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New Map Predicts Where Wolves Will Attack

Date:
February 27, 2004
Source:
Wildlife Conservation Society
Summary:
Scientists from the New York-based Wildlife Conservation Society and other groups have developed a high-tech map that predicts where wolves will prey on livestock, which in turn may allow wildlife managers and ranchers to prevent attacks in the first place.
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NEW YORK (FEB. 25, 2004) – Scientists from the New York-based Wildlife Conservation Society and other groups have developed a high-tech map that predicts where wolves will prey on livestock, which in turn may allow wildlife managers and ranchers to prevent attacks in the first place. The groups, which also included authors from the Wisconsin Dept. of Natural Resources and University of Wisconsin in Madison, published their results in the latest issue of the journal Conservation Biology.

Using geographic information system (GIS) mapping, the scientists looked at road density, farm size, availability of deer and other factors to develop statewide maps for Wisconsin and Minnesota. Despite dramatic differences in the two states' wolf populations, hunting policies, and farm sizes, the maps revealed several similarities among the sites where wolves had preyed on cattle in the past.

Each town in the two states was assigned a color-code ranging from red (highest risk) to blue (lowest risk). Low risk townships included those with lots of cropland, wetlands and open water. Overall, just 0.3 percent of Wisconsin's towns were classified as highest risk and none occurred in Minnesota. The two higher risk classes of townships (red and orange) were clustered in two areas that had not previously been identified as problematic.

The map revealed that southwest Wisconsin faced moderate to high risk, an area where breeding packs of wolves have not yet recolonized. The map also revealed that highest risk townships were clustered along the edge of the wolf population--areas with the lowest habitat suitability for wolves and where newly formed wolf packs encounter landowners with little, recent experience of conflict with wolves. Among farms, the authors found that those with large land holdings and large herds were more likely to suffer losses from wolves. In Minnesota, risk was particularly high for farms sharing the land with dense deer populations.

"We are optimistic that these maps will be used to reduce conflict between wolves and people," said Wildlife Conservation Society scientist Adrian Treves, lead author of the study. "By knowing in advance the kind of areas where wolves will prey on livestock, non lethal controls can be employed so that wolves won't be needlessly killed. Managers may be able to focus their outreach and interventions where it is most needed."

Techniques such as guard animals, improved fencing, and new scare devices that use random sounds and light can deter wolves from preying on livestock. Last year, Treves and other colleagues published a study showing how "audio scarecrows" that played amplified sounds of everything from helicopters to gunfire drove bears and wolves away from fenced properties.

Treves also said that the mapping technique could be adapted to other areas where human/wildlife conflicts occur, provided enough geographic data could be gathered.

"Whether it's tigers in India or black bears in New Jersey, this mapping technique could greatly reduce needless killing of wildlife, by preventing human/wildlife conflicts in the first place," he said.


Story Source:

Materials provided by Wildlife Conservation Society. Note: Content may be edited for style and length.


Cite This Page:

Wildlife Conservation Society. "New Map Predicts Where Wolves Will Attack." ScienceDaily. ScienceDaily, 27 February 2004. <www.sciencedaily.com/releases/2004/02/040227072718.htm>.
Wildlife Conservation Society. (2004, February 27). New Map Predicts Where Wolves Will Attack. ScienceDaily. Retrieved March 27, 2024 from www.sciencedaily.com/releases/2004/02/040227072718.htm
Wildlife Conservation Society. "New Map Predicts Where Wolves Will Attack." ScienceDaily. www.sciencedaily.com/releases/2004/02/040227072718.htm (accessed March 27, 2024).

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