The question of coexistence also depends on whether the people in a given municipality rely on their own agricultural products or earn their living in tourism or away from home. “Tourism-reliant municipalities even stand to benefit from the bears, since wildlife tourism is booming in the Abruzzo National Park.” Money is also being invested to make the local waste disposal, fruit crops and livestock bear-proof. The situation is different in rural municipalities, where preventive protection measures often lag behind. “If you own only ten sheep and a bear kills one of them, you feel your livelihood is threatened,” Mayer says.
A global problem
Mayer believes that the “large carnivore problem” is the same everywhere. She says it’s mostly an urban-rural conflict charged with emotion, and with a lot of symbolism projected onto the animals. “But it’s more about interpersonal issues and control; the wild animals only serve a symbolic function.”
The question, Mayer adds, is what measures are needed on the ground so that bear-human coexistence can succeed. One important factor that emerged from interviews with locals is that they want government compensation payments to be disbursed more quickly and with less red tape – or indeed for the government to actually make such payments in the first place. “Some people are angry because they’ve never been compensated for any damage caused by individual bears, despite promises to the contrary.”
A practical tool
The model and generated coexistence maps constitute a practical tool, for example for examining how bear-human coexistence in the landscape changes over time. It can also be used to test whether measures are effective at the local level.
“If the model produces a map that shows areas of low coexistence despite measures like fences to protect beehives from bears, you can infer how effective a measure is – and whether other measures might be better for promoting coexistence in that location,” Mayer says. “That’s something we can assess very well – or even predict – with the model.”
And it doesn’t take a powerful mainframe computer to generate these maps either: the current maps were made on Mayer’s laptop.
Network with many nodes
Mayer used a Bayesian network to approach this multi-layered problem. Such networks operate with conditional probabilities and can take into account and connect a variety of different factors. The model approach considers factors that both represent the human perspective and reflect the needs of the bears. These variables can be updated with explicit local information. To obtain this information, she worked with experts from nature conservation, tourism and research and conducted interviews with local people.
The bears’ perspective is represented by factors such as suitable habitats, migration corridors and whether attractive human-made food resources are present. The latter include waste disposal facilities, orchards and livestock that aren’t bear-proof. This affects the probability of bears appearing in and around settlements.