Most previous studies on vulnerability of smallholder farmer’s livelihood to climatic hazards had focused on large scale, global, regional or national levels. In addition, they gave more focuses to assessment of impacts of climatic hazards to farmers than assessment of farmer’s vulnerability to climatic hazards. Thus, this study was designed to bridge this gap by assessing vulnerability of farmer’s livelihood at household level measured as perceived sensitivity and lack of adaptive capacity to climatic hazards and by exploring sets of socioeconomic indicators that significantly determine vulnerability of farmers’ livelihoods. Cross-sectional data was collected through household survey from 379 randomly selected respondents which were also complemented with qualitative assessments. Principal component analysis was used to identify major socioeconomic indicators that contribute to vulnerability of farmer’s livelihood using orthogonal axis rotation in SPSS version 20. Binary logit model was used to identify principal socioeconomic indicators that significantly influence sensitivity and adaptive capacity of livelihoods of sampled farmers. The findings revealed that households that are heterogeneous in location of residence, sources of income, ownership to animals have significant influence on perceived sensitivity of farmers to climatic hazards. However, socioeconomic indicators such as age, gender, family size, have insignificant influence on sensitivity of farmer’s livelihood to climatic hazards. Gender, marital status, educational status of household head, coping mechanisms like grain & cash saving, NRM practices has significant influence on perceived adaptive capacity of farmers. Yet, access to social interconnectedness such as idir or iqub, family relatives, and cost of drinking water has insignificant influence on perceived adaptive capacity of farmers. Currently, 59%, 38% and 3% of sampled farmers have overall vulnerability status of low, moderate and high respectively. The overall conclusion is that differences in status of vulnerability of their livelihoods are attributed to differences in their present socioeconomic attributes. Community should strengthen existing hazard coping mechanisms whilst GOs and NGOs should support farmers in diversification of income sources and restocking of animals. Active community engagement in planning and execution of disaster risk reduction strategies and practices is also indispensable.
Table of Contents
Chapter I: Introduction
1.1 Background of the study
1.2 Statement of the problem
1.3 Objectives of the Study
1.3.1 General Objective
1.3.2 Specific Objectives
1.4 Research Questions
1.5 Significance of the study
1.6 Scope of the study
1.7 Limitation of the study
1.8 Organization of the study
Chapter II: Related Literature Review
2.1 Conceptual Literature
2.2 Definitions
2.3 Conceptual framework
2.4 Empirical Literature
2.4.1 Descriptive Analysis
2.4.2 Indicators Approach
2.4.3 Econometric Approach
2.4.4 Integrated Method
2.4.5 Principal Component Analysis
2.5 Literature gaps
Chapter III: Description of the Study Area and Methods & Materials
3.1 Brief description of the study area
3.1.1 Location
3.1.2 Socioeconomic status of Siraro district Farmers
3.1.3 Demographic features
3.2 Research Methods and Materials
3.2.1 Study design
3.2.2 Data Types and Sources
3.2.3 Sampling Techniques and Sample Size Determination
3.2.4 Data Collection Methods
3.2.5. Analytical framework
3.2.6 Methods of data Analysis
3.2.7 Data validity and reliability
3.2.8 Ethical considerations
Chapter IV: Data Presentation and Analysis
4.1 Location of respondents by Agro ecology & sampled kebeles
4.2 Household Characteristics
4.2.1 Demographic characteristics
4.2.2 Ethnic background and Religion of household heads
4.2.3 Human Capital
4. 3 Exposure of households to climate variability induced hazards
4.3.1 Farmer’s perception on trends of intensity of climatic hazards
4.3.2 Frequencies of climate variability induced hazards experienced
4.3.3 Climate Information
4.4 Livelihood Characteristics
4.4.1 Household’s Major Livelihood Means
4.4.2 Access to Natural Capital
4.4.3 Access to Financial Capital
4.5 Access to Physical Capital
4.5.1 Access to safe water supply
4.5.2 Access to Transportation and Markets
4.5.3 Access to Social Capital
4.6. Sensitivity of farmers’ livelihoods to climatic hazards
4.7 Adaptive capacity of smallholder farmers’ livelihoods
4.7.1 Awareness and participation of farmers on climate adaptation initiatives
4.7.2 Coping mechanisms to climate variability induced hazards
4.7.3 Farmers’ medium/long term adaptation strategies to climatic hazards
4.8 Test of Independence/Goodness of Fit Test
4.8.1 Test of Association between Sensitivity and socioeconomic indicators
4.8.2 Test of Association between Adaptive Capacity and socioeconomic indicators
4.9 Multivariate Analysis of Indicators of Vulnerability
4.9.1 Determinants of Vulnerability of smallholder farmers to climatic hazards
4.9.2 Communalities of indicators
4.9.3 Total Variance Explained by Retained Components
4.9.4 Factor loadings of retained components
4.10 Influences of factors on Sensitivity and Adaptive Capacity of Livelihoods
4.10.1 Sensitivity of livelihoods to climatic hazards
4.10.2 Adaptive capacity
4.10.3. Aggregate Vulnerability and Relative Status of Farmers’ Livelihoods
Chapter V: Conclusion and Recommendations
5.1 Conclusion
5.2 Recommendations
5.2.1 Community
5.2.2 Government and NGOs
Research Objectives and Focus
This study aims to assess the vulnerability of smallholder farmers' livelihoods at the household level in the Siraro district to climate variability-induced hazards. By analyzing perceived sensitivity and adaptive capacity, the research identifies key socioeconomic indicators that significantly influence the vulnerability status of farming households, ultimately contributing to better resilience-building strategies.
