The Role of Social Learning in Buffering or Amplifying Climate Stress in Long-Distance Migratory Species

Abstract

The current trend in climate change is the changing environmental conditions that migratory species
face over long distances, resulting in increased physiological stress, diversion of migration routes, and
decreased survival rates. Although the individual adaptive responses have been well researched, little
is known about the process of social learning, including the transfer of information by groups during
interaction, and how these moderates or exacerbates stress induced by climate change. The research
question addressed in this study is whether social learning serves as a buffer, increasing resilience, or
an amplifier, positively reinforcing maladaptive behavior in the context of climate stress. A
comparative study of five migratory species, three avian and two marine, was used to identify a set of
three GPS tracking data, climate exposure indices, and behavioral network metrics across 12 migration
seasons (2012-2023). Stress responses were measured as deviations in migration timing and route
flexibility, and the probability of survival and social learning was quantified using indices of group
cohesion and leader-follower relationships. Findings show that moderate amounts of social learning
effectively buffered climate stress, reducing route deviation errors by 27% and increasing migration
success rates by 18% during high-temperature anomalies. Nevertheless, the intensification of stress
effects by highly centralized social structures led to coordinated route failures and a 22% higher
mortality rate during extreme climate events. Flexible species had better adaptive ability than species
with strong information hierarchies. The results indicate that social learning has a dual impact on
climate adaptation, both as a resilience factor and a risk factor. Considering social dynamics in
conservation planning is thus essential for forecasting the outcomes of migration and for developing
efficient, climate-adaptive management measures.