From parameter uncertainty to process simulation: rethinking collision risk models

Collision Risk Models (CRMs) are central to environmental assessment for offshore wind but operate under data limitations and uncertain ecological assumptions. While stochastic extensions incorporate parameter uncertainty, the basic approach remains structurally unchanged, treating collision risk as a function of uncertain inputs rather than as the outcome of underlying behavioural and spatial processes. This paper argues for a shift from parameter estimation to simulation. Agent-based models (ABMs) provide a necessary extension to CRMs by simulating bird movement, behavioural responses, and interactions with turbine arrays. In this framework, collision risk emerges from generative processes rather than being imposed through fixed parameters such as avoidance rates. ABMs complement deterministic and stochastic CRMs, support scenario testing, generate synthetic data under data scarcity, and provide mechanistic insight into collision risk. ABMs have not been integrated into regulatory collision risk assessment but doing so would enhance the biological realism of collision modelling, offering a more robust basis for decision-making in offshore wind consenting.