Using maths to plan roads for wildlife

Saving koalas from cars

DPt92__Page_13_Image_0003We all have to negotiate roads in our daily lives; we cross roads to get to the shops, our kids cross roads as they walk or ride to school, and most of us have a road outside where we live. Although they are part of everyday life they pose significant risks to our safety. Vast amounts of money are invested every year making roads as safe as possible through the considered placement of busy roads and the installation of safety infrastructure, such as barriers and pedestrian crossings. The issue is exactly the same for our wildlife moving around the landscape. Yet we currently lack comprehensive plans to make our road networks as safe as possible for wildlife. EDG researchers are addressing this gap using the power of maths to develop new planning tools for environmentally-sensitive road planning.

Roads are pervasive and can invade some of the most remote places on Earth. Some consider them one of the greatest emerging threats to biodiversity. As such, roads are having significant impacts on wildlife worldwide. The most obvious threat is when individual animals are hit and killed by motor vehicles. A more subtle effect is interference that roads cause to animal migration or dispersal. But what can we do?

There are essentially two ways in which these impacts can be reduced (apart from not building roads in the first place). The first is by changing where we put roads. The second is by constructing fences and overpasses. Because conservation funds are limited, choosing what to do is hard because there are so many options. Luckily we can turn to decision science to help. In two recent studies we have developed insights into principles for road placement and tools for prioritising mitigation structures and their locations. In both cases we used koalas for the case study.

New roads or improved roads?

In the first study we were interested in the problem of designing whole road networks to accommodate increases in road traffic that would minimise the impact on wildlife. In doing so we considered two potential road design principles: (1) increases in vehicle numbers are accommodated through the construction of new roads, and (2) increases in vehicle numbers are accommodated through upgrades to existing roads (Rhodes et al, 2014).

We applied a mathematical model that is explicit about traffic volumes and road densities to a koala population around Port Stephens on the NSW north coast. We found that in almost all cases the effect of building new roads was more detrimental to wildlife populations than upgrading existing roads. This occurred because the additional impact on animals having to cross more roads was generally much higher than the additional impact of increases in traffic volume. Our modelling also suggests that building of new roads was only preferable when the existing road network (the starting point) was of very low density, but with very high traffic volumes. This might apply, for example, for a busy highway passing through a rural area with few other roads.

Figure 1. Map of study area near Port Stephens used in the analysis of whether new roads or upgraded roads had more impact on koalas. The map shows the the estimated distribution of koala habitat, and the estimated average daily traffic volume (axle-pairs day) on major roads. The biggest roads in the area carry over 20,000 vehicles per day. (From Rhodes et al, 2014)

Figure 1. Map of study area near Port Stephens used in the analysis of whether new roads or upgraded
roads had more impact on koalas. The map shows the the estimated distribution of koala habitat, and the
estimated average daily traffic volume (axle-pairs day) on major roads. The biggest roads in the area carry
over 20,000 vehicles per day. (From Rhodes et al, 2014)

Although our modelling looked at the impact of roads on koalas, the conclusions appeared generally robust enough that they are likely to apply to many other species as well. If so, then it has important implications for how we design road networks in general. Indeed, it’s possible to conceptualise road planning in way that is analogous to the land sharing / sparing debate in agricultural landscapes. At one end of the spectrum are planning strategies that aim for many roads spread across the landscape, but with each road having low traffic volumes; a road sharing approach with few road-free areas. At the other end of the spectrum are planning strategies that aim for few roads spread across the landscape, but with each road having high traffic volumes; a road sparing approach with many road-free areas. In designing road networks there are clearly a range of trade-offs that need to be considered such as cost, traffic flow, and accessibility and a range of options between the road sharing/ sparing extremes. However, our work suggests that, at least from a wildlife point of view, a road sharing-like approach is likely to be a poor option.

