Publication Release - Assessing relative hazard, risk, and seasonal differences of wildlife-aircraft collisions

Ross, C. D., M. Schank, M. J. Begier, B. F. Blackwell, and T. L. DeVault. 2025. Assessing relative hazard, risk, and seasonal differences of wildlife-aircraft collisions. Wildlife Society Bulletin 49:e1609.

Abstract

Wildlife collisions with aircraft have serious safety and economic implications. Strike risk models are used to assess the probability of an adverse event between wildlife and aircraft, providing information to guide wildlife management at airports. In the strike risk model actively used across the USA, species-specific strike risk is a product of severity and frequency. The severity component of risk, termed relative hazard score (RHS), is a composite variable that indexes the probability of aircraft damage, severe damage, and effect on flight when aircraft are struck by a species, whereas frequency is the number of strikes recorded per species. Our objectives were to update RHS values by incorporating recent strike data available for birds and mammals, update the active strike risk model, and investigate seasonal differences in bird strike risk across species. Using data from the Federal Aviation Administration (FAA)'s National Wildlife Strike Database (NWSD) for the years 2010–2023, we calculated RHS for 132 bird species and 16 mammal species. We found that large-bodied birds, such as the red-tailed hawk (Buteo jamaicensis; risk = 1,225,479), Canada goose (Branta canadensis; risk = 918,744), and turkey vulture (Cathartes aura; risk = 552,026) continue to pose the highest nationwide risk, with species-specific risk ranks fluctuating seasonally. Notably, our analysis highlights one facet of the dynamic nature of wildlife risk at airports, emphasizing the importance of adaptive management strategies that consider seasonal changes in strike risk. We also identify limitations in the current risk assessment model, suggesting future improvements through bias-corrected bird surveys and telemetry data to refine our understanding of species behavior and movement patterns in airport settings. Our findings provide insights for airport wildlife biologists to prioritize management actions, reduce wildlife-related risk, and improve aviation safety.