“I can migrate, but why should I?”—voluntary non-migration despite creeping environmental risks

Environmental risks increasingly influence human migration, yet the phenomenon of environmental non-migration—remaining in place despite such risks—is under-researched. This study addresses this gap by focusing on voluntary non-migration, defined as the conscious decision to stay despite environmental threats, contrasting with involuntary non-migration (being trapped). The International Organization for Migration (2018) highlights the surprisingly high number of people choosing not to migrate in the face of climate risks. While existing literature touches upon reasons such as place attachment and constraints, a comprehensive understanding of the decision-making process behind voluntary non-migration remains elusive. Therefore, this study investigates the factors influencing this decision, particularly focusing on the role of livelihood resilience and its interaction with societal and environmental conditions. The study employs a case study in southwest coastal Bangladesh, a region acutely vulnerable to environmental hazards, to explore the relationship between livelihood resilience, and voluntary non-migration decisions, both past and future. The study's objectives are to explore how societal and environmental factors drive non-migration decisions, relate those factors to adaptive capacity and resilience and investigate the relationship between non-migration and livelihood resilience and its spatial variability.

Existing research on environmental migration often portrays non-migration as the inverse of migration, neglecting its complexity. While some studies address psychosocial factors like place attachment and constraints, there's limited empirical knowledge on the decision-making process behind non-migration. The literature highlights the role of psychosocial factors like place attachment (Adams, 2016; Hamilton et al., 2016; Rist et al., 2018), the importance of social networks (Haartsen and Stockdale, 2018; Barcus and Shrestha, 2018; Ve et al., 2018), and the use of temporary migration as a strategy to stay long-term (Mata-Coda, 2018). Huntington et al. (2018) emphasize attachment, alertness, and buffering as coping strategies explaining non-migration in Arctic Alaska. However, the existing literature largely focuses on economic drivers, neglecting others and failing to provide a holistic view of non-migration decision-making (Wiegel et al., 2021). This research aims to bridge this gap by incorporating both societal and environmental factors into the analysis of non-migration decisions.

The study proposes an analytical concept represented as a hierarchical structure (Fig. 1). It begins by establishing the context (societal and environmental) in which decisions are made, focusing on how individual and household characteristics, alongside community-level attributes, influence livelihood resilience. This resilience, in turn, shapes the migration decision (to stay or migrate). The model categorizes outcomes into four types: (1) resilient non-migrants who choose to stay; (2) less resilient non-migrants trapped in their locations; (3) resilient migrants who choose to migrate; and (4) less resilient migrants forced to migrate. The concept is operationalized using a case study in southwest coastal Bangladesh, examining five villages affected by Cyclone Aila in 2009. Data collection involved in-depth interviews, group discussions, and a household survey (Table 2, Fig. 2) focusing on socio-economic characteristics, housing conditions, place attachment, social networks, environmental factors (climate, water, soil, biodiversity), and past and future migration motivations. Livelihood resilience is measured using a Livelihood Resilience Index (LRI), calculated using a multi-factor indexing method (Eqs. 1-3) which incorporates societal and environmental factors (Table 1). The LRI scores are categorized into less resilient, moderate, and resilient groups. The study then analyzes the relationships between LRI scores, past migration decisions (post-Cyclone Aila), and future migration intentions.

The study found that approximately 40% of respondents reported at least one family member migrating after Cyclone Aila, primarily for alternative income sources. Migration rates varied across villages depending on exposure to flooding (Fig. 3). Qualitative data revealed that place attachment, food security, social networks, fear of uncertainty in new locations, and access to essential resources (such as education) were key social factors influencing the decision to stay. Environmental factors such as access to fresh food, clean air, and adaptability to challenges like increasing water salinity also influenced non-migration decisions. The LRI calculation revealed a distribution of households: resilient (18%), moderate (37%), and less resilient (51%). Analysis showed a correlation between LRI and the voluntary nature of migration decisions, but resilience alone did not predict migration or non-migration decisions. Despite being less resilient, many households expressed a desire to stay in their villages (Table 3, Fig. 4, Fig. 5, Fig. 6). This highlights the significant role of aspirations in shaping migration choices alongside resilience. Seasonal and temporary migration emerged as long-term strategies for maintaining residence in their home communities.

The findings highlight the multifaceted nature of environmental non-migration decisions, emphasizing the need for a holistic approach that goes beyond simple push-pull models. The study's analytical concept effectively integrates livelihood resilience, aspirations, and capabilities to explain non-migration. The case study demonstrates the importance of considering both societal and environmental dimensions in understanding the decisions of people facing environmental risks. The LRI proved valuable in assessing the voluntary nature of migration choices, while also demonstrating that resilience is not the sole determinant. Aspirations, particularly the desire to remain in one’s community, play a significant role. The study acknowledges the influence of the environmental event’s characteristics (fast- or slow-onset) on migration decisions. A fast-onset event can trigger migration regardless of resilience, while slow-onset changes may allow more time for adaptation and influence the decision to stay.

This paper presents a novel analytical concept for understanding environmental non-migration, integrating livelihood resilience, aspirations, and capabilities. The findings emphasize the complexity of non-migration decisions, revealing that resilience plays a significant but not deterministic role, alongside aspirations. Future research should investigate further the interactions between these factors and the influence of environmental event characteristics (fast- versus slow-onset) to refine the model and enhance its predictive power. The model also needs longer-term, temporal observations to gain a better understanding of the dynamic relationship between resilience and migration decisions over time.

The study's geographical scope is limited to southwest coastal Bangladesh. The findings may not be generalizable to other contexts with different environmental characteristics, social structures, or economic conditions. The reliance on self-reported data for migration intentions might introduce bias. Further research should validate the findings using longitudinal studies and broader geographical contexts.