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Doctor of Philosophy in Agriculture

Permanent URI for this collectionhttp://41.89.31.6:4000/handle/123456789/162

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Start date: 2018End date: 2019

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    Predicting Grazing Conflicts Based on Limited Resources in Northern Kenya
    (KeMU, 2019-09) Ikuathu, Dominic Maringa
    This study aimed at determining causes of grazing conflicts in Northern Kenya which were used to develop a conflicts predicting model. It specifically intended to evaluate seasonality of pasture resources, establishing how availability of grazing resources was related to grazing conflicts and predicting how communities were likely to cope with them. It was anchored on the theory that competition for limited forage triggers intra and inter-conservancy livestock movements, causing conflicts over grazing resources. The study used mixed methods of ecological, remote sensing and social survey designs. Purposive sampling was used to select four conservancies out of a population of fifteen, where three of them were community-managed while the fourth was privately owned which acted as a control. Two plots each measuring 50mx50m were set up in each of them using handheld Global Positioning System (GPS). Clip-dry-and-weigh method was used to assess grass biomass during dry and wet seasons. Five samples of clippings were obtained per plot using 0.5mx0.5m wire quadrant randomly in both seasons. Visual estimates were used to assess ground cover percentages, species variability and diversity along transects between the plots in both seasons and recorded in Range Condition Checklists and tables of quantities. A population of 106 respondents was picked through systematic random sampling from the lists of conservancy grazing committees and data collected using self-administered structured questionnaires, focused group discussions and content analysis of literature. The data was analyzed using Statistical Package for Social Sciences (SPSS) version 26. Frequency counts, means and percentages were computed for all quantitative data and results presented using frequency distribution tables and graphs. Qualitative data on status of the bio-physical, land-use and rainfall patterns were tracked using remote sensing techniques. Temporal and spatial variability of forage, land-use and land-cover changes were tracked using MODIS 250m resolution and Landsat-8 sensor, which were analysed using Quantum Geographical Information System (QGIS) to produce Normalized Difference Vegetation Indices (NDVI). The results established that forage and water availability and livestock numbers were responsible for the largest variability of grazing conflicts. It was found that seasonality of rainfall and the communities grazing regimes trigger livestock movements to unknown areas, sparking a trail of conflicts on their way. The research also found out that in the largest period of the year, community conservancies bore the greatest effects of environmental externalities due to lack of adherence to grazing plans leading to overgrazing and pasture degradation. It was further found that pastoral communities have different methods of copping with grazing conflicts in the study area. The study synthesized results on dependent and independent variables and came up with a new model for predicting grazing conflicts in Northern Kenya. The study recommended further investigations on the effects of other factors contributing to grazing conflicts that were not accounted for. It also recommended further research on methodology to establish the levels of competition for resources by different browsers. On practice, it recommended inclusion of structured dialogue in conflicts mitigation and diversification of social-economic activities by the pastoralists to cushion them from the effects of grazing conflicts. On policy, it recommended inclusion of local administration, national agencies and relevant stakeholders on conflicts mitigation processes to make them more authentic and resultant agreements enforceable.
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    Evaluation of The Effect of Regulated Deficit Irrigation and Soil Moisture Conservation Practices on Maize (Zae Mays) Performance
    (KeMU, 2018-08) David M., Mshimiyimana
    Though it is argued that the soils in most of Kenya's marginal rainfall areas have high potential for agriculture, low soil water constitutes a major limiting factor for crop production. Irrigation is one of the options used in such areas when ample water is available but it requires some adjustments when water is limited. Unfortunately little research has been done locally to understand how deficit irrigation can be used as a strategy for water conservation in those areas. This study investigated how regulated deficit irrigation and water conservation practices affect the growth, yields and water productivity of two maize varieties. The study consisted of a greenhouse experiment carried out at Kithoka, Meru County and field experiments at Marimanti, Tharaka Nithi County and Mailisaba, Isiolo County. Two irrigation treatments deficit irrigation except during exponential growth stage (DIE) and deficit irrigation except during the reproductive stage (DIR)) were compared to two controls (full irrigation throughout the season (Fl) and deficit irrigation throughout the season (DI)). Two irrigation schedules (half of the weekly water requirement applied per week (HA) and weekly water requirement applied every two weeks (DII)) were evaluated in the greenhouse experiment. Other treatments tested were ridging compared to a control (flatbed) and a superabsorbent polymer (SAP) compared to a control without SAP. Two maize varieties were used (DUMA 43 and KDV 2). Growth parameters measured were plant height and plant diameter measured every 15 days from 30 days after sowing. Yield indicators were stand count, number of productive plants per plot, ear diameter and length, above ground biomass, grain yield, and harvest index. The data collected was summarized in MS EXCEL and analyzed using SPSS version 22 for F-test, Post-hoc tests at a=5% and linear regression where necessary. FI gave significantly higher plant diameter (2.206 cm), plant height (148.02 cm), and grain yields (3019 kg/ha). DIR gave significantly higher harvest index (0.4665). Water productivity was the same for DIE, DIR and FI (0.5082, 0.4987, and 0.4828 respectively). Ridging had significantly higher values for above ground biomass (165.85 g), grain yield per plant (70.83 g), total grain yield (2419.6 kg/ha), harvest index (0.4283) and water productivity (0.5026 kg/m '). SAP had a significant effect on grain yield (2359.1 kg/ha) and on water productivity (0.4891). The highest yields were given by FI combined with ridges (3194.4 kg/ha) and FI combined SAP (3148.9 kg/ha). DUMA 43 gave significantly higher yields under DIE and DIR (2469.7 kg/ha and 2524.3 kg/ha) and better water productivity (0.5510 kg/m ' and 0.5310 kg/m ') compared to KDV 2. The study concluded that regulated deficit irrigation affects significantly maize growth, grain yields, and irrigation water productivity and the interaction between regulated deficit irrigation, ridging and SAP has a significant effect. Regulated Deficit Irrigation was recommended as a viable practice when water for irrigation is limited. Further research can be undertaken on the effect of different rates of SAP on maize growth, yields and water productivity under regulated deficit irrigation.