How do migration decisions and drivers differ against extreme environmental events?

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.

Livelihood challenges of 'double strike' disasters: Evidence from rural communities of southwest coastal Bangladesh during the Covid-19 pandemic and cyclone Amphan.

The Covid-19 pandemic has adversely affected livelihoods in the Global South and exacerbated the effects of natural disaster. This study examines the 'double strike' of the Covid-19 lockdown and 'super-cyclone' Amphan on the 12 villages of Dakshin Bedkashi Union, southwest Bangladesh. It employs questionnaire surveys to assess the impact of the compound disaster on rural livelihoods over a period of five months, comparing pre-lockdown, post-lockdown, and post-Amphan phases. The results demonstrate the severe impact of the pandemic on income, occupation, and workdays, and consequently on livelihood resilience leading up to Amphan. Although effects vary moderately by livelihood category, village, and socio-spatial characteristics, overall rates of income reduction (58%) and occupation loss (77%) between the advent of the lockdown and the aftermath of Amphan are high. Thus, livelihood resilience to the double strike is generally poor. The study analyses the predictors of lost working days to illuminate the influences on livelihood resilience throughout the double strike. We conclude that the pandemic has presented novel challenges to this region, complicating vulnerability to more common cyclonic natural hazards. Finding that the degree of livelihood diversification is low in the sample, we recommend implementing diversification policies and strengthening local networks and community trust to better anticipate and combat the complex, varied impacts of double strike scenarios in future.