PHD-Department of Environmental Studies and Community Development

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Browsing PHD-Department of Environmental Studies and Community Development by Author "Mwoga, Gilbert Muthee"

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    Topo-sequence analysis of climate variability and land use changes among smallholder farmers in Meru County, Kenya
    (2014) Mwoga, Gilbert Muthee
    Land use change in Meru is increasingly being influenced by among other factors climatic variability, with consequent implications on community livelihoods. This study sought to assess the relationship between land use changes and climatic variability in this area with the ultimate aim of deriving lessons towards sustainable agricultural land management. A topo-sequence approach was used in order to capture specific effects across different agro-ecological zones. Rainfall data ranging from 1976 to 2009 for three stations, daily temperature and stream flow discharge served as hydro-climatic data. Geographic Information Systems generated land use data for the period 1976-2011. This information was triangulated with data from household surveys, key informants interviews, and focused group discussions. Other data were analysed using standard procedures. Future implications of land use changes were assessed by use of exploratory scenarios analysis. Findings indicated that the key evidence of climate variability was variations in rainfall, which influences planning for land productivity. In the low highland 1, coefficient of variability in rainfall amount for first season (i.e. March-May) was 0.43 and 0.26 for second season (i.e. October-January). For the upper midland 2 and in the transition zone with upper midland 3 the coefficient of variability for first season was 0.36 and 0.37 respectively. As such the first season was the main determinant of land use performance in both upper midland and low highland agro-ecological zones. Stream flow coefficient of variability ranged between 0.22 and 0.44 with months of February and September being more variable, while April and December were less variable. Therefore, proper management of water resources in the months of February and September is critical. There were variations in mean annual temperatures between low highland 1 and in upper midland 2. The observed increase in annual mean temperature trends in low highland 1 was linked to decreasing forest cover. That majority of the respondents (91.6%) concurred that there was climate variability is indicative of increasing awareness of this global threat and hence opportunity for spontaneous community participation in intervention measures. Observed land use changes could not however be linked to decadal rainfall trends, implying that other factors were at play in influencing land use trends. In six out of the seven sub-agroecological zones there were changes in land use types but no marked changes were detected in low midland 4 perhaps as a result low population density arising from absentee land lords, boundary disputes and poor infrastructure. While In low highland 1, upper midland 1, 2 and 3 and low midland 3, areas under agricultural use increased while that under forest decreased. In low midland 6 shrubs were replaced by rainfed crops (r² = 0.98) an indication that natural vegetation was being cleared for cultivation. Scenarios analysis suggests that agricultural land use would cover up to 86% by 2025 thus effectively replacing forested area and hence services there-from. Since there was some divergence in observed and perceived climate variability parameters, there is need to integrate farmers and scientific approaches in mitigation planning against effects of climate variability. Planning for effective land performance needs to be season based and agro-ecological zone specific. Emerging land uses which included tea and irrigated crops have had only short term gains. Continuing reduction in forest cover and stream volumes are likely to negatively impact community livelihoods in future. Strategic interventions that integrate policies, structures and process are needed for land use planning at the county and household levels to mitigate and adapt to climatic variability and its implications.