmental Studies, and water harvesting structures, setting aside exclosure areas and
Mekelle University, P.O. Box 231, Mekelle, Ethiopia.
nutrient management.
E-mail address: solomonhw@yahoo.com (S. Hishe).
Peer review under responsibility of International Research and Training Center It has been addressed by many researchers such as Geb-
on Erosion and Sedimentation and China Water and Power Press. reegziabher 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/).
232 S. Hishe et al. / International Soil and Water Conservation Research 5 (2017) 231–240

(2007) that in order to minimize land degradation and restore and recorded information about land use, average gradient, human
degraded landscapes, a lot of efforts have been done in Ethiopia influence and types of SWC structures.
through SWC measures. It has been addressed by Bewket and
Stroosnijder (2003) that local level investigation is essential to 2.3. Laboratory analysis
design area-specific and appropriate rehabilitation and manage-
ment interventions. Within a broader context of understanding The soil samples were air dried, crushed and sieved through a
land degradation and SWC, the specific objectives of the present 2 mm mesh sieve for analysis. The soil properties considered in
research paper are: (1) to evaluate the physico-chemical proper- this study were Soil Organic carbon (SOC), Soil Organic matter
ties of soil; (2) to compare the two situations of conserved and (SOM), total nitrogen (TN), pH, texture, bulk density, exchangeable
non-conserved landscapes impacted by SWC measures. Hence, the bases (Ca2 þ , Mg2 þ , Na þ and K þ ), available phosphorus (av. P),
effectiveness of such intervention on improving the fertility of soil percentage base saturation (PBS), and cation exchange capacity
biophysical and chemical properties shall be studied for better (CEC). The analysis for exchangeable cations, CEC and avail. P were
recommendation to policy makers. 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
2. Materials and methods at Mekelle University.
Bulk density was determined using the Walkley and Black
2.1. Study area description method (Black, 1965) method. Soil pH and texture were de-
termined using the glass electrode and hydrometer method as
The study was carried out in the Middle Silluh Valley (MSV), suggested by Van Reeuwijk (2002), Haldar and Sakar (2005), re-
northern highlands of Ethiopia with an area coverage of 490 km2. spectively. Soil Organic Matter (SOM) was calculated by multi-
According to the local agro-ecological classification system which plying SOC with a factor of 1.724 after determining the organic
mainly relies on altitude and temperature, the study area is carbon using Walkley-Black rapid titration method as described in
characterized by Woynadega (midland) and Dega (highland) Haldar and Sakar (2005). Total Nitrogen (TN) was determined by
(Mengistu, 2006). The River Sulluh flows in the middle of the the Micro Kjeldhal process as described in Landon (1984). The
study area in a north-south direction. The Middle Silluh Valley has determination of available Phosphorus (P) was made using the
an altitudinal range of 1818–2744 m.a.s.l. Within the study area, 28 Oslen et al. (1954) method as described in Van Reeuwijk (2002).
lower administrative units, locally called “Tabia” were situated The measurement of individual exchangeable cations (Na þ , K þ
from Kilte_Awulaelo, Saesie Tsaeda Emba and Hawzen districts. Ca þ þ , and Mg þ þ ) and Cation Exchange Capacity (CEC) was done
Out of the 28 tabias, only 15 tabias are fully situated within the by adding 1 M ammonium ethanoate (acetate) solution at pH 7 as
basin and the remaining have 50% or more of their territory. Mean suggested by Haldar and Sakar (2005), Rowell (1994).
annual rainfall from three stations for the period 2006–2015 is
536 mm and the minimum and maximum mean annual tem- 2.4. Data analysis
perature are is 10.7 °C and 26.6 °C respectively. The dominant soils
are Cambisols (moderately developed soils); Luvisols (evidence The different physical and chemical properties of soil samples
with accumulation of clay/organic matter); and Leptosols (highly mentioned as a dependent variables and landscape category as
calcareous material). The slope gradient of the study area also independent variable were statistically tested. From each six
ranges from flat (o 0.2%) to very steep (460%). The study area is landscape function, four samples were taken for the computation.
characterized by semi-arid environment where farmers dom- Analysis of variance (ANOVA) using the Statistical Package for
inantly produce wheat, barely, kerkaeta (mixed of barley and Social Scientists (SPSS 20) to evaluate whether significant differ-
wheat), Eragrostis tef, millet and beans. The predominant economic ence exists among the landscape categories or not as the data
activity of the inhabitant is subsistence agriculture. contains more than two factors. Therefore, the ANOVA test using
Monthly rainfall is high in the months of July and August in all Post Hoc Test of Least Significance Difference (LSD) at alpha value
the three stations. On the other hand, January and February are of 5% was applied in the analysis. The mean difference is calculated
driest months. May and June are the hottest months (Fig. 2). by subtracting the mean of one landscape category from the mean
of other respective landscape categories under a given dependent
2.2. Soil Sampling and data collection variable.

