ORIGINAL RESEARCH article

Front. Environ. Sci., 04 May 2021

Sec. Soil Processes

Volume 9 - 2021 | https://doi.org/10.3389/fenvs.2021.664104

Impact of Grazing Intensity on Soil Properties in Teltele Rangeland, Ethiopia

  • 1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institution of Ecology and Geography, Chinese Academy of Science, Urumqi, China

  • 2. National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institution of Ecology and Geography, Chinese Academy of Science, Urumqi, China

  • 3. University of China Academy of Science, Beijing, China

  • 4. Mekdela Amba University, College of Natural and Computational Science, Department of Chemsitry, TuluAwliya, Ethiopia

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Abstract

Grazing intensity (GI) is a major determining factor that controls the functioning of rangelands and the overall nutrient cycle. The Teltele rangeland is used for communal grazing area by the local pastorals; however, to date, there is no documented study data about the impact of GI. The objective of this study was to evaluate the impacts of grazing intensity on selected soil properties in the Teltele rangeland, Ethiopia. Soil samples were collected from different GI sites using different elevation gradient and soil depth from both open grazing and bush-encroached grazing land sand-assessed soil properties. Grazing intensity, elevation, and soil depth significantly (p < 0.05) affected both soils’ physical and chemical properties but rangeland types had no significant effect. The correlation analysis of soil characteristics with the principal component analysis axes showed significant variation. The highly weighted and correlated properties under principal component 1 (PC1) were electrical conductivity, organic carbon, total nitrogen, available phosphorus, and potassium, and under principal component 2, sand and bulk density with equal loaded value (r = −0.998), clay and silt, with silt (0.962) a more loaded one. Soil pH (0.743) demonstrated a significant (p < 0.05) positive correlation with sodium (−0.960) at PC1 (r = 0.610). Based on our results, we recommend further model-based studies on spatial–temporal change of soil properties due to impact of grazing intensity, combined with GIS and remote sensing data to be developed for sustainable rangeland management.

Introduction

Rangelands are lands on which the indigenous vegetation is predominantly grasses, grass-like plants, forbs, or shrubs and is managed as a natural ecosystem (Raj, 2005). Arid and semi-arid rangelands are heterogeneous in space and time because of variation in biotic and abiotic factors related to vegetation and soil properties and provide multiple ecosystem functions and services (Wang et al., 2016; Yang et al., 2016). Rangeland heterogeneity shapes vegetation structure and productivity (IPCC, 2013; Yigini and Panagos, 2016; Ademe et al., 2017). Variability in soil properties is a major main cause of rangeland heterogeneity (Ayalew, 2011). The major properties include soil textural, electrical conductivity (EC), organic matter (OM), and soil pH (Liu et al., 2011b; Abdalla et al., 2018). The primary use of the Teltele rangelands of Ethiopia is for livestock grazing (Derner et al., 2006). These rangelands are almost entirely occupied by a pastoral population using a system of communal resources for livestock production (Solomon et al., 2007). Grazing intensity is a major determining factor controlling rangeland functioning and the overall nutrient cycle (Hafner et al., 2012). Intensive livestock production and grazing gradually modify the soil characteristics, in particular organic carbon (OC), OM, EC, total nitrogen (TN), available phosphorus(P), exchangeable potassium (K), sodium (Na), texture, bulk density (BD), and pH (Pellant et al., 2000; Dessalegn et al., 2015; Zhou et al., 2017). Overgrazing can also cause soil erosion by reducing rangeland productivity and vegetation cover and in the long term, results in loss of environmental services, siltation of dams and river beds, reduction of groundwater, and social-community losses due to malnutrition and poverty (Adimassu et al., 2017). Furthermore, the removal of palatable species due to overgrazing suppresses their growth and facilitates the rapid encroachment of less desirable invasive species, mostly bush and shrubs plants species (Lin et al., 2010; Chen et al., 2015; Hailu et al., 2020).

Previous studies indicated that overgrazing increases soil heterogeneity (Su et al., 2006), while others reported that soil heterogeneity and vegetation diversity decrease with an increasing grazing intensity (Zhou et al., 2010; Zhao et al., 2011; Zhou et al., 2017). However, the majority of studies indicated that continuous and significant grazing intensities are generally accepted as having negative effects on OC (Piñeiro et al., 2010). Similarly, the effects of grazing on the spatial heterogeneity of grassland ecosystems related to soil properties have been inconsistent and need to be clarified in the Borana rangelands of Ethiopia. Evaluating dynamics of soil properties through grazing intensity (GI) requires clear and measurable data using comparable spatial methods at the study site. Therefore, understanding of soil properties is essential for rangeland management because such properties are among the primary factors that determine the forage production potential of an area in a particular climate (Hardy and Mentis, 1986; Aynekulu et al., 2017; Zhang et al., 2018). For centuries, the Teltele rangeland was used for communal grazing area by the local pastoralists, however, to date, there is no documented study data about the impact of GI on the soil properties in the rangeland area. This becomes one of the major gaps for sustainable rangeland management through balancing grazing capacity and maintaining rangeland productivity and livestock performance. Therefore, the objective of this study was to evaluate the soil properties in relation to the GI across different levels of altitude and grazing areas in Teltele rangeland, Ethiopia. So, this study aimed to address the following basic questions that can be used for effective implementation of management strategies and fill the knowledge gap mentioned above: 1) Is the significant difference observed in the soil properties due to variation of GI? 2) Does variation of grazing land type (GLT) had an impact on soil structure? 3) What is the interaction impact of GI with elevation (E) and soil depth (SD) on the soil properties? We hypothesized that 1) GI strongly affected soil properties, 2) GI had a similar impact on the soil properties both at the open grazing site and bush-encroached grazing site, and 3) interaction impact of GI, E, and SD is significant on the Teltele rangeland.

