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Smallholder farmers’ perceptions and adaptation to climate variability in Kenya: a case study of Kaveta and Mikuyuni villages, Kitui County

Sun, 01 Jan 2017 00:00:00 GMT

Title: Smallholder farmers’ perceptions and adaptation to climate variability in Kenya: a case study of Kaveta and Mikuyuni villages, Kitui County Authors: Mutunga, Jane, E. Abstract: The productivity of the agricultural sector has been highly challenged by the effects of climate change and variability. The increasing temperatures and erratic rains, as well as diseases and pests have significantly reduced crop yields in the arid and semi-arid regions of Kenya. Many farmers in the grassroots have hardly adopted any response options and have continued to suffer losses in their agricultural outputs. The present study sought to assess the perceptions of smallholder farmers on climate variability in selected Villages in Kitui County, identify adaptation measures adopted by the farmers as well as the factors and constraints influencing their adaptation measures. Descriptive survey design was used. A total of 177 households were randomly selected to constitute the study sample. Data was coded and analysed using Ms Excel and SPSS version 20 statistical packages. Logit regression model was used to analyse factors influencing farmers’ adaptation to climate variability. The results established that most farmers had perceived a changing climate with more than 70% and 100% of the respondents in Kaveta and Mikuyuni Villages respectively, reporting that they noted an increase in temperature and a decrease in annual rainfall over the years. Results from Logit regression analysis showed that age, household size, education level, farming experience, off- farm income, access to extension services, access to credit facilities, access to climate information and weather forecasts significantly (p<0.05) influenced farmers’ adaptation to climate variability in both Kaveta and Mikuyuni Villages. Inadequate technological capacity (78.2%), limited access to credit facilities (72.2%), limited access to extension services (68%) and high cost of adaptation (66.8%) were reported as the major constraints to farmers’ adaptation to climate variability in Kaveta Village while lack of access to irrigation water (89.6%), lack of labour (86%), high cost of adaptation (81.4%), unreliable weather forecasts (81.4%), inadequate land resources (76.4%) and inadequate financial resources (74%) were the major constraints to the farmers’ adaptation to the increasing temperature and changing rainfall patterns in Mikuyuni Village. From the study, it can be deduced that farmers from the drier area were more conscious of climate variability and thus adapted more to climate variability than farmers in the wetter areas

Contribution of forest provisioning ecosystem services to livelihoods of smallholder farmers adjacent Chyulu Hills forest

Tue, 01 Jan 2019 00:00:00 GMT

Title: Contribution of forest provisioning ecosystem services to livelihoods of smallholder farmers adjacent Chyulu Hills forest Authors: Minoo, Vicoria, M. Abstract: Forests are believed to play critical ecological, social, cultural, and economic role to the livelihoods of smallholder farmers in Kenya and even all over the world. Forestry Provisioning Ecosystem Services (FPES) contribute significantly to smallholder farmers‘ livelihoods though this contribution is sometimes not accounted for. Understanding the role played by FPES to the livelihood of smallscale farmers is crucial for sustainable management of the forest resources. This study therefore sought to investigate the contribution of FPES to the livelihoods of smallholder farmers adjacent Chyulu hills forest, Makueni County. The specific study objectives were to; (i) Identify the type of FPES provided by Chyulu hills forest to the adjacent communities (ii) Evaluate the contribution of FPES to the household income of smallholder farmers adjacent Chyulu hills forest and (iii) Assess factors influencing utilization of the Chyulu hills FPES. A survey research design was used. Stratified and purposive sampling methods were used to select the specific study Sub-locations. A sample size of 62 respondents was selected in the two Sub-locations using the coefficient of variation method (Nassiuma, 2000). Frequency distribution was used to determine the type of FPES extracted from Chyulu hills forest and the contribution of FPES to the household income of smallscale farmers. Logit regression model was used to analyze data on factors influencing utilization of the Chyulu hills forest. The results established that farmers in both Sub-locations extracted FPES with the 37.5% and 64.3% of the respondents in Mang‘elete and Kiu Sub-locations, respectively extracting the services from the forest. The types of FPES extracted from Chyulu hills forest were mainly food and medicinal plants. In Mang‘elete Sub-location, the most extracted food material was vegetables (44.4%) while in Kiu Sub-location honey was the most extracted at 87.5%. In Mang‘elete the most extracted herbal was Terminalia brownie (52.4%) while in Kiu Sub-location the most extracted was Grewia bicolor (60.9%). Results further showed that FPES contributed a substantial amount of money to the income of the respondents with total mean income from FPES in the two Sublocations being Ksh 811.36 (8.4%) while that from other sources such as farming being Ksh 8,907.53 (91.6%). There was a significant difference between the monthly mean incomes (Mang‘elete (M= 355.56, SD= 1,252.04) and Kiu (M= 1,267.17, SD=3,085.60, t (58) = -2.26, p<0.05) accrued from the sale of forest products. Logit regression results showed that occupation of the household head, distance from Chyulu hills forest and presence of fence significantly (p<0.05) influenced utilization of Chyulu hills FPES in Kiu and Mang‘elete Sub-locations. The study concluded that forest dependency is a reality irrespective of whether legal or illegal. It is recommended that conservation be enhanced by creating awareness of forest benefits to the community and training them on sustainable use of resources.

