Phenological Plasticity and Its Temperature-Related Drivers in Common Songbirds Across Europe

Phenological plasticity-the ability of organisms to adjust the timing of life-history events in response to environmental variability-is the primary adaptive mechanism for many organisms to changing seasonality (e.g., earlier spring). By enabling alignment between life-history events and resource availability, it helps to maintain fitness despite changing environmental conditions. Theory predicts that phenological plasticity should vary among populations because of heterogeneity in environmental variability, and among species because of differences in life-history (e.g., migration distance) and phylogenetic constraints. However, comprehensive, multi-species, and cross-population analyses of phenological plasticity remain scarce. Here, we address this gap by using a unique, four-decade dataset from Europe-wide monitoring of common songbirds. Our approach reveals how variation in phenological plasticity is structured according to site temperature properties, both within and across species. We found that long-distance migrants generally exhibit lower plasticity than residents or short-distance migrants, highlighting a fundamental constraint tied to migration strategy. Within species, populations inhabiting sites with predictable temperature profiles showed slightly stronger plastic responses, particularly among single-brooded species and those adapted to warmer breeding conditions. Notably, populations from the fastest-warming regions demonstrated marginally greater plasticity, regardless of other ecological traits, suggesting a global tendency for increased responsiveness in rapidly changing climates. These findings confirm and extend patterns previously observed at smaller scales, offering a more nuanced understanding of how local temperature conditions drive phenological plasticity. By demonstrating that the interplay between local environmental conditions and life-history traits underpins variation in breeding phenological responses, our study refines the current framework for predicting adaptive potential across populations and species under climate change.