Two bears photographed on train tracks. New research by UAlberta biologists is exploring ways to use animal learning to reduce wildlife and train collisions. Photo credit: Niels de Nijs
The issue of wildlife being struck and killed by trains is a perennial problem all over the world-and it is only getting worse, says Colleen Cassady St. Clair, ecologist and professor in the University of Alberta's Department of Biological Sciences.
"There are more trains, and these trains are traveling faster than ever before," explained St. Clair. "The possibility of collisions between wildlife and trains is increasing."
In Banff, where provincially-threatened grizzly bears are struck by trains, wildlife managers hoped research could determine why bears use the tracks and prevent it. But over the last eight years, St. Clair's research group has determined that many factors attract bears, from spilled grain to concentrated deer and elk populations, to berries that grow near the tracks, to the convenient corridor that tracks provide through the landscape. Through this research, it became obvious that keeping bears off the tracks altogether would be extremely difficult.
For St. Clair, another thing has become clear. It isn't possible to solve this problem without working with the bears themselves.
"The issue isn't keeping wildlife away from the tracks-it is keeping animals from being struck by trains," said St. Clair. "So we wondered, what if we shifted focus? What if we tried to teach bears to avoid the trains themselves, giving them enough time to get safely out of the way?"
Getting bears out of there
With this in mind, interdisciplinary PhD student Jonathan Backs, co-supervised by St. Clair and John Nychka in the Faculty of Engineering, developed a warning system to alert bears when trains are approaching, giving them more time to move out of the way. The device uses a two-part system to detect an approaching train and deploy a warning consisting of a ringing bell and a flashing light-similar to stimuli that are used at railway crossings for people. The devices were installed in four areas where wildlife-train collisions occurred in the past to test the ability of the device to change animal behaviour. Analyses of these data are not yet complete, but look promising.
"Even if the system was adopted, it couldn't solve the problem for every bear," added St. Clair. "Warning systems would only be installed at high-risk locations and it would take time for resident animals to learn to associate them with approaching trains. But, our hope is that this type of solution would be most beneficial to the animals that live in that area."
Though the approach of focusing on animal learning is relatively new, it is growing in popularity and interest among ecologists, who are using similar learning by association to teach animals to avoid people or particular sources of food.
"We might try more actively to teach animals to avoid areas of human-development and related effects that are damaging to them, while accepting that we share space with other species," said St. Clair. "Our human activities do get in their way. I think animal learning-inviting them to participate in their own conservation-could be a much bigger part of the solution for these problems."
The paper, "Animal learning may contribute to both problems and solutions for wildlife-train collisions," was published in Philosophical transactions of the Royal Society of London (doi: 10.1098/rstb.2018.0050).