Materials and Methods
Description of the Study
Areas
The study was conducted in the Jigjiga field site (9.356784 N,
42.795519W) of the Somali Regional State of Ethiopia (Figure 1), which
is part of a pastoral ecosystem. This area experiences two rainy
seasons: the main season occurs from July to September, and the shorter
one is from March to April. The average annual rainfall in the area is
660 mm (Gebremedhn et al. , 2022) and the soils are mainly sandy
loams (Alemie and Gebremedhin, 2019). The temperature is generally high
throughout the year, with mean minimum values around 20 °C and mean
maximum values around 35 °C (Gezahegn, 2006). The natural vegetation of
the area is Acacia wooded grasslands, with Chrysopogon aucheri and
Eragrostis spp, being the most dominant grass species and Acacia
ethbaica, Acacia busse, and Vachellia nitlotica . are being the most
dominant woody species of the study area (Hailu 2017). The land-use
system in the area is primarily pastoral, with the local community being
nomadic and relying heavily on livestock grazing for their livelihoods.
Site selection and sampling
design
Before selecting the study plots and sampling techniques, a preliminary
survey was conducted with local natural resource management experts and
elders who had extensive knowledge of grazing management practices in
the study area. Based on their input, three traditional rangeland
management practices were chosen for this study: enclosures, communal
open grazing, and browsing land. (i) Enclosures are used for hay
production, which is cut and carried to the livestock when there is a
feed shortage for grazing in the open communal grazing areas. (ii)
Communal open grazing areas are characterized by open grass vegetation
with scattered trees, and are used
for extensive livestock grazing throughout the year. (iii) Browsing
land, also known as “bay land” and is dominated by bush vegetation and
is used for camel and goat browsing. The communal open grazing area
represents the most common land-use system in the Somali rangelands. For
a detail description of the management systems of the field sites see
Gebremedhn et al., (2022).
The transect survey method was used for sampling vegetation attributes
across the three different management practices. Specifically, nine
square plots of 400 m2 each were established at an
interval of 5 km for grazing land from Harishin to Kebri Beyah
rangelands of the Jigjiga zone (Figure 1). Similarly, nine 400
m2 square plots were laid at an interval of 1 km for
browsing land from Awebere rangelands of the same zone (Figure 1).
Whereas for sampling enclosure sites, three 400 m2plots were randomly placed within each of the three private enclosures
aged 20 to 30 years, for a total of nine plots (three plots within every
three enclosures). This methodology allows for representative sampling
of vegetation attributes within different management practices and was
chosen as it can help to identify differences and similarities between
them.
Vegetation Sampling
To quantify the structure of woody vegetation, we measured tree/shrub
densities, canopy diameters, canopy heights, and stem heights of
identified woody species in each 400 m2 plot. Canopy
cover was calculated using the average of the two longest canopy
diameters perpendicular to each other and parallel to the ground,
following the method of Greig- Smith (1983). Stem height was measured as
the total height of the plant stems from the ground level to the highest
foliage. For species with multiple stems, each stem was measured
separately, and the average was taken. Height measurements and canopy
lengths and widths were conducted for the whole plant by measuring
multiple stems as if it was one tree. To estimate woody aboveground
biomass (AGB) in a non-destructive way, we used biomass regression
equations (allometric equations) developed by Hasen-Yusuf et al. (2013).
For sampling herbs vegetation, we placed five sub-quadrats of 1
m2 in a zigzag pattern (i.e., four at all corners and
one at the middle position of each 400 m2 plot, (as
shown in Figure 2), making a total of 135 plots. From each of the 1
m2 quadrats, we collected samples of species,
richness, composition and biomass. We determined species richness as the
sum of all plant species present in the 1 m2 quadrats.
The nomenclature of the plant species followed the Flora of Ethiopia
(Hedberg and Edwards 1995). We estimated herbaceous species frequency by
dividing the total number of quadrats in which the species occurred by
the total number of quadrats studied in the 1 m2quadrats. The recorded species were categorized into three desirability
classes based on their preference for grazing by livestock animals,
using local ecological knowledge derived from herders and documented
literature (Jerry et al. 1989). Additionally, we identified all
herbaceous vegetation within the plots as either grass or non-grass
species (forbs) following Behnke (1986). We estimated aboveground herb
biomass by harvesting live and dead material at ground level. We weighed
the harvested samples in the field to obtain fresh weight. Thirty
percent of the harvested samples from each quadrat were placed in a
paper bag for later dry matter analysis. This harvested biomass was
dried in an oven at 105°C for 48 hours and then weighed to obtain the
dry matter. All measurements were made from September to December for
all study plots when the vegetation was at its peak flowering stage.
Data
Analysis
All statistical analyses were carried out using R Statistical Software
version 4.1.1. (R Core Team 2020). To determine the impact of
traditional grazing management practices on herbaceous species
composition, we used Canonical Correspondence Analysis (CCA) test on the
frequency of herbaceous species present in the 1 m2plots, and the “anova.cca” function in the vegan package in R
Statistical Software (Ter, 1986). CCA is a multivariate method that
examines the relationship between species and their environment (Aminet al. , 2023).The ordination diagram generated from CCA describes
the differential habitat preferences of taxa based on gradients. To
determine the impact of traditional grazing management practices on
woody species composition, we used the Analysis of Similarities (ANOSIM)
test on the number of each woody species counted in the 400
m2 plots, and the “anosim” function in the vegan
library R Statistical package. ANOSIM is a non-parametric test that
compares groups of samples based on any distance measure (Clarke and
Ainsworth, 1993). We also performed Analysis of Variance (ANOVA) tests
on species richness, biomass, woody density, and canopy cover using the
“aov” function to determine the effects of traditional grazing
management practices. The student–Newman–Keuls post hoc test for
differences in means, performed using the SNK.test function under theagricolae package (version 1.4.0), was used to compute
significant differences among management practices.