2.1 Site description
Laikipia County lies between latitudes 0° 25’ 47.1” N and 0° 17’ 53.7” and longitudes 36° 57’ 32.9” E and 36° 47’ 39.9” E. It has been classified as semi-arid and arid rangelands. It is found in agro ecological zone V and experiences two rainy seasons and transition periods from the wet season to the dry season (20).
The short rains begin in October and end in November and the main rainy season occurs in the month of April to May which is erratic. Laikipia County experiences an average rainfall of 600±50 mm per annum and a high-temperature range between 25-30°C and low from 12-17°C (2). The elevation of Laikipia County varies between 1,500 m above sea level at Ewaso Nyiro basin in the North to a maximum of 2,611 m above sea level. The dominant soil type is Vertisols followed by Oxisols (3). A summary of the soil characteristics is presented in table 1.
The soils are characterized by imperfectly drained grey to black clay – vertisols and planosols, expanding into the lowland that comprises of metamorphic rocks of gneisses and migmatites with well drained soils; mostly dark reddish brown consisting of ferric and chromic luvisols (Ngigi 2006). The dominant soil type is vertisols followed by red sandy soils (3). Other soil properties of the study area have been summarized in table 1.
Table 1: Soil properties and grazing characteristics in Ilmotiok and Mpala Ranch
Grazing management
|
|
Ilmotiok
|
Mpala
|
Land Ownership
|
|
Community
|
Private
|
Total Livestock biomass (TLU)
|
|
897
|
2074
|
Total livestock and wildlife (TLU)
|
|
1334.4
|
4572.7
|
Land area (Ha)
|
|
3651
|
19000
|
Stocking density (TLU/Km2)
|
|
37
|
24
|
Stocking intensity
|
|
Heavy
|
Light to moderate
|
|
|
|
|
Soil property
|
|
|
|
pH (H2O 1:2)
|
|
7.06
|
6.63
|
EC (dS/m)
|
|
0.13
|
0.07
|
Sand %
|
|
62.25
|
55.49
|
Silt %
|
|
26.99
|
32.25
|
Clay %
|
|
10.76
|
12.33
|
Texture class
|
|
Sandy clay loam
|
Sandy loam
|
Bulk density (g/cm3)
|
|
1.48
|
1.51
|
Total N (g/kg)
|
|
1.11
|
1.51
|
CN ratio
|
|
5.19
|
5.05
|
Total OC (%)
|
|
0.85
|
1.01
|
Source: Kibet et al., (2016)
The main economic activities in Laikipia County includes but not limited to, livestock production, tourism, private and public conservancies, ranching, small- and large-scale farming, horticultural farming, sand harvesting and quarrying. This has made the entire region to be dependent on pastoralism and charcoal production. Two adjacent ranches Mpala Research Centre and Ilmotiok Community group ranch in Laikipia County, Kenya were selected for the study in 2016. Controlled grazing is practised in Mpala ranch and has been characterized to practice low to moderate grazing intensity is with a stocking density of wildlife and cattle with the exclusion of elephants to be 24TLU/Km2. IIlmotiok community group ranch has been classified to have a stocking density of 37TLU/Km2 (Table 1) and categorized as heavy grazing intensity (1).
2.3 Experimental design and treatment
The experimental design was a completely randomized block design with a split plot arrangement. The main treatments were the grazing management practices, and land cover types were the sub-plots. Topographical positions were used as a blocking factor. Land cover types were selected randomly based on the most dominant cover that is bare ground, patches of grass and mosaic of trees. The topographical positions were classified into mid-slope, foot slope and bottom land (Figure 2) as described by (21).
Topographical positions classification
Topographical positions were first classified as described by (21). A permanent point of reference was defined within the gradient point (A-F) and the coordinates and altitude of this point were recorded using a GPS gadget. Topographical positions within the study area were point sampled as shown in Figure 2.
Topographical positions within each grazing management practices were point sampled using a clinometer and two rods marked at equal height. At the starting point (A), reference point, the first rod was held vertically and the second rod was held parallel 30 m from the first rod as shown in figure 1. Variation in topographical points was determined using Equation 1 below.
Δ Topographical point = distance between sampling point x clinometer reading (Equation 1)
A cloth tape was used to demarcate the length of each transect line. 10 of the points were marked either as bottom-land, mid-slope, or foot slope if 33 percent of the length of transect (200 m) was considered to be bottom-land, mid-slope, or foot slope. The ratios of each topo-class within each transect and the total lengths of all contour lines were calculated out of these values. At each topographical location, depending on the elevation of neighbouring topographical positions, it was graded as mid-slope (A-B), foot slope (B-C), or bottomland (C-D). In each topographic positions, land cover types, bare ground, patches of grasses and mosaics of trees were randomly selected and used to plot, a 200m transect and replicated 3 times. In each land cover type, soil samples were collected up to 30cm soil depth at intervals of 10cm. The soils were later tested for MAOC and POC.
2.4 Soil Sampling and analysis
Soil samples were collected from a flat surface which had been cleared of roots and grass using a calibrated soil auger at depth intervals of 10cm from the surface (0cm) up to 30cm soil depth. A total of 162 (1kg) soil samples were collected i.e
2 grazing management practices * 3 topographical positions * 3 land cover types * 3 soil depths * 3 replicates = 162 soil samples
The samples were tested for POC, and MAOC classified into various C fractions (22). 50g of fresh soil was weighed and dispersed with 10% calgon solution for 6 hours. Sieves with a mesh size of 2mm, 250 µm and 50 µm were arranged in that order and the dispersed soil sample was placed on the 2mm sieve and the process of wet sieving was carried out. After 20 minutes had elapsed, the fractions that were in each sieve were collected and oven dried at 65ºC for 24 hours. The weight of the dried samples was recorded and used to determine the percentage of carbon fractions in terms of 2mm - 250 µm POC, and >53-38 µm MAOC carbon. C concentration in each fraction i.e. POC and MAOC was further classified using the Walkley-Black method described by (23). C content was isolated in each sieve i.e. 2mm, 250 µm and 50 µm was further analysed for C concentration using the Walkley-Black method described by (23). Carbon content percentage was calculated using equation 2.
2.4.5 Statistical analysis
R software version 3.5.3 (24) was used to carry out a multiple ANOVA tests for POC, and MAOC data. Agricolae package was used to do post hoc analysis with Tukey HSD test for POC, and MAOC to separate the means at 5% significance level.