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  Risk-sensitive learning is a winning strategy for leading an urban invasion

Breen, A. J., & Deffner, D. (2024). Risk-sensitive learning is a winning strategy for leading an urban invasion. eLife, 12: RP89315. doi:10.7554/eLife.89315.3.

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Breen_Risk-sensitive_eLife_2024.pdf (Publisher version), 5MB
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 Creators:
Breen, Alexis J.1, Author                 
Deffner, Dominik , Author
Affiliations:
1Department of Human Behavior Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_2173689              

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Free keywords: cognition; dispersal; ecology; evolutionary biology; great-tailed grackles; rapid range expansion; reinforcement learning; sex differences
 Abstract: In the unpredictable Anthropocene, a particularly pressing open question is how certain species invade urban environments. Sex-biased dispersal and learning arguably influence movement ecology, but their joint influence remains unexplored empirically, and might vary by space and time. We assayed reinforcement learning in wild-caught, temporarily captive core-, middle-, or edge-range great-tailed grackles—a bird species undergoing urban-tracking rapid range expansion, led by dispersing males. We show, across populations, both sexes initially perform similarly when learning stimulus-reward pairings, but, when reward contingencies reverse, male—versus female—grackles finish ‘relearning’ faster, making fewer choice-option switches. How do male grackles do this? Bayesian cognitive modelling revealed male grackles’ choice behaviour is governed more strongly by the ‘weight’ of relative differences in recent foraging payoffs—i.e., they show more pronounced risk-sensitive learning. Confirming this mechanism, agent-based forward simulations of reinforcement learning—where we simulate ‘birds’ based on empirical estimates of our grackles’ reinforcement learning—replicate our sex-difference behavioural data. Finally, evolutionary modelling revealed natural selection should favour risk-sensitive learning in hypothesised urban-like environments: stable but stochastic settings. Together, these results imply risk-sensitive learning is a winning strategy for urban-invasion leaders, underscoring the potential for life history and cognition to shape invasion success in human-modified environments.

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Language(s): eng - English
 Dates: 2024-04-02
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.7554/eLife.89315.3
 Degree: -

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Title: eLife
Source Genre: Journal
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Publ. Info: Cambridge : eLife Sciences Publications
Pages: - Volume / Issue: 12 Sequence Number: RP89315 Start / End Page: - Identifier: ISSN: 2050-084X