The value of pastoralism practiced in Kenya is not well appreciated, even though it is said to be enormous. The available statistics tend to underestimate this value from the point of view of its contribution to the local and national economies, due to the inadequacy of data and application of inappropriate valuation methodologies. This study analysed the contribution of pastoralism to Kenya's national economy, using the total economic value (TEV) approach and by considering the traditional and non-traditional pastoral values. Secondary data were collected on livestock population, herd composition and structure, honey, beeswax, firewood, fishing and tourism. The findings of this study show that Kenya's pastoral sector has an economic worth of US$1.

This study establishes the determinants of household vulnerability to food insecurity in pastoral households of Kajiado and agropastoral households of Makueni Counties of Kenya. A randomly selected sample of 198 households was interviewed. Descriptive analysis showed that pastoral households of Kajiado County were more vulnerable to food insecurity (VFI) with a VFI of 0.59 than agropastoral households in Makueni County, who had a VFI of 0.27. Further, a two stage least squares approach established that vulnerability of households to food insecurity is determined by land size, household size, rainfall and herd size for Makueni County and access to climate information, herd size, off-farm employment and gender of the household head for Kajiado County. The findings imply that Makueni County needs access to and control over land resources, destocking through improved livestock breeds and creation of a microclimate to enhance rainfall levels. For Kajiado County, policies need to promote access to climate information, diversification of livelihoods and female access to production resources.

The causes of land degradation in the African drylands have been shown to vary. Some researchers consider climate to be the major contributor to degradation, with anthropogenic factors playing a minor role. Others reverse the significance of these two factors. A third group attributes land degradation to climate and anthropogenic factors equally. This study was undertaken to establish the factors influencing land degradation in a semi-arid environment in southeastern Kenya and the rate of change in vegetation types for a period of 35 years (1973-2007). The reduction in grassland cover was used as an indicator of land degradation. Causes of land degradation were determined by a multiple regression analysis. A log-linear regression analysis was used to establish the rate of vegetation change. The multiple and log-linear regression analyses showed: (1) woody vegetation, livestock population and cultivated area to be the main contributors of reduction in grassland cover in the area, and (2) an increase in undesirable woody species, livestock population and cultivated area had a significant (P<0.05) negative effect on grassland vegetation. Increased human population, low amounts of rainfall and drought showed no significant negative effect on grassland vegetation cover. In conclusion, human and livestock population growth and increased agricultural land have contributed to intensive crop cultivation and overgrazing in the semi-arid lands. This overuse of the semi-arid rangelands has worsened the deterioration of the natural grassland vegetation.

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Vulnerability to climate change impact is the most pressing issues for less developed countries whose economy mainly depends on the agricultural sector. The demand for food is growing swiftly whereas impacts of climate change on the global food production are increasing. More area specific research outputs and evidences-based policy directions are needed to tackle the ever changing climate and to reduce its impacts on the agricultural production. The aim of this study was to investigate subsistence farmer household’s vulnerability level to climate change impacts and its associations with household’s agricultural production. Then primary data was collected from 400 households from Kolla Temben District, Tigray Regional State, North Ethiopia. Multistage sampling techniques were applied to select households for interview from the district. In the first stage, 4 Kebelles (Kebelle - administration unit) were selected randomly out of 27 Kebelles and then400 households were selected for interview through systematic random sampling techniques (Figure 1). Multiple regressions were used to examine the associations between household’s vulnerability to climate change impacts and agricultural production. Grounded theory and content analysis techniques were use to analyze data from key informant interviews and focus group discussions. For every single unit increase in household vulnerability to climate change impacts, there was an average agricultural production decrease between 16.99 and 25.83 (Table 4). For single unit increase in household’s vulnerability to climate change impact, there was a decrease of total crop production, Total income, total livestock, total food consumption and food consumption per adult equivalent. Rainfall decrease, small farmland ownership, steep topography, frequent flood occurrences and large family size are among the major factors that negatively affect household’s agricultural production and total income. The more the vulnerable the households, the less in total annual crop production, total livestock size, total income from agricultural production and the more dependent on food aid). There is a negative association between household’s vulnerability level to climate change impacts and agricultural production (crop production, total livestock ownerships and total income from crop production). More access to irrigation and agricultural fertilizers, improved varieties of crops, small family size, improve farmland ownership size, more access to education and Agricultural Extension services are an effective areas of intervention to improve household’s resilient, reduce households vulnerability level to climate change impacts and increase household’s total agricultural production.