Materials and Methods

Study Area

This study was conducted from January–December 2019 in Teltele district, Borana zone, Ethiopia (Figure 1), which covers an area of 15,430 km2 of which 68% (10,492 km2) is rangeland (Billi et al., 2015). The Teltele rangeland is 666 km south of Addis Ababa. The area is situated approximately between 4° 56′ 23″ and 5° 49′ 21″ N latitude and 37° 41′ 51″ and 38° 39′ 37″ E longitude. Mean elevation is 500–1,500 m with a maximum of 2059 m. The mean annual temperature ranges from 28–33°C with little seasonal variation. The rainfall is distributed with 60% from March–May and 27% from September–November and with high temporal and spatial fluctuations (Dalle et al., 2015). Potential evapotranspiration is 700–3,000 mm (Billi et al., 2015). The soil in the study area includes 53% red sandy loam soil, 30% black clay, and volcanic light-colored silt clay and 17% silt, and the vegetation mainly dominated by encroaching woody species, and those that frequently thinned out, including Senegalia mellifera, Vachellia reficiens, and Vachellia oerfota (Coppock and scarnecchia, 1994; Gemdeo et al., 2005). The 2017 national census data reported a total population of 100,501 in this district, 51,670 men and 48,831 women. Cattle, goats, sheep, camels, mules, donkeys, and horses are the main livestock species.

FIGURE 1

FIGURE 1

Location map of the study area.

Grazing Site Selection

A reconnaissance survey and discussion were conducted with local pastoralists and district Pastoral Development Officers on grazing intensity issues. The sampling site was selected both from open (free from any bush encroachment) and from bush-encroached grazing site since both grazing land types were available in the study area with different GI. In each grazing land type, three grazing treatments were categorized based on GI. Grazing intensity data were collected using the same procedures described by Fenetahun et al. (2020,2021), the same authors at the same study site. Based on the discussion and survey data, grazing sites were chosen based on similar, uniform, and same soil series. All sites were on the northeast part of Teltele woreda and have laid in similar slope and elevation range, and all sampling sites had been grazed by livestock for several decades up to date and almost have the same seasonal and environmental features. Cattle, goats, and sheep are among the dominant livestock. The grazing sites were used for yearly round, seasonal, and some are already fenced by the government for conservation and rehabilitation purposes in order to use it when the harsh environment like drought will happen. The status of pasture and rangeland condition of grazing site was used to estimate the level of GI (Morteza et al., 2012). We selected a site with two treatments: a non-grazing (NG) (as a control) and a grazing site (moderately grazing and overgrazing) that was considered to see the effect of grazing intensity based on grazing intensity gradient (Fenetahun et al., 2021). The rate of GI was described as follows: non-grazed (NG) (livestock have been excluded from the pasture by fence and the ground was almost completely covered by vegetation) and moderately grazed (MG) (pasture has been used for grazing in regular rotational basis, that is, used during non-dry seasons but not in the rainy season and vegetation covers almost 50–55% and overgrazed (OG) (pasture is used for grazing constantly throughout the year and totally grazed and undergoes degradation, and vegetation cover was in most cases less than 15%) for the last 1.5 years, and also, GI was divided into MG and OG based on the current carrying capacity potential (Fenetahun et al., 2020; Fenetahun et al., 2021). The treatments of sample collection involved at NG (∼0 ha AU−1Y−1), MG (6 ha AU−1 Y−1), and OG (12 ha AU−1 Y−1 and above) grazing area based on the current carrying capacity of rangeland was calculated by Fenetahun et al. (2020) and physical field observation. Also, we have selected the sampling site which has almost similar rainfall pattern and temperature in order to reduce the climate difference effect on soil composition.

Soil Sampling and Analyses

For soil sample collection, we applied the judgment sampling method (USEPA, 2002) to locate sampling sites for both open-grazing land (OGL) and bush encouraged (BE), landscape E lower (LE) (700–1,000 m), medium (ME) (1,001–1,300 m), and higher (HE) (1,301–1,600 m), and at soil depths (SD) of 0–10 cm and 10–20 cm using an auger at all GI because most grass roots are found within this layer (Mekuria et al., 2018; Zhu et al., 2015). Then, established a 5-km transect at each site, three main plots (50 m × 50 m), the western plot having a GI of NG, the middle plot a GI of MG, and the eastern plot a GI of OG, were marked and had a 1 km interval between each GI plots, and in each marked plot, five quadrats of (1 m × 1 m) were placed at 5 m buffer zone for each sampling quadrat that was used for soil sample collection (Figure 2). Soil sampling was done both during the dry season (end of February 2019) and the rainy season (end of May 2019) along each of the grazing sites in order to overcome the season variation effect and we took the mean value. Thus, a total of 108 quadrat samples were collected (2 grazing land types × 3 landscape E × 3 GI plots × 2 SD) × 3 replications. The samples were mixed at the point of sampling and 0.5 kg sub-samples from each sampling point were taken in the laboratory in a plastic bag and were oven-dried at 105°C for 24 h in order to avoid delay. Samples for the BD estimation were collected two days after a rainfall event, a 5 cm × 5 cm soil corer of volume 98.13 cm3 was used, making sure not to disturb soil aggregation (Masebo et al., 2014; Hishe et al., 2017). Samples were analyzed in the soil laboratory at Yabello Pastoral and Dryland Agricultural Soil Research Center. After drying, soil samples were crushed to pass a 2-mm stainless steel sieve to remove foreign bodies (Hishe et al., 2017). Analysis was performed for OC, TN, P, K, Na, pH, EC contents, and particle size distribution (clay, silt, and sand) following standard procedures is described (Table 1) below.

FIGURE 2

FIGURE 2

Sampling lay out.

TABLE 1

Major soil physiochemical properties Analyses procedures and methods used References
Soil texture Hydrometer procedure van Reeuwijk (2002)
Organic carbon Wet oxidation method Walkley and Black (1934)
EC and pH 1:2.5 soil/water suspension Motsara and Roy (2008)
Exchangeable cations 1-M ammonium acetate solution at pH 7 Haldar and Sakar (2005)
Phosphorus (p) Olsen’s extraction Van der Waal (2009)
Total N Kjeldahl procedure Miles and Farina (2013)
Bulk densities Dividing oven-dry mass to volume of the core sampler Alemayehu and Fisseha (2018); Wilke (2005)

Standard procedures and methods used to analyses soil properties.

