Research, Connect, Protect



Threatening processes

Consistent patterns of vehicle collision risk for six mammal species

Visintin, C, van der Ree, R & McCarthy, MA 2017, Journal of Environmental Management, vol. 201, no. 1, pp. 397-406.

The authors of this study developed a quantitative risk model framework for evaluating the extent to which the variables of species occurrence, road speed and traffic volume influence the risk of wildlife-vehicle collision for a section of road. The framework was applied to examine the risk of wildlife-vehicle collisions on Victorian roads for six species including the koala.

  The occurrence of six terrestrial mammal species throughout the study region was predicted by identifying correlations between several ecological indicator variables and animal observation records and then extrapolating across the region to create a map of species presence likelihood. Using detailed wildlife-vehicle collision records, the influence of road speed and traffic volume upon risk of collision for each species was quantified. As expected, collision risk for all species increased with the likelihood of species occurrence. Compared to most other species, however, the koala had a relatively high risk of collision at a low likelihood of occurrence. Similarly, collision risk for the koala was lower than for other species when the likelihood of occurrence was high. This may be due to the arboreal nature of the species, as where suitable habitat exists koalas may be less likely to come to the ground and interact with roads. Conversely, although the likelihood of a koala occurring in an area without suitable habitat is low, a koala that did travel through such an area may be at an increased risk of wildlife-vehicle collision. For most species, collision risk increased greatly with increased traffic speed. This relationship could also be expected, as at higher speeds motorists have less time to take measures to avoid a collision with an animal once that animal has been sighted. For all species, a quadratic relationship was observed between traffic volume and risk of collision, with a peak in collision risk at moderate traffic volumes followed by a gradual decline in risk. This trend may indicate a threshold effect whereby high levels of traffic volume results in mortalities that reduce local species abundance. The peak in risk, therefore, occurs at moderate levels of traffic volume at which collisions are frequent but do not cause local population declines. A few road sections were identified as presenting the highest risk of wildlife-vehicle collision of all roads and for all six species.

  Both wildlife-vehicle collisions and measures to prevent them are costly to governments. It is, therefore, important for decision-makers to understand the factors that contribute to collision risk to identify where mitigation is likely to be the most beneficial. The model presented in this study can be used to identify areas of greatest collision risk for species individually or cumulatively across entire management areas and consequently to prioritise sites for mitigation. Questions that remain about trends or anomalies observed in the model’s output can also direct efforts for future data collection and analysis.


Summarised by Joanna Horsfall


Disclaimer: The summary of this report is provided for reference purposes only and does not represent the findings or opinions contained in the original report. Although every effort has been made to bring forward the main elements of the report, this review is no substitute for the full the report itself. Should you have any concerns or perceive any errors please contact us and we shall endeavour to rectify and improve the review.