Optimal planning for mitigating the impacts of roads on wildlife

Abstract

Summary Roads have a significant impact on wildlife world‐wide. Two of the ways to mitigate the impact of roads are to improve connectivity and reduce mortality through fences and wildlife crossings. However, these are expensive actions that will have different effects in different places. Thus, deciding where and how to act in order to achieve the greatest return on investment is crucial. Currently, there are no quantitative approaches to prioritize different road mitigation options. Here, we use a decision science framework to determine the most cost‐effective combination of actions to mitigate the effects of roads on wildlife under budget constraints. We illustrate our approach using a case study of a threatened koala Phascolarctos cinereus population in south‐east Queensland. We applied a spatially explicit population model to explore the benefits of three kinds of mitigation actions: no action at all and fences with or without crossings, on different road segments. We explored the trade‐off between expected koala population size, relative to the best outcome, and budget. There is a strong demand for mitigation as the already declining population was reduced even further when no mitigation was employed, while applying the most cost‐effective combination of mitigation actions minimized that decline. Additionally, uncertainty in species attributes (speed of crossing a road and population growth rate) affected population viability but not the decision about which suite of actions (mitigation measures) to take – so our advice on the best action is robust to uncertainty even if the outcome is not. Most importantly, the trade‐off curves between investment and population size are almost linear in this case study. Hence, there is no cheap solution and any reduction in the budget will result in a substantial reduction in expected population size. Synthesis and applications. This is the first time that the problem of mitigating the effects of roads on wildlife was formulated mathematically and systematically using decision science. Our approach is adaptable to a diversity of species and systems affected by road mortality allowing flexibility for a range of mitigation actions and biological outcomes. Our method will allow managers and decision‐makers to increase the efficiency of mitigation actions.