Soil samples were collected from 24 sample sites in August

2016 (Fig. 1). Different soil sampling method have their own ad- 3. Results and discussion
vantages and drawbacks Landon (1984). suggests judgment sam-
pling for selection of typical sites is feasible to represent large 3.1. Soil physical properties
areas. Accordingly, we used judgment sampling to take re-
presentative soil samples from conserved and non-conserved sites. The soil physical properties were different under different
The sites were four each from terraced hillside, non-terraced landscape categories (Table 1). Mean bulk density (BD) was low in
hillside, terraced farmland, non-terraced farmland, open grazing the terraced hillside, non-terraced hillside and exclosure area.
land and exclosure area. After removing the first 10 cm topsoil to SMC, BD, sand, silt and clay contents were significantly different
exclude the presence of nematodes. Soil samples were taken using under different landscape categories.
augur from 10 to 30 cm depth. One kg of soil from each sample site A one-way analysis of variance (ANOVA) was conducted to
was packed in a plastic bag for laboratory analysis. In order to explore the impact of different landscape category (conserved and
determine soil moisture content later in the lab, 200 g soils were non-conserved types) on soil physical property parameters (Bulk
collected from each sample site and measured on scale in-situ. density fertility, soil moisture content, sand, silt and clay content)
Moreover, for determination of bulk density, 24 undisturbed soil status. For the sand content, there is statistically significance dif-
samples were collected using core samplers. In characterizing the ference at P o0.05 level for the six landscape groups: F(5, 23) ¼
sample sites, we followed a similar approach as in Abegaz, Wi- 4.179, Po 0.05. Similarly, for the clay content, there is statistically
nowiecki, Vågen, Langan, and Smith (2016); Winowiecki (2015) significance difference at P o0.05 level for the six landscape
 S. Hishe et al. / International Soil and Water Conservation Research 5 (2017) 231–240 233

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 only statistically significant difference at P o0.05 (Table 2) for the
lowest in NTFL and GL (20%). For the remaining bulk density, soil comparison between non-terraced farmland with terraced hillside
moisture and silt content there was no statistically significance landscape which is more by 0.19 of the mean. The non-conserved
difference at P o0.05. (Table 1b) landscape (NTHS, NTFL and GL) were found significantly higher
mean value of BD than the conserved landscapes of THS, TFL and
3.1.1. Bulk density ExA (Table 2). This could be due to the presence of significantly
The highest mean bulk density (BD) was recorded in the non- higher OM resulted from conservation measures and decay of
terraced farmland followed by terraced farmland and grazing land plant residues. In line to this, similar result was reported by
1.65 g/cm³, 1.60 g/cm³ and 1.60 g/cm³ respectively (Table 1, a). For G.Selassie et al. (2013), Demelash and Stahr (2010), Selassie et al.
the bulk density dependent variable using the LSD test, there is (2015), Abay, Abdu, and Tefera (2016). Terraced farmland was
234 S. Hishe et al. / International Soil and Water Conservation Research 5 (2017) 231–240

