P. Mugabe, H. Kipkulei, Stefan Sieber, Emmanuel Mhache, K. Löhr
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Effectively, 309 households were randomly sampled across the villages to provide the perception of climate change and associated impacts on agriculture and livelihoods. Both qualitative and quantitative statistical techniques were employed to analyse the incidence, frequency, and intensity of regional extreme climate events. The meteorological and climate modelling data were subjected to trend analysis using the Mann–Kendall and Sen’s slope estimator tests, and the present and projected spatial and temporal trends of climatic variables in the region were analysed. The household-based questionnaire results were combined with climate modelling and the literature to determine the implications of climate change for regional agricultural production and food security. The results revealed that local knowledge and climate model data strongly concur on regional climate changes. 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引用次数: 0
摘要
气候多变性影响着各种全球性挑战,包括粮食安全、生物多样性丧失、水资源短缺和人类福祉。然而,在空间明确层面上的气候模式和趋势以及社区感知却鲜有涉及。本文分别利用历史(1983-2010 年)和预测(2022-2050 年)气象和气候模型数据,研究了坦桑尼亚巴加莫约区气候条件的空间和时间趋势。研究还包括社区对过去气候事件的了解和经验。评估了预测气候变化对地区农业生产和粮食安全的影响。研究利用了在该地区七个村庄进行的家庭调查所获得的经验数据。实际上,各村随机抽样了 309 户家庭,以了解他们对气候变化的看法以及气候变化对农业和生计的相关影响。采用定性和定量统计技术分析了区域极端气候事件的发生率、频率和强度。利用 Mann-Kendall 和 Sen 的斜率估计检验对气象和气候模型数据进行了趋势分析,并分析了该地区气候变量目前和预计的空间和时间趋势。家庭问卷调查结果与气候模型和文献相结合,确定了气候变化对地区农业生产和粮食安全的影响。结果显示,当地知识和气候模型数据在区域气候变化方面高度一致。此外,该地区极有可能经历不同程度的升温和降水减少。气候趋势和模式的变化预计将极大地影响农业生产,影响生计,阻碍粮食安全工作。建议包括采取针对具体情况的措施和有针对性的战略,以提高整个地区的抗灾能力。
Examining climate trends and patterns and their implications for agricultural productivity in Bagamoyo District, Tanzania
Climate variability impacts various global challenges, including food security, biodiversity loss, water scarcity, and human well-being. However, climate patterns and trends and community perceptions at spatially-explicit levels have been minimally addressed. The spatial and temporal trends of climate conditions in Bagamoyo District in Tanzania were examined using historical (1983–2010) and projected (2022–2050) meteorological and climate model data, respectively. Community knowledge and experiences of past climate occurrences were included. The implications of projected climate change for regional agricultural production and food security were assessed. The study drew on empirical data obtained from household surveys conducted in seven villages in the district. Effectively, 309 households were randomly sampled across the villages to provide the perception of climate change and associated impacts on agriculture and livelihoods. Both qualitative and quantitative statistical techniques were employed to analyse the incidence, frequency, and intensity of regional extreme climate events. The meteorological and climate modelling data were subjected to trend analysis using the Mann–Kendall and Sen’s slope estimator tests, and the present and projected spatial and temporal trends of climatic variables in the region were analysed. The household-based questionnaire results were combined with climate modelling and the literature to determine the implications of climate change for regional agricultural production and food security. The results revealed that local knowledge and climate model data strongly concur on regional climate changes. Furthermore, the region is highly likely to experience increased warming and decreased precipitation at varying magnitudes. The shifts in climate trends and patterns are anticipated to greatly impact agricultural production, affecting livelihoods and hampering food security efforts. Recommendations include adopting context-specific measures and tailored strategies for enhancing resilience throughout the entire region.