Data Analysis

The effect of GLT (OGL and BE), GI, and E impact on selected soil properties was analyzed by using analysis of variance (ANOVA) effect in SAS version 9.1.3 (Statistical Analysis System) with different statistical packages. Some of the properties possessed extreme outliers and did not meet the normality assumptions. Then, an assessment of significant differences evaluation at p < 0.05 was used to analyze the impact of treatment using the LSMEANS procedure (Yang and Luo, 2011). A Spearman rank correlation analysis and matrix were carried out to investigate the impact of soil factors resulting from the different GI, and a full set of soil properties data across GI, E, SD, and GLT were subjected to principal component analysis (PCA) to evaluate the impact of GI on each soil properties and also in order to evaluate the bonding characteristics within each soil properties. The criterion used for selecting the optimal subset of the main component (PC) is to select a subset with eigenvalues greater than 1.

Results

Physical Properties

From our result, we can understand that both levels of GI, E, and SD, had significant (p < 0.05) effects whereas GLT (OGL and BE) had no significant (p > 0.05) effect on all of the soil physical properties. Sand soil content was highest on the OG level of grazing than the MG and NG, at both SD and E, particularly at HE grazing position and at the 0–10 cm of SD and lowest on the NG level of grazing, at LE grazing position and at the 10–20 cm of SD in both GLT. Clay and silt soil content were highest on NG level of grazing than MG and OG at both SD and E, particularly at LE grazing position and at 10–20 cm of SD and lowest on OG level of grazing, at HE grazing position and at 0–10 cm of SD (Table 2). Also, the interaction (X) effect of both GI, E, and SD, across GLT had significant effects on all of the physical properties of the soil, both within and across the different grazing sites (Table 3 and Figure 3). The highest sand soil particle distribution was recorded at OG X BE X HE X 0–10 cm depth and the lowest was recorded at NG X BE X LE X 10–20 cm depth. The highest clay and silt soil particle distribution were recorded at NG X BE X LE X 10–20 cm depth and the lowest clay and silt were recorded at OG X BE X HE X 0–10 cm depth. The highest concentration of BD was observed at 0–10 cm depth in all GI and E. The highest BD was recorded at OG, in the BE site, at HE of 0–10 cm depth and lowest was recorded at NG, in the BE site at LE of 10–20 cm depth. This indicated that the interaction effect of GLT had significant effects on all of the physical properties of the soil.s

TABLE 2

Impacting factors and class Soil particle size distribution (%) BD (gcm−3)
Sand Clay Silt
Grazing land type (GLT) OGL 43.22 ± 0.05 36.01 ± 0.04 20.77 ± 0.14 1.16 ± 0.12
BE 45.34 ± 0.02 35.03 ± 0.05 19.63 ± 0.07 1.18 ± 0.23
Grazing intensity (GI) NG 42.38 ± 0.04a 38.76 ± 0.62a 18.86 ± 0.17a 1.14 ± 0.08a
MG 50.56 ± 0.03b 31.65 ± 0.21b 17.79 ± 0.09b 1.36 ± 0.17b
OG 61.92 ± 0.17c 27.63 ± 0.17c 10.45 ± 0.31c 1.67 ± 0.15c
Elevation (E) (m) LE 39.18 ± 0.16a 38.24 ± 0.89a 22.58 ± 0.03a 1.05 ± 0.05a
ME 50.54 ± 0.09b 33.39 ± 0.71b 16.07 ± 0.14b 1.34 ± 0.13b
HE 58.37 ± 0.11c 30.19 ± 0.09c 11.44 ± 0.18c 1.57 ± 0.11c
Soil depth (SD) (cm) 0–10 49.18 ± 0.05a 32.16 ± 0.14a 18.66 ± 0.06a 1.32 ± 0.08a
10–20 40.71 ± 0.12b 35.0 ± 0.42b 24.29 ± 0.03b 1.09 ± 0.10b
 P-GLT Ns Ns Ns Ns
 P-GI ** ** * **
 P-E ** * ** **
 P-SD * * * *

Mean (±SE) value of soil physical particle size distribution under different grazing land type, elevation, grazing intensity, and soil depths.

Mean values within columns under each topic followed by different letters are significantly different from each other at p < 0.05, OGL = open-grazing land, BE, bush encroached; NG, non-grazing; MG, moderately grazing; OG, overgrazing; LE, lower elevation; ME, middle elevation; HE, higher elevation; BD, bulk density; ns, nonsignificant, * significant, ** highly significant. SE = standard error.