Table 1 farmlands respectively where more textural soil was dominant

Effects of changes in landscape on some selected physical properties in the Middle (Table 3). This could probably be due to the combination of factors
Silluh Valley, Northern Ethiopia, and ANOVA results.
such as continuous cultivation leading to high soil porosity and the
(a) Landscape Mean of selected soil physical properties dominancy of course soil textural class (Table 4). For soil moisture
content as dependent variable using the Least Significance Dif-
SMC (cm³/cm³) BD (gm/cm³) Sand (%) Silt (%) Clay (%) ference (LSD) test, there is just measurably critical distinction at P
o0.05 for the comparison between non-terraced farmland with
THS 17.21 1.46 36.00 31.00 33.00
NTHS 18.81 1.50 39.50 25.00 35.50 grazing land (Table 3).
TFL 19.20 1.60 62.00 13.50 26.50
NTFL 25.14 1.65 70.00 9.50 20.50 3.1.3. Soil texture
ExA 15.00 1.51 51.00 24.00 25.00 3.1.3.1. Sand content. The soil textures of the study area was as-
GL 11.09 1.60 60.50 19.00 20.50
(b) F, mean and ANOVA statistics
sessed based on proportion of three mineral particles, sand, silt
F 1.346 1.513 4.179 2.283 4.193 and clay in a soil. The sand texture was relatively highest mean
Mean (n ¼24) 17.738 1.526 53.17 20.33 26.50 value in the non-conserved area (NTHS, NTFL and GL) than the
P 0.290 0.325 0.011* 0.90 0.011* conserved once (TSL, TFL and ExA) (Table 1a). The non-terraced
THS-Terraced Hillside; NTHS-Non-Terraced Hillside; TFL-Terraced Farmland; NTFL-
farmland had shown the highest mean sand fraction (70%) in
Non-terraced farmland; ExA-Exclosure area; GL-Grazing land. comparison to the terraced farmland (62%). On the contrary, the
*
Significant level at p o 0.05 & & each landscape categories contain four sample lowest sand content was observed in the terraced hillside (36%)
sites and Values are average of 24 samples. which is the effect of conservation practices to accumulate better
organic matter and clay materials. The study area was mostly
more by 26.0 and 22.5 of the mean in comparison to terraced characterized by Enticho sandstone and Adigrat sandstone parent
hillside and non-terraced hillside respectively. According to material (Fig. 1). Other reason may be trampling by grazing ani-
Landon (1984) classification, the soils with mean 1.53 g/cm3 bulk mals could facilitate the export of finer clay and silt particles
density ranges with soils showing root restriction which reduces through wind and water erosion.
the plants ability to exploit the plants environment. A strong ne-
gative significant correlation was found (r ¼  0.75) between CEC 3.1.3.2. Silt content. The silt content was higher in the conserved
and bulk density of soil samples (Fig. 3(b)). This was evidenced by landscape (THS, TFL and ExA) than in the non-conserved land-
Schnitzer and Khan (1978), that the increased aggregation of CEC scape (NTHS, NTFL and GL). This result was in concurrence with
due to clay content may lower bulk density. Bezabih, Aticho, Mossisa, and Dume (2016) who found higher
mean silt proportion in woodland and fallow land than cultivated
3.1.2. Soil moisture content (SMC) land without soil bunds. However, the results of the silt content in
The soil samples were collected during the rainy season in the this study was not in line with Demelash and Stahr (2010), Men-
month of August 2016, and the distribution of rainfall throughout gistu et al. (2015); who found that the silt content was high in
the study areas was almost homogeneous. SMC is generally re- non-conserved rather than conserved land which is characterized
ported as the ratio of the mass of water present in a soil sample to with basaltic Trap series of volcanic eruptions parent material.
the mass of the sample after it has been dried at 105 °C to a On the other hand, the smallest proportion of silt content
constant weight (Haldar & Sakar, 2005; Van Reeuwijk, 2002). The (9.5%) was recorded in the non-terraced farmland (Table 1a). A
lowest mean soil moisture content was observed in the grazing statistically significance difference was observed at P o0.05 for
lands (11.09%) which characterized with less vegetation cover and terraced hillside contrasted with terraced farmland and non-ter-
slope ranges between 2% and 17%. This could facilitate to loose raced farm land.
water without infiltrating into the soil and increased the eva-
poration rate to the atmosphere. On the contrary, the highest 3.1.3.3. Clay content. The proportion of clay content in both the
mean value of SMC was observed in the terraced and non-terraced 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 Landscape Category (I) Landscape Category (J) Mean difference (I-J) Sig. 95% confidence interval

Lower bound Upper bound

Bulk Density (gm/Cm3) NTFL THS 0.188* 0.039  0.365  0.01

Soil Moisture (%) NTFL GL 14.047* 0.024 2.030 26.06
Sand Content (%) TFL THS 26.000* 0.012 6.49 45.51
TFL NTHS 22.500* 0.026 2.99 42.01
NTFL THS 34.000* 0.002 14.49 53.51
NTFL NTHS 30.500* 0.004 10.99 50.01
GL THS 24.500* 0.017 4.99 44.01
GL NTHS 21.000* 0.036 1.49 40.51
Silt Content (%) THS TFL 17.500* 0.030 1.90 33.10
THS NTFL 21.500* 0.010 5.90 37.10
Clay Content (%) THS NTFL 12.500* 0.011 3.29 21.71
THS GL 12.500* 0.011 3.29 21.71
NTHS TFL 11.000* 0.022 1.79 20.21
NTHS NTFL 15.000* 0.003 5.79 24.21
NTHS ExA 10.500* 0.028 1.29 19.71
NTHS GL 15.000* 0.003 5.79 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.
 S. Hishe et al. / International Soil and Water Conservation Research 5 (2017) 231–240 235

