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Computer Models Find Cost-Effective Solutions For Species Preservation

Cincinnati -- A University of Cincinnati computer model already used by major corporations to plan efficient distribution networks is now being used by conservation researchers to study the most cost-effective plans for species preservation.

In a paper to be published in Science Friday, March 27, University of Cincinnati researcher Jeffrey Camm and his collaborators will report on the use of optimization techniques to select the right tracts of lands for nature reserves, taking into account both species distributions and land values.

The co-authors are: Amy Ando with Resources for the Future in Washington, D.C.; Stephen Polasky, a resource economist at Oregon State University; and Andrew Solow of the Woods Hole Oceanographic Institution. Camm is head of the quantitative analysis and operations management department in UC's College of Business Administration.

The team's work is an extension of the research done by Andrew Dobson et al. on efficient conservation, which was published in Science last year (Vol. 275, p.550). Dobson reported that conservation could be made more efficient by identifying species "hot spots" where large numbers of endangered species are located. However, Camm's group discovered that species "hot spots" are often real estate hot spots, dramatically increasing the cost of conservation efforts.

So, Ando developed a data base of land values and estimated land values for 2,822 key counties across the United States. Camm factored those values into a computer optimization model, and the results provide a more flexible approach as well as a more economical approach.

"We found that you can get the same number of species using more land and locations at a much cheaper cost than just looking at the species distribution," said Camm. "If you factor in the land values, you might have to buy more locations, but they're cheaper to cover the same species."

That's a significant advantage over previous methods for planning the develop
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Contact: Jeffrey Camm
jeff.camm@uc.edu
513-556-7146
University of Cincinnati
26-Mar-1998


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