Impact mitigation

In the second study, we developed a new framework for prioritising among different road mitigation options (fences and crossings) that can be applied to road networks to minimise the impact on wildlife. More specifically, our framework identifies the positioning of mitigation measures, such as fences and animal passages, in such a way that the abundance of a species is maximized while taking costs into account (Polak et al, 2014). This research represents the first attempt to use decision science to identify road mitigation actions for biodiversity conservation.

To test our framework we used information about a koala population located on the Koala Coast (in south east Queensland, see the box ‘The ‘Coast’ is clear’). These koalas are greatly affected by roads, with vehicle impacts representing the second highest cause of mortality for this population. We developed a population model for four patches of habitat separated by four roads with different lengths, traffic volumes and mitigation measures. We considered three possible mitigation actions for each of the four road segments: do nothing; erect fences without wildlife crossings; and erect fences with wildlife crossings. For each mitigation action combination we used the population model to predict population sizes in 100 years.

We discovered that there is a strong need for mitigation as the already declining koala population will be reduced to near extinction without it. Sadly, for this case study, there was no ‘easy win’ solution where we could achieve an adequate level of conservation for a low monetary cost. We found an almost linear relationship between the benefit to koalas and cost that indicates there are no cheap solutions for this system. Further, if we want to maintain the local koala population we need to invest a substantial amount of resources; we estimate that an investment of 1.7 million dollars in road mitigation is essential, and this applies for an area with only 8 km of roads!

Our approach appears to be very flexible and can be adapted to other species, systems and even the employment of other mitigation actions. The population model can be adjusted to match the needs of different species, indeed multiple species. This new framework will allow decision-makers to clearly measure the trade-off between potential biodiversity benefits and economic cost in road mitigation measures. It’s our hope that this approach will be adopted by decision-makers and applied to locations in need of mitigation in order to protect species threatened by roads all over the world, rather than the ad-hoc approaches commonly used now.

The road ahead

The impact of roads on wildlife populations arises from a range of complex spatial processes involving interactions between movement behaviours and the spatial pattern of habitat and roads. These studies make important contributions to understanding how best to plan future road infrastructure if mitigating the impacts on wildlife is part of the planner’s remit. One of the key challenges now is developing ways to effectively integrate the results of studies such as these into strategic planning processes for infrastructure and wildlife management.


The ‘Coast’ is clear

The Koala Coast is located 20 km south-east of Brisbane, and covers an area of around 375 km². It contains one of the most significant koala populations in Australia, but this is a population at risk. The region is experiencing rapid human population growth with associated urbanisation and the loss of habitat. This has also resulted in elevated rates of mortality due to vehicle collisions and domestic dog attacks. There has also been an increased prevalence of disease, which might be due to increased stress levels associated with habitat loss. What it adds up to is a 64% decline in this koala population over the past 10 years, and the very real possibility that Australia’s Koala Coast might one day soon be a place where koalas are no more.

More info: Decision Point #50  (Images by Liana Joseph)


The wandering male

The Port Stephens study (Rhodes et al, 2014) showed that male koalas were more susceptible to road traffic mortality than females and the range of conditions under which building new roads was the better strategy was even more limited for males than females. The reason for this is that males generally have larger home ranges and move greater distances than females, particularly during the breeding season, with the result that males tend to cross roads more frequently than females. This is consistent with empirical evidence on differences between the sexes in vehicle collision mortality rates in koalas. The higher movement rates of male koalas also makes them more susceptible to the effect of increased road densities versus increased traffic volumes on existing roads. The general implications of this are that, for very mobile species, upgrading existing roads is even more likely to be the better strategy than it is for less mobile species.


More info: Tal Polak t.polak@uq.edu.au and Jonathan Rhodes j.rhodes@uq.edu.au

References

Polak T, JR Rhodes, D Jones & HP Possingham (2014). Optimal planning for mitigating the impacts of roads on wildlife. Journal of Applied Ecology 51:726-734.

Rhodes JR, D Lunney, J Callaghan & CA McAlpine (2014). A few large roads or many small ones? How to accommodate growth in vehicle numbers to minimise impacts on wildlife. Plos One 9 e91093. doi:10.1371/journal.pone.0091093

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