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 non-conserved at Zikrie sub watershed.
hillside (35.5% and 33% respectively) where better vegetation The one way ANOVA Post Hoc Test of LSD revealed that clay
cover exists. This can be basically the direct result of the chemical content on a terraced hillside showed statistically significant dif-
weathering of silicate minerals from the prevalence sedimentary ference at P o0.05 with non-terraced farm land and grazing land.
rocks in the study area and the vegetation cover protects from The clay content of the terraced hillside shows in a higher mean
washing away. The lowest proportion of clay was observed equally difference of 12.5 in relation to both the non-terraced farm land
(20.5%) in the non-terraced farm land and grazing land. This is true and grazing land (Table 2).
that clay materials are fine particles that can be easily transported
to other areas, unless different conservation measures are applied. 3.1.4. Soil textural classes
The mean values of clay content in the conserved landscape (TFL The major textural classes for the study sample sites are pro-
and ExA) was higher than the comparing non-conserved land- vided in Table 3. Each of the textural classes listed in Table 3 are
scape (NTFL & GL). Similar result was reported by Mengistu et al. according to the different landscape category considered in the
(2015) indicating that in all landscape position with conservation study objective. In the terraced hillside, 75% of the textural classes
practice at Minchet sub watershed shown higher clay content than are in the loamy clay with the slope range 9–39% make up finely
236 S. Hishe et al. / International Soil and Water Conservation Research 5 (2017) 231–240

Table 3 Table 5
Effects of changes in landscape on soil textural classes in the Middle Silluh Valley, Effects of changes in landscape on selected soil chemical properties in the Middle
Northern Ethiopia. Silluh Valley, Northern Ethiopia.

Landscape Average Textural classes of landscape categories (%) Slope (%) Landscape Mean of some soil chemical properties
Category
Clay Clay Loam Sandy Clay Sandy Sandy pH SOC (%) SOM (%) TN (%) Av. P (ppm)
Loam Clay loam
Loam THS 6.0 2.34 4.04 0.19 0.72
NTHS 6.0 1.72 2.01 0.14 0.71
THS – 75 – – 25 – 9–39 TFL 6.0 0.70 1.20 0.10 0.56
NTHS 25 25 – 25 25 – 9–19 NTFL 5.5 0.63 1.09 0.05 0.45
TFL 25 – – – 75 – 5–10 ExA 6.0 1.07 1.84 0.07 0.67
NTFL – – – – 50 50 4–10 GL 6.0 0.79 1.37 0.06 0.61
ExA – – 25 – 25 50 5–29
GL 25 25 50 2–17 THS-Terraced Hillside; NTHS-Non-Terraced Hillside; TFL-Terraced Farmland; NTFL-
Non-terraced farmland; ExA-Exclosure area; GL-Grazing land.
THS-Terraced Hillside; NTHS-Non-Terraced Hillside; TFL-Terraced Farmland; NTFL-
Non-terraced farmland; ExA-Exclosure area; GL-Grazing land. *Significant level at
the time a landscape is conserved, the higher the effect on organic
p o0.05 & each Values are average of 4 samples.
matter accumulation mainly due to the decay of leaves and litter
materials and decomposed in to humus. This result comes to an
Table 4
agreement with findings of Mengistu et al. (2015), Negusse et al.
Mean and significance level of selected soil chemical properties in the Middle Silluh
Valley, Northern Ethiopia. (2013).
Results of the preliminary correlation analysis as indicated in
pH SOC (%) SOM (%) TN (%) Av. P (ppm) Fig. 3(c) and (d) shows that there was very weak positive corre-
lation between CEC and organic matter content (r ¼0.03) and be-
F 0.231 3.344 3.344 1.952 0.303
Mean 5.95 1.21 2.085 0.101 0.617 tween CEC and clay content (r ¼0.05). This result is in-line with
P 0.944 0.026* 0.026* 0.135 0.905 the result found by Montecillo (1983). The results of the analysis
*
indicates that there was statistically significant (p o 0.05) differ-
Significant level at p o 0.05.
ence in OM content among the different landscape categories
(Table 4). Rowell (1994) described that soil organic matter is the
textured soils. The non-terraced hillside with the slope range be- central to the maintenance of soil fertility: mineralization of N, P
tween 9–19% was also characterized 25% by clay and 25% clay loam and S, the soils ability to hold nutrient cations, structural ability
textural classes which contains a higher proportion of clay and and water holding capacity are all affected by OM content
relatively lower amounts of sand and silt. This is relatively good for Schnitzer and Khan (1978). also agreed that organic matter im-
plant growth than clay since it has more open spaces that en- proves infiltration, decrease evaporation, improve drainage in fine
courage aeration and more water holding capacity to be readily textured soils, foster more extensive and deeper root systems.
available for plants' use. In the terraced farm land, non-terraced In our study, the soil organic carbon (SOC) in the terraced
farm land, area exclosure and grazing land areas, the soil texture hillside was noted higher than in the other sampled landscapes.
class is dominated by sandy clay loam to sandy loam. As the study
However, a small difference in SOC concentration was found be-
area is geologically dominated by Enticho sandstone and Adigrat
tween THS and NTHS landscape, and moderate difference in ExA
sandstone, the abundance of more sandy texture in those rela-
landscape (Table 5). The lowest mean OC was found in TFL ¼0.7%;
tively gentle slope areas was greatly expected.
NTFL ¼0.63% and GL ¼0.79%. As soil organic carbon does not pro-
vide alone any essential nutrient to crops, there is close relation-
3.2. Soil chemical properties
ships between SOC and SON over a wide range of soils (Gaiser &
Stahr, 2013) and are also strongly correlated. The accumulation of
The effects of independent variables in the study area (area
SOC is one of the initial soil forming processes and is determined
exclosure and grazing land, terraced hillside and non-terraced
by physical, chemical, biological and anthropogenic factors with
hillside, terraced farmland and non-terraced farmland) on the
complex interactions (Gaiser & Stahr, 2013) (Table 6).
considered dependent variable chemical properties of soils were
The average mean value of soil organic carbon was arranged by
statistically tested. The study area was characterized with het-
THS 4NTHS 4ExA 4GL 4TFL4 NTFL (Table 5). This shows that a
erogeneous landscape and land use types. SWC conservation
direct relationship with the vegetation cover and conservation
measures through community mobilization work was applied to
measure applications and inversely with intensive human and li-
reduce soil erosion, increase infiltration and improve the vegeta-
tion cover in non-cultivable land and maximize the fertility of soil vestock interference. Similar results were also found by Bezabih
in general.
Table 6
Critical levels for some soil fertility parameters.
3.2.1. Soil organic matter and soil organic carbon
The results of the analysis indicates that there was statistically Status Critical Level
significant (p o 0.05) difference in OM content among the dif-
ferent landscape categories (Table 5). The highest mean organic Soil pH TN (%) OM (%) Av. P (mg/kg)* K þ (mg/kg)

