Temporal dynamics and policy implications in an innovation arms race
Human-modified environments offer novel resources, but their exploitation can be a source of human-wildlife conflict. Residents of Sydney have reported increasing cases of bin-opening behavior by sulphur-crested cockatoos (Cacatua galerita), with evidence this behavior is socially learned between birds. Households protected their bins, yet cockatoos have learned to defeat these defences. In response, residents increased their defence-level, setting the stage for a behavioral "arms race". Here, we investigate this arms race by combining field observations with agent-based modeling. We systematically document protections in a suburban locality over two years, revealing spatial clustering of protections indicative of social learning among residents. We find that protections have decreased since 2019, and overly-costly protection is dis-preferred. With a controlled assay, we characterize the knowledge of local cockatoos, finding differential proficiency in defeating protections. Surprisingly, we identified several cockatoos that can defeat high-efficacy protections, such as locks. Finally, we simulate interactions between two populations of learning agents representing households and cockatoos. We find that social learning accelerates adaptation in both species, while coordination reduces costs associated with defensive escalation. However, policy interventions can have unintended consequences, accelerating cockatoos skill acquisition and shifting conflict to neighboring areas. Our findings highlight the dynamic nature of human-wildlife conflict and the importance of considering behavioral feedback loops in urban wildlife management.