TABLE 3

Interactive factors (GI X GLT X E X SD) Soil particle size distribution (%) BD (gcm−3)
Sand Clay Silt
NG OGL LE 0–10 45.49 ± 0.91a 33.01 ± 0.19a 21.5 ± 0.30a 1.22 ± 0.05a
10–20 39.80 ± 0.22b 36.89 ± 0.17b 23.31 ± 0.09b 1.07 ± 0.08b
ME 0–10 49.91 ± 0.14c 30.08 ± 0.91c 20.01 ± 0.54c 1.34 ± 0.14c
10–20 40.62 ± 0.07d 35.93 ± 0.28d 23.45 ± 0.41d 1.09 ± 0.03d
HE 0–10 54.11 ± 0.18e 27.71 ± 0.33e 18.18 ± 0.05e 1.45 ± 0.06e
10–20 41.34 ± 0.23f 30.98 ± 0.41f 27.69 ± 0.66f 1.11 ± 0.03f
BE LE 0–10 45.92 ± 0.51a 32.67 ± 0.08a 21.41 ± 0.37a 1.23 ± 0.07a
10–20 38.95 ± 0.09b 37.31 ± 0.58b 23.74 ± 0.28b 1.05 ± 0.21b
ME 0–10 50.33 ± 0.33c 30.65 ± 0.61c 19.02 ± 0.33c 1.35 ± 0.08c
10–20 41.57 ± 0.61d 34.95 ± 0.04d 23.48 ± 0.09d 1.12 ± 0.31d
HE 0–10 55.05 ± 0.42e 26.55 ± 0.77e 18.4 ± 0.29e 1.48 ± 0.04e
10–20 42.09 ± 0.18f 31.89 ± 0.02f 26.02 ± 0.44f 1.13 ± 0.02f
MG OGL LE 0–10 52.76 ± 0.22aa 30.99 ± 0.03aa 16.25 ± 0.45aa 1.42 ± 0.06aa
10–20 47.09 ± 0.41ba 34.45 ± 0.36ba 18.46 ± 0.05ba 1.26 ± 0.03ba
ME 0–10 56.79 ± 0.09ca 28.99 ± 0.07ca 14.22 ± 0.12ca 1.52 ± 0.06ca
10–20 49.06 ± 0.17da 32.45 ± 0.06da 18.49 ± 0.16da 1.32 ± 0.17da
HE 0–10 58.10 ± 0.31ea 27.87 ± 0.15ea 14.03 ± 0.06ea 1.56 ± 0.14ea
10–20 52.21 ± 0.06fa 30.04 ± 0.27fa 17.75 ± 0.07fa 1.40 ± 0.05fa
BE LE 0–10 53.67 ± 0.41aa 29.99 ± 0.16aa 16.34 ± 0.33aa 1.44 ± 0.39aa
10–20 48.49 ± 0.05ba 33.87 ± 0.02ba 17.64 ± 0.36ba 1.30 ± 0.53ba
ME 0–10 57.63 ± 0.36ca 28.02 ± 0.51ca 14.35 ± 0.11ca 1.55 ± 0.04ca
10–20 50.18 ± 0.38da 32.20 ± 0.31da 17.62 ± 0.08da 1.35 ± 0.37da
HE 0–10 59.64 ± 0.06ea 27.07 ± 0.22ea 13.29 ± 0.19ea 1.60 ± 0.29ea
10–20 53.78 ± 0.04fa 29.82 ± 0.08fa 16.40 ± 0.12fa 1.44 ± 0.18fa
OG OGL LE 0–10 58.66 ± 0.06ab 26.77 ± 0.15ab 14.57 ± 0.21ab 1.57 ± 0.17ab
10–20 53.05 ± 0.18bb 28.84 ± 0.23bb 18.11 ± 0.32bb 1.42 ± 0.39bb
ME 0–10 63.71 ± 0.23cb 24.41 ± 0.04cb 13.88 ± 0.07cb 1.69 ± 0.33cb
10–20 54.06 ± 0.25db 25.97 ± 0.51db 19.97 ± 0.42db 1.45 ± 0.07db
HE 0–10 64.07 ± 0.04eb 23.80 ± 0.04eb 12.13 ± 0.05eb 1.72 ± 0.06eb
10–20 55.93 ± 0.08fb 25.79 ± 0.18fb 18.28 ± 0.36fb 1.50 ± 0.23fb
BE LE 0–10 59.09 ± 0.44ab 26.10 ± 0.17ab 14.81 ± 0.03ab 1.59 ± 0.14ab
10–20 54.10 ± 0.27bb 28.2 ± 0.32bb 17.70 ± 0.39bb 1.45 ± 0.11bb
ME 0–10 64.0 ± 0.15cb 23.94 ± 0.08cb 12.06 ± 0.02cb 1.72 ± 0.18cb
10–20 55.71 ± 0.14db 24.69 ± 0.13db 20.33 ± 0.09db 1.50 ± 0.44db
HE 0–10 65.31 ± 0.07eb 23.05 ± 0.34eb 11.64 ± 0.12eb 1.74 ± 0.03eb
10–20 56.08 ± 0.07eb 23.98 ± 0.28fb 19.94 ± 0.16fb 1.51 ± 0.07fb
P-GI X GLT X E X SD ** ** ** **

Mean (±SE) value of soil physical particle size distribution under the interaction effects of grazing intensity with grazing land type, elevation, and soil depths.

Mean values within columns under each topic followed by different letters are significantly different at p < 0.05 and with same letter under row in each grazing intensity within different grazing land type are no significantly different (p > 0.05) from each other. ** highly significant, BD, bulk density; NG, non-grazing; OGL, open-grazing land; LE, lower elevation; ME, middle elevation; HE, higher elevation; BE, bush encroached; MG, moderately grazing; OG, overgrazing; GI, grazing intensity; GLT, grazing land type; E, elevation (m); SD, soil depth (cm); SE, standard error.

FIGURE 3

FIGURE 3

Mean ± SE particle size distribution across grazing intensity. Bars with different letters are significantly different for each grazing intensity site, PSD, particle size distribution; NG, non-grazing; MG, moderately grazing; OG, overgrazing.

Chemical Properties

Results indicated that both levels of GI, E, and SD, exhibited a significant (p < 0.05) effect but GLT had no significant (p > 0.05) effect on all of the soil chemical properties. The highest EC, OC, TN, P, and K contents were recorded at NG than the MG and OG level of grazing at both SD and E, particularly at HE grazing position and at the 10–20 cm of SD and lowest at OG level of grazing at both SD and E, particularly at LE grazing position and at the 0–10 cm of SD in both GLT. The highest pH and Na values were recorded at OG than NG and MG level of grazing at both SD and E, particularly at LE and at the 0–10 cm of SD and lowest at NG level of grazing, especially at HE and at the 10–20 cm of SD (Table 4). Interaction (X) effects of both GI, E, and SD, across GLT had significant effects on all of the chemical properties of the soil, both within and across the different grazing sites (Table 5 and Figure 4). The highest EC, OC, TN, P, and K contents were recorded at NG X OGL X HE X 10–20 cm depth and the lowest was recorded at OG X BE X LE X 0–10 cm depth. The highest pH and Na values were recorded at OG X BE X LE X 0–10 cm depth and the lowest was recorded at NG X OGL X HE X 10–20 cm depth. Further, the interaction effect of bush encroachment also had affected the soil chemical properties distribution in the grazing rangeland.

