How do migration decisions and drivers differ against extreme environmental events?
How do migration decisions and drivers differ against extreme environmental events?
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移民决策和驱动因素与极端环境事件有何不同？
DOI：
10.1080/17477891.2023.2195152
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Samanta, Gopa
中科院分区：
文献类型：
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作者：
Mallick, Bishawjit;Best, Kelsea;Carrico, Amanda;Ghosh, Tuhin;Priodarshini, Rup;Sultana, Zakia;Samanta, Gopa
移徙往往被理解为应对环境威胁和气候变化影响的一项生计战略。然而，由于环境事件的类型、严重性和频率的不同，移民决策的不同程度还鲜有人探讨。本文通过对孟加拉西南部地区的家庭调查来探索这一研究差距。多项回归模型被用来模拟在快速发生(即气旋和洪水)和缓慢发生(盐碱化、淤积和河岸侵蚀)环境现象的背景下所报告的未来移民决策(200个样本家庭)。结果表明：i)以前的灾害经历和社区中不断增加的冲突在缓发现象(盐度)的背景下促使在不久的将来进行移徙；(Ii)经济实力和自我效能感在突发事件和慢发事件的背景下都会增加不移徙意愿；以及(Iii)这些对移徙的影响的程度和模式因人口统计而异，包括教育、宗教和年龄。重要的是，这一分析表明，移民决定与环境事件的类型、严重性和频率之间的关系受到社会经济条件的影响。因此，这项研究支持专门针对极端环境事件的类型和暴露而量身定做的未来适应规划。
Migration is often understood to be a livelihood strategy to cope with the effects of environmental threats and climate change. Yet, the extent to which migration decisions differ due to the type, severity, and frequency of environmental events has been little explored. This paper employs household surveys in southwestern Bangladesh to explore this research gap. A multinominal regression model is used to simulate reported future migration decisions (200 sample households) in the context of both rapid-onset (i.e. cyclone and flood) and slow-onset (salinity, siltation, and riverbank erosion) environmental phenomena. Results show: i) previous disaster experience and increasing conflict in the community motivate migration in the near future in the context of slow-onset phenomena (salinity); (ii) economic strength and self-efficacy increase non-migration intention in both contexts of sudden and slow-onset events; and (iii) the extent and pattern of these influences on migration differ across demographics, including education, religion, and age. Importantly, this analysis shows that the relationship between migration decisions and the type, severity, and frequency of environmental events is influenced by socioeconomic conditions. Therefore, this research supports future adaptation planning specifically tailored to the type and exposure of extreme environmental events.