- Assessing the sensitivity of household livelihood means to climate variability.
- Exploring current resilience and adaptation strategies adopted by farmers.
- Identifying demographic and socioeconomic indicators influencing vulnerability.
- Categorizing households based on their vulnerability status to climate variability.
- Informing disaster response plans and policy updates for local environmental management.
Excerpt from the Book
4.2.1 Demographic characteristics
As indicated in table 3, 81% (307) of the sampled respondents are male headed households while the remaining 19% (72) are female headed households. Middle age (30-45 years) respondents constitute to the largest proportion (66.2%) followed by young age (up to 29 years) constituting 15.6% and an age interval of 46-61 years with 12.7 % of the total sampled household heads. Old age (62 years and above) constitutes to 5.5% of the total sampled household heads. Largest number of middle age group is an indication of availability of large number of reproductively active age groups which in turn shows large number of dependent children in the study population. Table 3
With regard to marital status of household heads, the result depicted on table 3, shows that 50.4% (191) of the total 379 household heads surveyed are monogamously married followed by 26% (99), 19% (72) & 4.5% (17) who are polygamous, widowed and separated respectively. Polygamous marriage is common in Siraro district like many other areas dominated by Islam religion followers. There was no single household head interviewed even if the choice was included in the survey.
In terms of family size per household head using size intervals, the household survey result shows that the largest proportion (62.0%) of total respondents has 6-10 family size followed by 33.2 % & 4.7 % who have 1-5 & >=11family members that the household heads are responsible to care for respectively. The average family size was 6.66 per household head which is consistent with the CSA projection of 6 persons per household for the district. However, it should be noted that in case of polygamous marriage, family size is higher per household head as the household head is responsible to all family members living in two, three or four households with their respective mothers. Yet, large family size has both negative and positive impacts to the households to adapt to impacts from climate variability.
Summary of Chapters
Chapter I: Introduction: Provides the research background, the problem statement regarding climate hazards in Siraro district, study objectives, and research questions.
Chapter II: Related Literature Review: Offers a critical review of key concepts related to climate variability, vulnerability of social ecosystems, and empirical studies on rural livelihoods.
Chapter III: Description of the Study Area and Methods & Materials: Describes the geography of Siraro district and details the study design, sampling techniques, and data collection methods used.
Chapter IV: Data Presentation and Analysis: Analyzes household characteristics, exposure to hazards, livelihood strategies, and the multivariate analysis of vulnerability indicators.
Chapter V: Conclusion and Recommendations: Summarizes the major findings regarding livelihood vulnerability and provides actionable recommendations for the community and government agencies.
Keywords
Climate Variability, Livelihood Vulnerability, Smallholder Farmers, Siraro District, Ethiopia, Adaptation Strategies, Adaptive Capacity, Sensitivity, Socioeconomic Indicators, Disaster Risk Reduction, Household Survey, Rainfall Variability, Flooding, Principal Component Analysis, Resilience.
Frequently Asked Questions
What is the primary focus of this research?
The research examines the vulnerability of smallholder farmers' livelihoods in the Siraro district of Ethiopia in response to climate variability-induced hazards like rainfall variability and flooding.
What are the central themes of the work?
The core themes include social vulnerability, exposure to climate extremes, household livelihood characteristics, adaptive capacity, and the influence of socioeconomic factors on farmer resilience.
What is the main objective of the study?
The goal is to assess household-level vulnerability by identifying socio-economic indicators that influence how farmers perceive and adapt to climatic shocks, ultimately contributing to local resilience building.
Which scientific methods were employed?
The study utilizes a cross-sectional mixed-method design, employing descriptive statistics, Principal Component Analysis (PCA) for indicator reduction, and binary logit models to determine the factors influencing vulnerability.
What topics are covered in the main body?
The body covers household demographic characteristics, climate hazard exposure, livelihood means, access to capitals (natural, social, physical, financial), and multivariate analysis of vulnerability determinants.
Which keywords define this work?
Key terms include Climate Variability, Livelihood Vulnerability, Smallholder Farmers, Adaptive Capacity, and Disaster Risk Reduction.
How does landholding size affect vulnerability in Siraro?
The study notes that landholding size is shrinking, and most farmers manage less than 0.5 hectares, forcing them to rely on renting land or diversification strategies to survive climatic shocks.
What role does the "Productive Safety Net Program" (PSNP) play?
The PSNP serves as a short-to-medium-term adaptation practice, helping households build assets and manage food insecurity, though participation varies significantly across the district.
How is "Adaptive Capacity" measured in this research?
Adaptive capacity is defined as the farmers' awareness, engagement in coping mechanisms, and the practice of at least one adaptation measure to deal with climate variability.
What are the key conclusions regarding the vulnerability status of farmers?
The findings indicate that 59.5% of farmers have low, 37.7% have moderate, and 2.6% have high vulnerability status, with differences largely attributed to their specific socio-economic and demographic attributes.
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- Jarso Wakeyo Utala (Autor:in), 2016, Vulnerabilty of farmer's livelihood to climate variability induced hazards in Siraro District, West Arsi Zone, Oromia, Regional State, Ethiopia, München, GRIN Verlag, https://www.grin.com/document/461981