TABLE 4

Impacting factors and class Soil chemical properties
EC (dSm−1) OC (%) TN (%) Av. p (%) Av. K (%) Ex. Na (%) pH (pH m)
GLT OGL 0.07 ± 0.01 1.00 ± 0.03 0.18 ± 0.07 12.03 ± 0.09 0.76 ± 0.03 0.41 ± 0.01 6.74 ± 0.08
BE 0.07 ± 0.01 0.99 ± 0.02 0.16 ± 0.01 11.98 ± 0.17 0.74 ± 0.02 0.42 ± 0.01 6.78 ± 0.12
GI NG 0.09 ± 0.01a 1.07 ± 0.08a 0.19 ± 0.02a 12.08 ± 0.38a 0.89 ± 0.05a 0.38 ± 0.01a 5.45 ± 0.07a
MG 0.06 ± 0.03b 0.68 ± 0.03b 0.10 ± 0.01b 8.20 ± 0.44days 0.71 ± 0.01b 0.64 ± 0.08b 6.03 ± 0.10b
OG 0.04 ± 0.01c 0.48 ± 0.06c 0.08 ± 0.03c 6.09 ± 0.21c 0.39 ± 0.02c 0.91 ± 0.05c 6.91 ± 0.04c
E LE 0.03 ± 0.02a 0.49 ± 0.09a 0.06 ± 0.02a 5.98 ± 0.14a 0.41 ± 0.01a 0.92 ± 0.08a 6.88 ± 0.14a
ME 0.06 ± 0.04b 0.72 ± 0.12b 0.11 ± 0.04b 7.07 ± 0.04b 0.59 ± 0.03b 0.61 ± 0.03b 6.03 ± 0.21b
HE 0.08 ± 0.01c 1.03 ± 0.03c 0.17 ± 0.05c 11.97 ± 0.06c 0.79 ± 0.03c 0.44 ± 0.07c 5.42 ± 0.006c
SD 0–10 0.05 ± 0.03a 0.61 ± 0.07a 0.05 ± 0.02a 8.09 ± 0.09a 0.5 ± 0.02a 0.89 ± 0.09a 6.86 ± 0.19a
10–20 0.07 ± 0.01b 1.04 ± 0.04b 0.18 ± 0.06b 11.88 ± 0.11b 0.83 ± 0.04b 0.45 ± 0.02b 5.96 ± 0.03b
P-GLT Ns Ns Ns Ns Ns ns Ns
P-GI * ** ** ** ** ** **
P-E * ** * ** * ** **
P-SD * ** ** ** * ** *

Mean (±SE) value of soil chemical properties distribution under different grazing land type, elevation, grazing intensity, and soil depths.

Mean values within columns under each topic followed by different letters are significantly different from each other at p < 0.05, EC, electrical conductivity; OC, organic carbon; TN, total nitrogen; Av. p, available phosphorus; Av. K, available potassium; Ex. Na, exchangeable sodium; pH, soil reaction; OGL, open-grazing land; BE, bush encroached; NG, non-grazing; MG, moderately grazing; OG, overgrazing; LE, lower elevation; ME, middle elevation; HE, higher elevation; SD, soil depth (cm); E, elevation(m); GI, grazing intensity; GLT, grazing land type; ns, nonsignificant, * significant, ** highly significant.

