Guidance for management of free-roaming community cats: a bioeconomic analysis

This study used computer simulation modeling to estimate and compare costs of different free-roaming cat (FRC) management options (lethal and non-lethal removal, trap-neuter-return, combinations of these options and no action) and their ability to reduce FRC population abundance in open demographic settings. The findings provide a resource for selecting management approaches that are well matched for specific communities, goals and timelines, and they represent use of best available science to address FRC issues.

Multiple FRC management approaches were simulated at varying intensities using a stochastic individual-based model in the software package Vortex. Itemized costs were obtained from published literature and expert feedback. Metrics generated to evaluate and compare management scenarios included final population size, total cost and a cost efficiency index, which was the ratio between total cost and population size reduction.

Simulations suggested that cost-effective reduction of FRC numbers required sufficient management intensity, regardless of management approach, and greatly improved when cat abandonment was minimized. Removal yielded the fastest initial reduction in cat abundance, but trap-neuter-return was a viable and potentially more cost-effective approach if performed at higher intensities over a sufficient duration. Of five management scenarios that reduced the final population size by approximately 45%, the three scenarios that relied exclusively on removal were considerably more expensive than the two scenarios that relied exclusively or primarily on sterilization.

FRCs present a challenge in many municipalities, and stakeholders representing different perspectives may promote varying and sometimes incompatible population management policies and strategies. Although scientific research is often used to identify FRC impacts, its use to identify viable, cost-effective management solutions has been inadequate. The data provided by simulating different interventions, combined with community-specific goals, priorities and ethics, provide a framework for better-informed FRC policy and management outcomes.