Molla Sisay Demeke, Zeleke Menberu Teshome, Tamiru Sisay Misganaw
Environment and Development, Department of Development and Environmental Management Studies, University of Gondar, Gondar, Ethiopia.
Environment and Development, Department of Geography and Environmental Studies, Debre Tabor University, Debre Tabor, Ethiopia.
Heliyon. 2023 Dec 8;10(1):e23399. doi: 10.1016/j.heliyon.2023.e23399. eCollection 2024 Jan 15.
In comparison to other types of resilience, livelihood resilience in the context of climate-related extremes like droughts is grounded in actual-life scenarios with the purpose of carefully assessing and improving the resiliency of individuals, households, communities, and nations. This study assesses households' livelihood resilience to droughts in Raya Kobo District. A mixed approach with a concurrent research design was used to achieve this goal. The quantitative data were collected from 354 randomly selected survey respondents, while the qualitative data were collected from purposefully chosen FGD and KI participants. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) models were employed to analyse the quantitative data, whereas thematic data analysis was used to analyse the qualitative data through the creation of major and sub-themes. To determine households' livelihood resilience, the livelihood resilience index (LRI) was measured using thirty-eight indicators of resilience based on the five livelihood assets. The study identified fifteen latent dimensions, such as infrastructure, technology, water harvesting scheme, land quality, cropping season, household working capacity, farm experience, educational status, social trust, risk response, social security, support service, income, crop diversity, and assets. The average score of these latent dimensions is 0.3999, suggesting that households in the study area are less resilient. The MLR results show a positive association between the latent dimensions and LRI and the relative importance of the latent dimensions for LRI. These findings provide significant policy implications regarding mitigating vulnerability, strengthening resilience, and establishing pathways out of livelihood insecurity. Education, healthcare, road construction, agricultural inputs (pesticides, herbicides, chemical fertilizers, and improved seeds), irrigation technologies (small-scale drip irrigation systems and human-powered pedals), income diversification, social trust, risk response, social security, support services, and asset building should be the focus of policymakers.
与其他类型的复原力相比,在干旱等与气候相关的极端情况下的生计复原力基于实际生活场景,旨在仔细评估和提高个人、家庭、社区和国家的复原力。本研究评估了拉亚科博区家庭对干旱的生计复原力。采用了一种混合方法和并发研究设计来实现这一目标。定量数据收集自354名随机选择的调查受访者,而定性数据收集自特意挑选的焦点小组讨论(FGD)和关键信息提供者(KI)参与者。主成分分析(PCA)和多元线性回归(MLR)模型用于分析定量数据,而定性数据分析则通过创建主要和子主题来进行。为了确定家庭的生计复原力,生计复原力指数(LRI)使用基于五种生计资产的38个复原力指标进行衡量。该研究确定了15个潜在维度,如基础设施、技术、集水方案、土地质量、种植季节、家庭工作能力、农场经验、教育状况、社会信任、风险应对、社会保障、支持服务、收入、作物多样性和资产。这些潜在维度的平均得分是0.3999,表明研究区域内的家庭复原力较低。MLR结果显示潜在维度与LRI之间存在正相关,以及潜在维度对LRI的相对重要性。这些发现为减轻脆弱性、增强复原力和建立摆脱生计不安全的途径提供了重要的政策启示。教育、医疗保健、道路建设、农业投入(农药、除草剂、化肥和改良种子)、灌溉技术(小型滴灌系统和人力踏板)、收入多样化、社会信任、风险应对、社会保障、支持服务和资产建设应成为政策制定者的重点。