Behavioral plasticity shapes population aging patterns in a long-lived avian scavenger.

Studying the mechanisms shaping age-related changes in behavior ("behavioral aging") is important for understanding population dynamics in our changing world. Yet, studies that capture within-individual behavioral changes in wild populations of long-lived animals are still scarce. Here, we used a 15-y GPS-tracking dataset of a social obligate scavenger, the griffon vulture (Gyps fulvus), to investigate age-related changes in movement and social behaviors, and disentangle the role of behavioral plasticity and selective disappearance in shaping such patterns. We tracked 142 individuals for up to 12 y and found a nonlinear increase in site fidelity with age: a sharp increase in site fidelity before sexual maturity (<5 y old), stabilization during adulthood (6 to 15 y), and a further increase at old age (>15 y). This pattern resulted from individuals changing behavior throughout their life (behavioral plasticity) and not from selective disappearance. Mature vultures increased the predictability of their movement routines and spent more nights at the most popular roosting sites compared to younger individuals. Thus, adults likely have a competitive advantage over younger conspecifics. These changes in site fidelity and movement routines were mirrored in changes to social behavior. Older individuals interacted less with their associates (decreasing average strength with age), particularly during the breeding season. Our results reveal a variety of behavioral aging patterns in long-lived species and underscore the importance of behavioral plasticity in shaping such patterns. Comprehensive longitudinal studies are imperative for understanding how plasticity and selection shape the persistence of wild animal populations facing human-induced environmental changes.

A wrap-around movement path randomization method to distinguish social and spatial drivers of animal interactions.

Studying the spatial-social interface requires tools that distinguish between social and spatial drivers of interactions. Testing hypotheses about the factors determining animal interactions often involves comparing observed interactions with reference or 'null' models. One approach to accounting for spatial drivers of social interactions in reference models is randomizing animal movement paths to decouple spatial and social phenotypes while maintaining environmental effects on movements. Here, we update a reference model that detects social attraction above the effect of spatial constraints. We explore the use of our 'wrap-around' method and compare its performance to the previous approach using agent-based simulations. The wrap-around method provides reference models that are more similar to the original tracking data, while still distinguishing between social and spatial drivers. Furthermore, the wrap-around approach results in fewer false-positives than its predecessor, especially when animals do not return to one place each night but change movement foci, either locally or directionally. Finally, we show that interactions among GPS-tracked griffon vultures (Gyps fulvus) emerge from social attraction rather than from spatial constraints on their movements. We conclude by highlighting the biological situations in which the updated method might be most suitable for testing hypotheses about the underlying causes of social interactions. This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.