TABLE 5

Interactive factors (GI X GLT X E X SD) Soil chemical properties
EC (dSm−1) OC (%) TN (%) Av. p (%) Av. K (%) Ex. Na (%) pH (pH m)
NG OGL LE 0–10 0.05 ± 0.02a 0.46 ± 0.02a 0.08 ± 0.03a 10.21 ± 0.07a 0.58 ± 0.02a 0.45 ± 0.02a 5.92 ± 0.12a
10–20 0.09 ± 0.01b 0.61 ± 0.04b 0.11 ± 0.01b 10.82 ± 0.12b 0.69 ± 0.06b 0.37 ± 0.01b 5.78 ± 0.16b
ME 0–10 0.08 ± 0.03c 0.57 ± 0.05c 0.07 ± 0.02c 10.48 ± 0.07c 0.62 ± 0.02c 0.33 ± 0.01c 5.63 ± 0.20c
10–20 0.13 ± 0.07d 0.92 ± 0.12d 0.12 ± 0.02d 11.05 ± 0.41d 0.81 ± 0.08d 0.27 ± 0.02d 5.42 ± 0.05d
HE 0–10 0.08 ± 0.04e 0.79 ± 0.03e 0.09 ± 0.01e 10.98 ± 0.04e 0.78 ± 0.01e 0.31 ± 0.03e 5.36 ± 0.18e
10–20 0.19 ± 0.02f 1.18 ± 0.21f 0.19 ± 0.07f 12.13 ± 0.18f 0.99 ± 0.09f 0.22 ± 0.04f 5.27 ± 0.03f
BE LE 0–10 0.04 ± 0.01a 0.47 ± 0.03a 0.07 ± 0.01a 10.22 ± 0.11a 0.58 ± 0.04a 0.47 ± 0.05a 5.94 ± 0.06a
10–20 0.07 ± 0.02b 0.60 ± 0.01b 0.10 ± 0.03b 10.80 ± 0.22b 0.66 ± 0.02b 0.38 ± 0.08b 5.79 ± 0.44b
ME 0–10 0.07 ± 0.01c 0.56 ± 0.05c 0.06 ± 0.01c 10.46 ± 0.06c 0.62 ± 0.03c 0.35 ± 0.03c 5.66 ± 0.06c
10–20 0.09 ± 0.03d 0.92 ± 0.03d 0.12 ± 0.04d 11.06 ± 0.08d 0.79 ± 0.01d 0.29 ± 0.04d 5.44 ± 0.15d
HE 0–10 0.07 ± 0.02e 0.78 ± 0.02e 0.08 ± 0.01e 10.96 ± 0.33e 0.76 ± 0.05e 0.31 ± 0.05e 5.39 ± 0.08e
10–20 0.18 ± 0.06f 1.16 ± 0.09f 0.18 ± 0.06f 12.11 ± 0.03f 0.98 ± 0.08f 0.24 ± 0.06f 5.29 ± 0.11f
MG OGL LE 0–10 0.04 ± 0.01aa 0.41 ± 0.01aa 0.08 ± 0.02aa 10.33 ± 0.08aa 0.39 ± 0.02aa 0.72 ± 0.07aa 6.05 ± 0.10aa
10–20 0.07 ± 0.02ba 0.58 ± 0.03ba 0.10 ± 0.01ba 10.54 ± 0.03ba 0.54 ± 0.01ba 0.6 ± 0.03ba 6.02 ± 0.19ba
ME 0–10 0.08 ± 0.01ca 0.47 ± 0.07ca 0.09 ± 0.01ca 10.59 ± 0.10ca 0.60 ± 0.04ca 0.60 ± 0.07ca 6.02 ± 0.07ca
10–20 0.10 ± 0.07da 0.71 ± 0.02da 0.12 ± 0.03da 10.87 ± 0.12da 0.80 ± 0.05da 0.50 ± 0.01da 5.95 ± 0.13da
HE 0–10 0.09 ± 0.02ea 0.82 ± 0.05ea 0.11 ± 0.02ea 10.96 ± 0.07ea 0.72 ± 0.01ea 0.47 ± 0.04ea 5.93 ± 0.06ea
10–20 0.13 ± 0.07fa 0.97 ± 0.06fa 0.14 ± 0.04fa 11.05 ± 0.51fa 0.83 ± 0.05fa 0.44 ± 0.07fa 5.88 ± 0.23fa
BE LE 0–10 0.04 ± 0.01aa 0.40 ± 0.02aa 0.07 ± 0.01aa 10.33 ± 0.18aa 0.38 ± 0.01aa 0.73 ± 0.02aa 6.07 ± 0.44aa
10–20 0.09 ± 0.01ba 0.58 ± 0.03ba 0.09 ± 0.02ba 10.53 ± 0.07ba 0.52 ± 0.07ba 0.61 ± 0.08ba 6.01 ± 0.08ba
ME 0–10 0.08 ± 0.02ca 0.45 ± 0.07ca 0.09 ± 0.01ca 10.60 ± 0.43ca 0.59 ± 0.02ca 0.61 ± 0.05ca 6.04 ± 0.45ca
10–20 0.09 ± 0.02da 0.70 ± 0.02da 0.11 ± 0.03da 10.87 ± 0.27da 0.78 ± 0.08da 0.52 ± 0.03da 6.02 ± 0.33da
HE 0–10 0.08 ± 0.01ea 0.82 ± 0.09ea 0.10 ± 0.03ea 10.94 ± 0.33ea 0.72 ± 0.04ea 0.48 ± 0.01ea 5.93 ± 0.13ea
10–20 0.13 ± 0.03fa 0.95 ± 0.07fa 0.12 ± 0.01fa 11.04 ± 0.39fa 0.81 ± 0.05fa 0.46 ± 0.02fa 5.90 ± 0.05fa
OG OGL LE 0–10 0.02 ± 0.01ab 0.38 ± 0.02ab 0.05 ± 0.01ab 5.96 ± 0.20ab 0.38 ± 0.02ab 0.97 ± 0.07ab 6.93 ± 0.16ab
10–20 0.04 ± 0.01bb 0.43 ± 0.07bb 0.07 ± 0.01bb 6.03 ± 0.09bb 0.51 ± 0.08bb 0.91 ± 0.01bb 6.92 ± 0.14bb
ME 0–10 0.04 ± 0.02cb 0.50 ± 0.03cb 0.04 ± 0.02cb 5.99 ± 0.17cb 0.42 ± 0.01cb 0.91 ± 0.09cb 6.87 ± 0.07cb
10–20 0.06 ± 0.01db 0.56 ± 0.04db 0.08 ± 0.01db 6.68 ± 0.04db 0.63 ± 0.04db 0.82 ± 0.02db 6.78 ± 0.44db
HE 0–10 0.06 ± 0.01eb 0.61 ± 0.07eb 0.07 ± 0.01eb 6.83 ± 0.41eb 0.47 ± 0.03eb 0.86 ± 0.06eb 6.81 ± 0.31eb
10–20 0.08 ± 0.02fb 0.67 ± 0.04fb 0.11 ± 0.07fb 7.89 ± 0.44fb 0.66 ± 0.05fb 0.77 ± 0.03fb 6.53 ± 0.06fb
BE LE 0–10 0.03 ± 0.01ab 0.38 ± 0.02ab 0.04 ± 0.01ab 5.94 ± 0.24ab 0.36 ± 0.02ab 0.98 ± 0.08ab 6.95 ± 0.22ab
10–20 0.03 ± 0.01bb 0.42 ± 0.01bb 0.06 ± 0.01bb 6.02 ± 0.07bb 0.51 ± 0.03bb 0.93 ± 0.03bb 6.92 ± 0.08bb
ME 0–10 0.03 ± 0.01cb 0.50 ± 0.05cb 0.03 ± 0.01cb 5.98 ± 0.16cb 0.40 ± 0.01cb 0.91 ± 0.04cb 6.89 ± 0.12cb
10–20 0.05 ± 0.01db 0.55 ± 0.03db 0.08 ± 0.02db 6.68 ± 0.06db 0.63 ± 0.06db 0.84 ± 0.02db 6.78 ± 0.13db
HE 0–10 0.06 ± 0.01eb 0.60 ± 0.07eb 0.07 ± 0.01eb 6.83 ± 0.11eb 0.47 ± 0.03eb 0.87 ± 0.07eb 6.81 ± 0.06eb
10.20 0.07 ± 0.02fb 0.67 ± 0.04fb 0.10 ± 0.03fb 7.88 ± 0.05fb 0.65 ± 0.02fb 0.77 ± 0.01fb 6.55 ± 0.41fb
P-GI X GLT X E X SD * ** ** ** * * **

Mean (±SE) value of soil chemical properties distribution under the interaction effects of grazing intensity with grazing land type, elevation and soil depths.

Mean values within columns under each effect followed by different letters are significantly different from each other at p < 0.05, EC, electrical conductivity; OC, organic carbon; TN, total nitrogen; Av. p, available phosphorus; Av. K, available potassium; Ex. Na, exchangeable sodium; pH, soil reaction; OGL, open-grazing land; BE, bush-encroached grazing land; NG, non-grazing; MG, moderately grazing; OG, overgrazing; LE, lower elevation; ME, middle elevation; E, elevation (m); GI, grazing intensity; HE, higher elevation; SD, soil depth(cm); ns, nonsignificant; * significant, ** highly significant.

FIGURE 4

FIGURE 4

Mean ± SE soil chemical properties abundance across grazing intensity. Bars with different letters are significantly different for each grazing intensity site. SCP, soil chemical properties; GI, grazing intensity; NG, non-grazing; MG, moderately grazing; OG, overgrazing.

Correlation Analysis of Soil Properties With Grazing Intensity

The correlation analysis of the regression lines describes the relationship between the soil properties and the GI. In relation to soil physical properties, there is a positive correlation between sand and BD contents with the GI but a negative correlation with clay and silt contents with the rate of GI (Figure 5). In the case of soil chemical properties, GI showed a negative correlation with the soil EC, OC, TN, P, and K contents and a positive correlation with soil pH and Na contents (Figure 6).

