Land use and climate change adaptation strategies in Kenya

Climate variability and change mitigation and adaptation policies need to prioritize land users needs at local level because it is at this level that impact is felt most. In order to address the challenge of socio-economic and unique regional geographical setting, a customized methodological framework was developed for application in assessment of climate change vulnerability perception and adaptation options around the East African region. Indicators of climate change and variability most appropriate for the region were derived from focused discussions involving key informants in various sectors of the economy drawn from three East African countries. Using these indicators, a structured questionnaire was developed from which surveys and interviews were done on selected sample of target population of farming communities in the Mt. Kenya region. The key highlights of the questionnaire were vulnerability and adaptation. Data obtained from respondents was standardized and subjected to multivariate and ANOVA analysis. Based on principle component analysis (PCA), two main vulnerability categories were identified namely the social and the bio-physical vulnerability indicators. Analysis of variance using Kruskal-Wallis test showed significant statistical variation (P¿=¿0.05) in the perceived vulnerability across the spatial distribution of the 198 respondents. Three insights were distinguished and were discernible by agro-ecological zones. Different vulnerability profiles and adaptive capacity profiles were generated demonstrating the need for prioritizing adaptation and mitigation efforts at local level. There was a high correlation between the bio-physical and social factor/livelihood variables that were assessed

Land use and climate change adaptation strategies in Kenya.

Climate variability and change mitigation and adaptation policies need to prioritize land users needs at local level because it is at this level that impact is felt most. In order to address the challenge of socio-economic and unique regional geographical setting, a customized methodological framework was developed for application in assessment of climate change vulnerability perception and adaptation options around the East African region. Indicators of climate change and variability most appropriate for the region were derived from focused discussions involving key informants in various sectors of the economy drawn from three East African countries. Using these indicators, a structured questionnaire was developed from which surveys and interviews were done on selected sample of target population of farming communities in the Mt. Kenya region. The key highlights of the questionnaire were vulnerability and adaptation. Data obtained from respondents was standardized and subjected to multivariate and ANOVA analysis. Based on principle component analysis (PCA), two main vulnerability categories were identified namely the social and the bio-physical vulnerability indicators. Analysis of variance using Kruskal-Wallis test showed significant statistical variation (P ≤ 0.05) in the perceived vulnerability across the spatial distribution of the 198 respondents. Three insights were distinguished and were discernible by agro-ecological zones. Different vulnerability profiles and adaptive capacity profiles were generated demonstrating the need for prioritizing adaptation and mitigation efforts at local level. There was a high correlation between the bio-physical and social factor/livelihood variables that were assessed

Evaluating Diversity Among Kenyan Papaya Germplasm Using Simple Sequence Repeat Markers

Papaya is an important fruit crop, produced in Kenya for local consumption and export. Despite a history of varietal introductions, no attempts concerned on developing varieties suited to Kenyan conditions have been documented. The objective of this study was to provide information on the diversity of germplasm available in Kenya, as a precursor to systematic plant breeding program. Forty two papaya accessions were collected from farmers’ fields located in Coast, Rift Valley, Western, Nyanza, Central and Eastern provinces. Genetic diversity was determined using seven simple sequence repeat (SSR) markers, computing allelic richness and frequency, expected heterozygosity and cluster analysis. Results indicated that the markers were highly polymorphic among the accessions, with polymorphic information content (PIC) varying from 0.75 to 0.852 with an average of 0.81. The genetic similarity among the 42 papaya accessions ranged from 0.764 to 0.932 with an average of 0.844 showing that most papaya accessions used in this study were closely related. About 96.9% of the pair-wise comparisons among papaya accessions exhibited genetic similarity greater than 0.802, while less than 4% (3.1%) showed genetic similarity lower than 0.802. The phylogenetic analysis grouped the 42 accessions into two main clusters A and B. Cluster A had four sub-clusters while cluster B had one cluster. Accessions from Coast, and some from Rift Valley Provinces, presented the highest variation, being scattered throughout the tree, with little or no differentiation from most accessions, whereas some accessions from Coast regrouped in clusters A (iv) and B. The genetic differences among the accessions revealed by the formation of distinct clusters suggest significant genetic variability emanation from varying sources of the papaya germplasm in Kenya. Although the level of genetic diversity revealed by SSR markers in this study is sufficient to distinguish between breeding lines for varietal protection, the rather narrow genetic diversity demonstrated indicates the need to introduce new germplasm or use other techniques such as mutation and genetic engineering to provide breeding materials for the future improvement of papaya in Kenya