Evaluation of farmers’ vulnerability to climate variability and extreme events in selected agro-ecological zones in Kitui County, Kenya

Wed, 01 Jan 2020 00:00:00 GMT

Title: Evaluation of farmers’ vulnerability to climate variability and extreme events in selected agro-ecological zones in Kitui County, Kenya Authors: Kamau, Mercy W. Abstract: Climate variability and extreme events are some of the most pressing environmental challenges occurring in the contemporary world. Farming communities in Sub-Saharan Africa, particularly in Kenya are more vulnerable to climate variability and extreme events due to high dependence on weather patterns in their farming activities. There is little understanding of the vulnerability to climate variability and extreme events among farmers in Kitui County based on the agroecological zones. This study evaluated farmers’ vulnerability to climate variability and extremes and adaptation strategies adopted in selected parts of Kitui County using data collected from 341 households in Yuku, Kaveta, Kauwi and Kasaini sub-locations which represented arid, semihumid, semi-arid and transitional zone from semi-humid to semi-arid agro-ecological zones respectively. Purposive sampling method was applied in identifying the sub-locations of study while proportionate and systematic sampling were used to select the households which formed the units of analysis. Analysis on vulnerability was based on indices constructed from carefully selected indicators for exposure, sensitivity, and adaptive capacity. The indicators were weighted using Equal Weight Analysis. Vulnerability indices indicated that Yuku sub-location was the most vulnerable to climate variability and extreme events (1.487) followed by Kauwi (0.214), Kasaini (0.085) and Kaveta sub-location (-0.530). Further, the results indicated that farmers the study areas had adopted multiple adaptation strategies in response to climate variability and extreme events. Results of the logistic regression analysis showed that gender, education level, farming experience and age significantly (p<0.05) influenced adoption of adaptation strategies to climate variability and extreme events in the study areas. Policy measures and development efforts should be focused towards addressing the factors that influence adoption of adaptation strategies while improving the adaptive capacity of farming households in Kitui County.

Assessment of rain water harvesting technologies for improved food security in Kauwi sub-location, Kitui County

Sat, 01 Jan 2022 00:00:00 GMT

Title: Assessment of rain water harvesting technologies for improved food security in Kauwi sub-location, Kitui County Authors: Koreeny, Modvine Abstract: Water is an essential natural resource, vital for any development to take place. However, not more than one percent of the water is freely available for human needs including agricultural production in the entire world. Arid and semi-arid lands globally are facing water scarcity challenges. Rainfed agricultural system is the major farming method in these areas, but this has been challenged greatly by aridity and climatic uncertainty. Kitui County is an ASAL where farmers are experiencing little annual rainfall averagely as well as varying temporal and spatial rainfall supplyhence the need to evaluate use of rain water harvesting technologies in the area. The main aim of this study was to assess rain water harvesting technologies for enhanced security of food in Kauwi sub-location, Kitui County. Specifically, the study aimed at studying the extent of utilization of the rain water harvesting technologies, factors that influence utilization of rain water harvesting technologies and exploring farmers’ perception of effectiveness of rain water harvesting technologies in Kauwi sub-location, Kitui County. The study adopted a survey design. Random sampling was used to identify the villages and systematic sampling applied in selecting the households to be interviewed. Data was collected through personal observation and administering interview schedules to a sample size of 160 households. From the logistic regression model, Zai pits variation was explained at 45% and cases correctly predicted at 93.1% where age p<0.05, B=0.11 and land size, p<0.05, B=0.56 were factors that significantly influenced its utilization. This study has generated information to be used by the farmers to help in prioritizing factors that influence decision on utilizing rain water harvesting technologies. The ministry of agriculture can use this information as a guideline for designing agricultural developments strategies. The Policy makers can use this information to develop agricultural policies.