Abstract
How do animals successfully invade urban environments? Sex-biased dispersal and learning arguably influence movement ecology, but their joint influence remains unexplored empirically, which might vary by space and time. We assayed reinforcement learning in wild-caught, temporarily-captive core-, middle- or edge-range inhabitants of great-tailed grackles—a bird species undergoing urban-tracking rapid range expansion, led by dispersing males. Across populations, Bayesian models revealed: both sexes initially learn at similar pace, but, when reward contingencies reverse, males—versus females—’relearn’ faster via pronounced reward-payoff sensitivity, a risk-sensitive learning strategy. Confirming this mechanism, agent-based forward simulations of reinforcement learning replicate our sex-difference data. Separate evolutionary modelling revealed risk-sensitive learning is favoured by natural selection in stable but stochastic settings—characteristics typical of urban environments. Risk-sensitive learning, then, is a winning strategy for urban-invasion leaders, implying life history (sex-biased dispersal) and cognition (learning) interactively shape invasion success in the unpredictable Anthropocene. Our study sets the scene for future comparative research.
Competing Interest Statement
The authors have declared no competing interest.
