| dc.description.abstract | 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. | en_US |