matter was recorded in the conserved landscape (THS ¼ 4.04%, Very Low o 5.5 o 0.1 o2.0 0–15 o 90
TFL¼ 1.20% and ExA ¼ 1.84%) as compared to the corresponding Low 5.6–6.5 0.1–0.15 2.0–3.0 15–30 90–190
non-conserved landscape (NTHS ¼ 2.01%, NTF ¼ 1.09%, and GL ¼ Optimum 6.6–7.3 0.15–0.3 3.0–7.0 30–80 190–600
1.37%). These variations are the results of soil and water con- High 7.4–8.4 0.3–0.5 7.0–8.0 80–150 600–900
Very High 48.4 40.5 48.0 4150 4900
servation schemes applied in the area. For instance, the highest
organic matter in situ (6.56%) at village Samuel of Tabia GiraAras in Source: Table adopted from Agricultural Transformation Agency (ATA), Addis
Hawzen district was recorded from the terraced hillside conserved Ababa, 2014.
by the local community since 1984. This indicates that the longer *
¼ 1 mg/kg is equal to 1 ppm.
 S. Hishe et al. / International Soil and Water Conservation Research 5 (2017) 231–240 237

Table 7 correlation between TN and SOM content shows strong positive

One Way ANOVA multiple comparison for different soil fertility among landscape relationship (%TN ¼ -0.0034 þ0.05 SOM%, r ¼0.97) (Fig. 3a).
categories using Post Hoc Test of LSD in the Middle Silluh Valley, Northern Ethiopia.
In the one way ANOVA at Po0.5 level of significance, TN was
Dependent Land Ca- Land Ca- Mean dif- Sig. 95% confidence not statistically significant difference among the landscape cate-
Variable tegory (I) tegory (J) ference interval gories (Table 4). However, the multiple comparison for TN content
(I-J) among landscape categories using Post Hoc Test of LSD was eval-
Lower Upper uated and the result indicates a terraced hillside was observed
bound bound
statistically significant difference at P o0.05 with non-terraced
SOC (%) THS TFL 1.65* 0.006 0.53447 2.75826 farm land; exclosure area and grazing land. The mean TN content
THS NTFL 1.71* 0.005 0.60217 2.82595 results of terraced hillside was higher by 0.14, 0.12 and 0.13 of the
THS ExA 1.28* 0.027 0.16655 2.39033 mean in relation to NTFL, ExA and GL respectively (Table 7). Ac-
THS GL 1.55* 0.009 0.43887 2.66266
cording to some studies, total nitrogen content in the top 15–
SOM (%) THS TFL 2.84* 0.006 0.92143 4.75524
THS NTFL 2.96* 0.005 1.0381 4.87194 20 cm of surface soils ranges from 0.01% (or even less in desert
THS ExA 2.20* 0.027 0.28713 4.12093 soils) to more than 2.5% in peats (Prasad & Power, 1997). Soil ni-
THS GL 2.67* 0.009 0.75662 4.59043 trogen is derived primarily from atmospheric nitrogen gas (N2),
TN (%) THS NTFL 0.138* 0.022 0.02244 0.25266 however soil micro-organisms, both free living and symbiotically
THS ExA 0.123* 0.038 0.00739 0.23761
THS GL 0.133* 0.026 0.01789 0.24811
associated with plants fix N2 to produce organic nitrogen (Rowell,
1994). When plant residues decompose, much of the nitrogen they
THS-Terraced Hillside; TFL-Terraced Farmland; NTFL-Non-terraced farmland; ExA- contain will undergo several microbial conversions and will
Exclosure area; GL-Grazing land. eventually end up back as nitrates (Prasad & Power, 1997). Hence,
*
The mean difference is significant at the 0.05 level. total nitrogen is one of the essential nutrient for plant and animals.

et al. (2016), Khan, Hayat, Ahmad, Ramzan, and Shah (2013); that 3.2.3. Available phosphorus
less amount of SOC was detected in farmlands, which could be due As indicated in the Table 5, the lowest percent's of available
to the poor land management and frequent destabilization of the phosphorus (0.45 ppm) was in the pH 5.5 in the non-terraced
soil. The one-way ANOVA showed that landscapes under different farmlands. The relatively higher percentage of available phos-
management had a significant effect on soil organic carbon. As phorous was also observed in the THS and NTHS landscape cate-
indicated in Table 7, a terraced hillside was observed statistically gories which have a mean pH 6.0 value uniformly (Table 5). Ac-
significant difference at P o0.05 with terraced farmland, non- cording to ATA (2014) critical level classification for available
terraced farmland, exclosure area and grazing land. The mean SOC phosphorus (Table 6), there was very weak status of available
content results of terraced hillside was higher by 1.65 from TFL, by phosphorus in all the landscape categories of the soil. According to
