Deresse Teshome, Tolessa Terefe, Mamo Siraj, Bohnett Eve, Engdaw Getnet
Department of Environmental Sciences, College of Natural and Computational Science, Bule Hora University, Bule Hora Town, Ethiopia.
Department of Disaster Risk Management and Sustainable Development, Ambo University, Ambo Town, Ethiopia.
Environ Monit Assess. 2025 Jul 25;197(8):951. doi: 10.1007/s10661-025-14414-7.
The purpose of this study was to investigate the spatiotemporal trends and variability of climate impacts on coffee production in Abaya and Gelana Woredas. To clarify reliable data from the participants, the study utilized a mixed-research approach. Combining quantitative climate analysis (Mann-Kendall test, Sen's slope, and rainfall indices) with qualitative data from surveys and interviews, this research assessed how climate variability, socioeconomic factors, and physical conditions affect coffee yield. Statistical analysis (regression and t-tests) reveals significant climate trends across the study area, including warming nighttime temperatures (T), cooling daytime temperatures (T), and seasonal rainfall fluctuations. Rainfall trends varied among kebeles: In Bunata, Belg (Z = 1.07) and Meher (Z = 1.03) conveyed moderate but non-significant increases, although annual rainfall showed a near-significant decline (Z = - 1.84, Q = - 0.076). In contrast, Guangawa Badiya, Giwe, and Jirme exhibited positive rainfall trends in both Belg (Z = 2.21) and Meher (Z = 2.67), while Odo Mike experienced negative rainfall trends, particularly in Meher (Q = - 0.391) and annually (Q = - 0.660). Temperature trends revealed a decrease in T across all sites (Bunata - 0.61, Guangawa Badiya - 0.66, Odo Mike - 0.45, Giwe - 0.43), while T increased entirely, with notable seasonal variability in T. Regression modeling showed a strong correlation (R = 0.871) between climate variability, soil erosion, land size, and coffee production, explaining 83.2% of the variation in yields. Key adaptation strategies reported by farmers included intercropping (8.7%), income diversification (8.7%), cultivar selection (8.6%), agroforestry (8.5%), and integrated pest management (IPM) (7.8%). While rising T, decreasing T, and rainfall variability contributed to variations in coffee production in Guangawa Badiya, Giwe, and Jirme, these changes led to a decline in Bunata and Odo Mike. Coffee production has been impacted by climate change due to reducing the diurnal temperature range, hindering blooming and bean development, and making pests more vulnerable. Intense rainfall causes soil erosion and nutrient loss, while irregular rainfall impacts important development phases, resulting in flower drop and low yields. This study underscores the importance of adaptive strategies such as intercropping, agroforestry, income diversification, enhanced water management, and government support in ensuring the sustainability of coffee farming amidst ongoing climate fluctuations.
本研究的目的是调查阿巴亚和盖拉纳沃雷达斯地区气候对咖啡生产影响的时空趋势及变异性。为了从参与者那里获取可靠数据，该研究采用了混合研究方法。本研究将定量气候分析（曼-肯德尔检验、森斜率和降雨指数）与来自调查和访谈的定性数据相结合，评估了气候变异性、社会经济因素和自然条件如何影响咖啡产量。统计分析（回归分析和t检验）揭示了整个研究区域显著的气候趋势，包括夜间气温升高（T）、白天气温降低（T）以及季节性降雨波动。不同社区的降雨趋势各不相同：在布纳塔，贝尔格季（Z = 1.07）和梅赫尔季（Z = 1.03）降雨量有适度但不显著的增加，尽管年降雨量显示出接近显著的下降（Z = -1.84，Q = -0.076）。相比之下，广瓦巴迪亚、吉韦和杰尔梅在贝尔格季（Z = 2.21）和梅赫尔季（Z = 2.67）都呈现出正降雨趋势，而奥多迈克则经历了负降雨趋势，特别是在梅赫尔季（Q = -0.391）和全年（Q = -0.660）。温度趋势显示所有地点的T都在下降（布纳塔 -0.61、广瓦巴迪亚 -0.66、奥多迈克 -0.45、吉韦 -0.43），而T则完全上升，T存在显著的季节性变化。回归模型显示气候变异性、土壤侵蚀、土地面积和咖啡产量之间存在很强的相关性（R = 0.871），解释了产量变化的83.2%。农民报告的关键适应策略包括间作（8.7%）、收入多样化（8.7%）、品种选择（8.6%）、农林业（8.5%）和综合虫害管理（IPM）（7.8%）。虽然T升高、T降低和降雨变异性导致了广瓦巴迪亚、吉韦和杰尔梅的咖啡产量变化，但这些变化导致了布纳塔和奥多迈克的产量下降。气候变化对咖啡生产产生了影响，因为它缩小了昼夜温差，阻碍了开花和咖啡豆发育，并使害虫更容易滋生。强降雨导致土壤侵蚀和养分流失，而降雨不规律影响了重要的发育阶段，导致落花和低产。本研究强调了间作、农林业、收入多样化、加强水资源管理和政府支持等适应策略在确保咖啡种植在持续的气候波动中可持续发展的重要性。