FIGURE 5

FIGURE 5

Correlations between soil physical properties and grazing intensity. GI, grazing intensity; NG, non-grazing; MG, moderately grazing; OG, overgrazing.

FIGURE 6

FIGURE 6

Correlations between soil chemical properties and grazing intensity (GI, grazing intensity; NG, non-grazing; MG, moderately grazing; OG, overgrazing.

Correlation Matrix and Principal Component Analysis of Soil Particle

Observing the correlation matrix and PCA that were computed for each pair of soil properties at each GLT along with the interaction effect of GI, E, and SD, and EC, OC, TN, P, and K showed positive correlations with each other and with clay and silt soil contents, whereas, a negative correlation with Na, pH, and sand soil contents across both GLT, GI, E, and SD (Table 6 and Figure 7B). The location of soil properties under different regions of the PCA axes is based on the correlation coefficient between each variable. Since the main components are orthogonal, this defines a projection of the data on vector space spanned by the first two principal components. Thus, we used two PCs with eigenvalues >1 for our study (Table 6 and Figure 7A). Therefore, the location of each soil property in the PCA diagram is very significant and important. The highly weighted and positively correlated properties under PC1 were EC, OC, TN, P, and K and highly impacted or negatively correlated with Na and pH (Figure 7B). Under PC2, the highly weighted and positively correlated properties were sand and BD with a high negative correlation of the other weighted and positively correlated properties of clay and silt. Soil pH showed a strong positive correlation with Na at PC1 with a more loaded value of Na, and this result strongly agrees with the data reported by Kane (2015).

TABLE 6

EC OC TN Av. p Av. K Ex. Na pH Sand Clay Silt BD
EC 1.000
OC 0.933 1.000
TN 0.891 0.961 1.000
Av. p 0.887 0.974 0.917 1.000
Av. K 0.949 0.948 0.913 0.912 1.000
Ex. Na −0.928 −0.967 −0.963 −0.914 −0.951 1.000
pH −0.746 0.594 0.584 0.471 0.713 0.610 1.000
Sand 0.112 0.298 0.248 0.290 0.306 0.266 0.064 1.000
Clay 0.226 0.354 0.330 0.318 0.345 0.339 0.069 −0.934 1.000
Silt 0.010 0.225 0.159 0.241 0.246 -0.182 0.164 −0.959 0.793 1.000
BD 0.118 0.308 0.254 0.298 0.309 0.280 0.076 0.998 0.932 0.957 1.000

Correlation matrix within each pair of soil properties across the interaction effect of impacting factors.

EC, electrical conductivity; OC, organic carbon; TN, total nitrogen; Av. p, available phosphorus; Av. K, available potassium; Ex. Na, exchangeable sodium; pH, soil reaction.

FIGURE 7

FIGURE 7

(A) Scree plot for the different components considered for the principal component analysis with eigenvalues greater than one and (B) principal component analysis (PCA) of the overall data set. OC, organic carbon; TN, total nitrogen; Av. p, available phosphorus; Av. K, available potassium; Ex. Na, exchangble sodium; BD, bulk density; EC, electrical conductivity.

Discussion

Impact of Grazing Intensity on Soil Properties

Grazing Intensity Impact on Soil Physical Properties

The Teltele rangeland site was selected because it is one of the driest parts of the Borana region and therefore the pastoral communities in this region are the most vulnerable to rangeland degradation due to overgrazing. The GI significantly affected all the soil properties that we measured. The clay and silt soil contents distribution were decreased with increasing GI and decreased SD and decreased with increasing E, while the sand soil content distribution was increased with decreasing GI and increasing E and decreased with increasing SD (Stavi et al., 2008; Larreguy et al., 2014; Yun and Wesche, 2016; Lu et al., 2017; Zhang et al., 2018). In general, in this study, grazing was associated with higher BD, increase in the sand, decreased clay and silt, decreased soil moisture, decreased diversity and coverage of grass species, and results increasing in unpalatable plant species. The result showed a positive relationship between sand and BD soil contents with GI, that is, increased while GI increasing and vice versa. This indicates the direct linkage of BD with sand content and an inverse linkage with clay and silt content and results in line with data reported by Gashaw et al. (2017), Tufa et al. (2019). In addition, the major cause for increasing of BD on the grazing site is the presence of high sand soil content distribution and higher porous spaces compared with other soil particles (Adesodun et al., 2007; Wolka et al., 2011; Chaudhari et al., 2013; Adimassu et al., 2017; Zhou et al., 2017; Paulo et al., 2018). The soil structure, moisture content, OM composition, and GI determine the soil content distribution in the grazing site (Liu et al., 2011b; Ademe et al., 2017; Tufa et al., 2019). For instance, the NG site has a better OM and moisture content and in the NG grazing level, clay and silt soil contents were observed dominantly and mainly at LE position of 10–20 cm of SD. This is due to the upper part of 0–10 cm SD, easily exposed to any livestock trampling during grazing and facilitates wind and flood erosion. This speedup water runoff and loss of soil moisture and changes to bare land, resulting in clay and silt soil particle easily eroded from the site and dominated with sand soil content (Fei et al., 2010; Zhou et al., 2010; Morteza et al., 2012; Descalzi et al., 2018). The data reported by Alemayehu and Fisseha (2018), Demelash and Karl (2010) indicated that higher clay and lower sand content was recorded at non-conserving or OG sites without any influence of the difference in E in contrast to our current result. Consequently, the linear regression analysis showed that the GI had a positive relationship with sand and BD soil contents and a negative relationship with clay and silt contents (Ademe et al., 2017).