1.71 from NTFL, by 1.28 from ExA and by 1.55 from GL respectively. Landon (1984) also, the available phosphorus in the study area was
However, there was no statistically significance difference shown classified as acutely deficient (o 3 ppm P.). This indicates that
between terraced hillside and non-terraced hillside due to their there is high deficiency of available phosphorus in the study area.
vegetation cover was almost similar and the degree of decom- Phosphorus is one the most important element in the soil nu-
position of plant residue to be the same. trient required by plant. Plants grow slowly when the levels of
A simple regressions were calculated between CEC (me/ 100 g available phosphorus in the soil is low. The presence of organic
soil) as the dependent variable and clay content (%) and SOC (%) as phosphorus content depends upon a number of factors such as
the independent variable. The Pearson's correlation between SOC climate, vegetation, soil texture, land use pattern, fertilizer prac-
and clay content shows strong positive relationship (%Clay¼ tices, drainage, irrigation and moreover the availability of phos-
19.35 þ5.91 SOC%, r ¼0.67 (Fig. 3f). This result is in consistent with phorus in the soil is greatest in the pH range 6.0–6.5 (Prasad &
other studies conducted by Soares and Alleoni (2008) in the areas Power, 1997).
of native vegetation in State of São Paulo, Brazil, where SOC con- In general, we can conclude that Middle Silluh Valley was
tents were strongly associated with the clay contents and other by characterized by low available phosphorus and this could be due
Olorunfemi, Fasinmirin, and Ojo (2016) conducted in Ekiti State, in to the existence of acidic soil (mean pH with 5.5–6.0) throughout
the forest vegetative zone of Nigeria. On the other hand, a lower and the presence of low organic matter. This result is supported by
positive coefficient was obtained for a correlation of CEC and SOC Tisdale and Nelson (1975) who found available phosphorous de-
(CEC ¼ 3.34 þ 0.063 SOC%, r ¼ 0.031) (Fig. 3e). This is in contrast creased with higher acidic soil pH. This is true that nutrients are
to the findings of Olorunfemi et al. (2016), Rashidi and Seilsepour recycled by decomposition through the soil organic matter and
(2008) who reported higher correlation between CEC and SOC. provides more than 90% nitrogen and about 50–60% phosphorus
According to Evans 1996, the results of our finding was classified and sulfur (Osman, 2013). At low or acidic pH (o 5.5), phosphorus
as very weak positive correlation. is combined with Al, Fe, and Mn as their polyphosphates and at
high pH (48.0), P is precipitated with Ca (Landon, 1984; Osman,
3.2.2. Total nitrogen (TN) 2013). Both at soil acidity and alkalinity, availability of phosphorus
The highest mean total nitrogen in the study area was found in is reduced to deficiency levels. Availability of P is usually higher in
the THS, and TFL for 0.19% and 0.10% respectively. The existent of the pH range of 6.5 and 7.0 (Osman, 2013). That is why one of the
better TN in these two landscape was due to the presence of most important benefits of liming acidic soil is improving phos-
physical SWC measures in general; and in the TFL farmers have phorus availability. Moreover, the addition of phosphorus through
applied manure and commercial fertilizer every year for max- fertilization can improve its availability.
imizing their crop production. In the NTHS, higher mean TN con-
tent was observed (0.14) and this could be due specifically to the 3.2.4. Exchangeable bases
contribution of nitrogen fixing plants. In general, the findings were Both the conserved and non-conserved landscapes in the study
in agreement with Alemayehu (2007), Amare et al. (2016), Mulu- area have shown non-significant difference among the mean va-
geta and Karl (2010), Selassie et al. (2015) stated that SWC sup- lues of exchangeable Ca þ þ , K þ , Mg þ þ , Na þ and sum of ex-
plemented with rehabilitated vegetation cover had positive impact changeable bases. The mean relative abundance of basic cations in
in improving the total nitrogen of the soil. The Pearson's the exchange complex for all the landscape categories in the study
238 S. Hishe et al. / International Soil and Water Conservation Research 5 (2017) 231–240

