Using species relevant timeframes to partition, prioritise and monitor vehicle-strike blackspots: a case study using the Koala <i>Phascolarctos cinereus</i> in Lismore, New South Wales

Vehicle-strike accounts for the death of millions of animals annually and can cause damage to property and humans. Mitigating the potential for vehicle-strike is expensive. Therefore, objectively identifying and prioritising areas for mitigation works is important. We partitioned roads in Lismore, New South Wales into 1-km segments and overlaid this with generationally-partitioned vehicle-strike records for the threatened Koala Phascolarctos cinereus. Extending generational timeframes to accommodate under-reporting in areas of low observer density, a K-distance plot was used to identify road segments with the greatest vehicle-strike potential, whereafter we used the 95% confidence interval derived from averaging the Euclidean distances between the five nearest records to identify vehicle-strike clusters. Output was standardised into the number of koalas struck by vehicles per kilometre per generation, which we then ranked to identify road segments where the potential for ongoing vehicle-strike was greatest. We conclude that techniques of cluster analyses informed by recognised conservation criteria allow roads to be ranked by severity of impact and can therefore guide management actions that maximise financial and/or ecological return, as well as providing important baseline metrics for monitoring purposes.