Grazing Intensity Impact on Soil Chemical Properties

The soil chemical properties are soil management properties dependent on the soil structure, air and water conductivity, and highly influenced by grazing management. As a result, grazing significantly affected the soil chemical properties concentration found at the grazing rangeland site. At the grazing site of LE, the density of livestock was higher than that of ME and HE and had a great effect on the soil chemical properties distribution of the grazing site, even under similar GI and GLT. The soil EC was high at the NG grazing level than that in the MG and OG. The reason for the highest EC observed at the NG site mainly at HE in the soil surface of 10–20 cm is due to the high availability of OC, TN, P, and K, resulting in high cation and anion concentration, and EC is the sum of two ions (Kidane, 2006; Yan et al., 2013; Zhang et al., 2018; Guo et al., 2019). The major reason for the distribution of OC, TN, P, and K was higher in the managed area or NG area is due to the availability of higher grass biomass which results in increased availability of soil nutrients during decomposition (Hamilton and Frank, 2001; Wang et al., 2018),but when the rangeland was exposed to continuous grazing and transformed into OG degraded area, the aboveground grass biomass declined and the formation of OM was affected. The rangeland site exposed to different erosion agents like wind and water resulted in a lower distribution of OC, TN, P, and K and lead to the distribution of Na and pH become higher (Zhang et al., 2009; Chaudhari et al., 2013; Guo et al., 2019). The other possible reason for the highest EC, OC, TN, P, and K values was recorded at soil surface of 10–20 cm depth compared to the soil surface of 0–10 cm was due to high distribution of clay and silt soil particle at soil surface of 10–20 cm than 0–10 cm (Demelash and Karl, 2010; Aytenew and Kibret, 2016; Ademe et al., 2017). Those soil chemical properties had an abundance of direct linkage between them. The pH and Na showed higher values at 0–10 cm of SD across all grazing level, especially at the OG site of HE, and this was due to the high distribution of sand soil particles and a positive relationship with pH and Na (Tufa et al., 2019; Yang et al., 2016; Wolka et al., 2011). As pH increases, the availability of certain major basic cations like Na, clay, and CEC are positively correlated because clay minerals provide the negative charge to attract the cations. The variation of GLT does not show a significant effect on the soil chemical properties except with slight variation. This means the values of EC, OC, TN, P, and K showed slightly higher value at OGL compared to BE grazing site, whereas pH and Na values showed higher at BE at OGL grazing site and our result is in agreement with the data reported by Mulder et al. (2015). Further, the linear regression analysis showed that a significant negative relationship with the soil EC, OC, TN, P, and K and a positive relationship with Na and pH as GI increased, and this result supported with the data reported by Kate (2019), Hao and He (2019). Overall, grazing has shown a decreasing effect on the abundance of soil organic matter and the water-holding capacity, which leads to an increase in soil BD, sandy soil particles, and Na and pH and decrease in EC, OC, TN, P, and K; therefore, our hypothesis was accepted. Managing rangeland grazing used to protect not only the soil contents of the rangeland but also the water availability, and this research will be used as a reference and initiative for further research and aware the pastoralist community through showing how over stoking currently impacts both the rangeland soil and productivity in the Teltele rangeland, and this was the implication of our current work.

Conclusion

In the Teltele rangeland, grazing intensity strongly influenced the soil properties of the grazing rangeland. The increase in the distribution of the apparent density of the soil was mainly due to the increase in the distribution of sand soil particles and decline of sand and silt soil particle. This caused speedup of water infiltration, changes in chemical properties, and fertility of the soil and is among the major impacts of overgrazing. It can be concluded that managing the level of grazing is an essential technique used for improving arid and semi-arid rangeland areas including Teltele. Managing the grazing period and balancing the number of livestock grazed on the grazing land help reduce the grazing density and restore the soil properties, through improved vegetation cover and reduced runoff and erosion. Variation of grazing land type had less impact on the soil properties as compared with grazing intensity, elevation, and soil depth difference effect. Further, studies are needed for better understanding of seasonal management of grazing intensity for a better improvement of the grazing land soil properties and enhanced general ecosystem function of rangeland. Timely reform and balancing of carrying capacity of livestock at a certain grazing area are needed for proper rehabilitation of rangeland through providing a recovery period and for the proper implementation of the limited number of livestock and reduce grazing intensity, introduction and application of appropriate laws that is formulated by both the local communities and government official that govern the way how to use of communal grazing areas. Based on our result, we also recommend that the influence of grazing intensity should be further studied by combining GIS, remote sensing, and NDVI data to see temporal and spatial changes due to the effect of grazing and model-based data that showed a change of soil properties is more reliable in the Teltele rangeland site.

Statements

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Author contributions

YF: data collection, writing up, gap assessment and design of the experiments. XX, WD, TF, and VN: editing, proofing, laboratory assistance, provide important advice as well as supervision of the whole work.

Funding

This study received financial support from CAS-TWAS fellowship program and African Great Green Wall Adaptation Technical Cooperation Research and Demonstration (Grant No. 2018YFE0106000), Science and Technology Partnership Program, Ministry of Science and Technology of China (Grant No. KY 201702010), Integration and application of appropriate technologies for desertification control in Africa (Grant No. SAJC2021080, and International cooperation and Exchanges NSFC (Grant No. 41861144020).

Acknowledgments

The authors wish to thank the University of Chinese Academy of Science and CAS-TWAS fellowship program that provides funding and the PhD Scholarship for the first author. They also acknowledge the African Great Green Wall Adaptation Technical Cooperation Research and Demonstration (2018YFE0106000), Science and Technology Partnership Program, Ministry of Science and Technology of China (Grant Nos. KY 201702010), and International cooperation and Exchanges NSFC (Grant Nos. 41861144020) financial support to do this paper, also our great thanks go to the local community and stakeholder of the Teltele district for giving us the basic information that is still the challenge for them for our next research step. Once again, Yabello Pastoral and Dryland Agricultural Soil Research Center deserve many thanks for providing us the laboratory and other facilitates while conducting our experiment.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Summary

Keywords

stocking rate, soil depth, elevation, soil indicators, management practice 2

Citation

Fenetahun Y, Yuan Y, Xinwen X, Fentahun T, Nzabarinda V and Yong-dong W (2021) Impact of Grazing Intensity on Soil Properties in Teltele Rangeland, Ethiopia. Front. Environ. Sci. 9:664104. doi: 10.3389/fenvs.2021.664104

Received

02 March 2021

Accepted

09 April 2021

Published

04 May 2021

Volume

9 - 2021

Edited by

Rosa Francaviglia, Council for Agricultural and Economics Research, Italy

Reviewed by

Jian Sun, Institute of Tibetan Plateau Research, China

Manuel Pulido Fernández, University of Extremadura, Spain

Updates

Copyright

*Correspondence: Wang Yong-dong,

This article was submitted to Soil Processes, a section of the journal Frontiers in Environmental Science

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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