Gypsy moth management made more efficient, cost...( A computer model that provides land ...)

A computer model that provides land managers with a more efficient and cost-effective approach for controlling gypsy moths and other invasive pests has been created by biologists at Penn State University and the University of Cambridge in the United Kingdom. Gypsy moths, which were introduced to North America in the late 1860s, are responsible for the defoliation of over a million acres of forest land each year and the loss of tens of millions of dollars. In a paper to be published later this month (April 2008) in the journal Ecological Applications, the team's results indicate that the best strategies for managing the destructive pests include eradicating medium-density infestations and reducing high-density infestations, rather than reducing spreading from the main infestation.

"Our model is state dependent, which means that it recommends different management strategies depending on the situation," said Katriona Shea, Penn State associate professor of biology and the team's leader. "Most managers currently use the same strategy in all situations, but our model suggests that by tailoring their approach to a particular situation, managers can be more effective in slowing the spread of invasive species."

Saving time and money is of the utmost importance with gypsy moths, which have by now spread throughout the northeastern United States and into the Midwest. "Some people argue that it's just a matter of time before the moths spread across the entire United States, so why bother trying to slow them down"" said Shea. "But we see it differently. We hope that by slowing their spread we can buy some time to find a better way to deal with them."

Although the model has little to offer those states that already have succumbed to infestation, it does have the potential to slow or halt the moths' spread into new areas. States that stand to benefit the most include North Carolina, Virginia, West Virginia, Ohio, Indiana, Illinois, a
'/>"/>