Table 8 and BD (r¼ –0.747, n ¼ 24, p o 0.001); SOM and sand content (r¼
Mean, Suggested quantity, and significance level of Exchangeable Bases, CEC, and –0.614, n ¼ 24, p o 0.01) (Table 9).
PBS in the Middle Silluh Valley, Northern Ethiopia.
The SOM has shown strong positive significant correlation with
Exchangeable Bases† CEC† PBS (%) 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
Measurement Ca K Mg Na SEB 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
F 0.232 0.110 0.074 1.543 0.227 0.231 0.321
Mean 1.943 0.011 0.245 0.0247 0.222 3.43 54.18 0.958 respectively (Table 9). The available phosphorus has also
Suggested Quantity♀ 45 40.5 40.5 o 1.0 – 415 4 50 shown negatively moderate significant with Na þ , Ca þ þ , Mg þ þ ,
P 0.943 0.989 0.995 0.222 0.946 0.945 0.894 SEB, CEC and PBS at r between  0.521 to  0.591 where p o 0.01
†
(Table 9).
meq. 100 g  1; CEC ¼ Cation Exchange capacity; PBS ¼ Percentage Base Sa-
turation; SEB-Sum of Exchangeable Bases.
♀
¼ Suggested quantity adapted from Landon (1984). Significance level at
P o 0.05. 4. Conclusion

The government of Ethiopia is trying to reverse the degraded

samples were in the order of Ca þ þ 4 Mg þ þ 4 Na þ 4 K þ landscape through different land conservation measures with the
(Table 8). The results of this study was in agreement with Amare participation of the local communities. This investigation has also
et al. (2016), Amdemariam, Selassie, Haile, and Yamoh (2011), demonstrated on the effects of different methods of soil and water
Lelago, Mamo, and Haile (2016), Hailu, Moges, and Yimer (2012), conservations applied on the physical and chemical properties of
who found a non-significant variation in exchangeable bases soil in the Middle Silluh Valley, northern Ethiopia. The conserved
among different soil and water conservation measures. Similarly,
landscape categories (TFL and ExA) shown better clay content than
the difference in the sum of exchangeable base (SEB) was not
the non-conserved landscape categories (TFL and GL). On the other
statistically significant at P o0.05 among the mean of different
hand the non-conserved landscape (NTHS, NTFL and GL) were
landscape categories.
observed to have a significantly higher mean value of BD than the
conserved landscapes (THS, TFL and ExA). As many studies re-
3.2.5. Cation exchange capacity (CEC)
vealed, the lower BD in the conserved landscape could be due to
The cation exchange capacity (CEC) is a measure of the number
the presence of significantly higher SOM resulting from con-
of adsorption sites per unit weight of soil at a particular pH. The
servation measures and decay of plant residues.
soil samples collected and analyzed for the study area indicates
The SWC measures implemented on the hillside of the study
that there is no statistically significant variation among the mean
area have also shown great impact on the improvement of the
values for the CEC for different landscape category. The result of
SOM and TN of the soil. This was a good indicator for further ap-
this study was in agreement with Hailu et al. (2012), Mulugeta and
plication of SWC measures on other degraded hillside landscapes
Karl (2010) who found a non-significant variation in CEC among
of the region. Both the conserved and non-conserved landscapes
different soil and water conservation measures.
in the study area have shown non significance difference among
According to Jones (2012), soils with CEC within 1–10 meq/
the mean values of exchangeable Ca þ þ , K þ , Mg þ þ , Na þ and sum
100 g range are characterized with high sand content, low organic
of exchangeable bases. The sandstone parent material of the study
matter content and low water holding capacity. Hence with an
area and acidic nature of the soil exacerbates the deficiency of
average mean of 3.43 meq/100 g of soil CEC in the study area in-
exchangeable cations, despite the fact that SWC measures are
dicates that there was an existence of physical ramifications as-
sociated with high sand content and geologically the study area is practiced.
dominated with sandstone parent materials (Enticho and Adigrat In general, the effects of SWC intervention at the Middle Silluh
sandstone). As a result, the soil could be exposed for low capacity River were found to have pronounced positive effects on some
of holding plant nutrient elements and loss by leaching from the selected soil physical and chemical properties. The different con-
soil profile. As a recommendation to the terraced and non-terraced servation measures applied in the area like bench terrace, soil
farm lands, the application of large amount of fertilizer or lime is bund, stone bund, check dam, trench, preserving area exclosure,
required to obtain better crop production. Based on Landon (1984) and re-afforestation were significantly important not only to pro-
class rating, the mean CEC of the study area is very low (o5 meq/ tect soil erosion, but also to maintain soil fertility. In order to
100 g of soil) and such observation of low CEC in a study area achieve the desired target and be sustainable, the different forms
indicates the requirement of better management of the land. of conserved landscapes should be prevented from the inter-
ference of human being and livestock for better recovery of natural
3.3. Correlation matrix of physical and chemical soil properties resources.

A partial correlation was carried out to explore the relationship

between each single property of a soil and the other 16 parameters Acknowledgement
considered in the analysis of this study. The correlation between
total nitrogen (TN) and soil organic matter (SOM) was very strong The authors would like to thank TRECCAfrica II for providing
positive partial correlation, r ¼ 0.928, n ¼24, p o 0.01. Moreover, scholarship to the principal investigator to study at the Institute of
there was also a positive moderate correlation with clay content Resources Assessment, University of Dar es Salaam, Tanzania. The
(r ¼0.613), however, TN was strong negatively correlated with BD, Meteorological agency of Mekelle branch also for supplying cli-
r ¼ 0.742. This result is directly similar with the findings of Abay matic data. We thank Mekelle University, Department of Earth
et al. (2016) who studied on the central highlands of Ethiopia. Sciences and Department of Land Resources Management and
Likewise, SOM was strong positive significantly correlated with Environmental Protection for their soil analysis. Many thanks to
clay content, and moderate positive significantly correlated with the College of Social Sciences and Languages in Mekelle University
silt content (r ¼ 0.673 and r ¼ 0.426) respectively. On the contrary, for providing vehicle to the fieldwork during soil sample collec-
there was a strong negative significant correlations between SOM tion. Our appreciation also to Dr. Luca Ongaro for proof reading the
 S. Hishe et al. / International Soil and Water Conservation Research 5 (2017) 231–240 239

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, SOM-
manuscript. The authors would like to thank the three anonymous

TN

1
reviewers for their valuable comments and suggestions on the
improvement of this manuscript. The first author is also grateful to

0.928**
Mekelle University for granting research fund under registration
SOM

number CRPO/CSSL/PhD/003/08.

1
1.000**
0.928**
SOC

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