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New model explains why costly insect 'outbreaks' hard to predict

Many insect species notably the gypsy moth, one of North America's most devastating forest pests produce periodic population surges, known as outbreaks, only to crash down to low levels. These outbreaks can devastate huge areas of forest, but they occur at long, irregular intervals and so are hard to predict. In the 15 July 2004 issue of Nature, three researchers present a model that appears to untangle the factors that trigger such outbreaks, and that helps to explain why outbreaks are so unpredictable.

By combining elements from two prevailing but flawed insect-outbreak theories, and supplementing the combined theory with additional data, the researchers produced a mathematical model that reproduces the unpredictable outbreaks of gypsy moth populations more accurately than any model yet.

"We used gypsy moths as our example, but this theory should apply to any forest insect that has outbreaks," said Greg Dwyer, Ph.D., assistant professor of ecology and evolution at the University of Chicago and lead author of the study. "The model is quite general, and there are many insects beyond gypsy moths for which this applies."

Approximately 80 species of butterflies and moths undergo outbreaks, as do some small mammals, including voles and lemmings.

Ecologists who study insect outbreaks previously fell into two camps. One camp has focused on host-pathogen or host-parasite models, which presume that outbreaks primarily depend upon the presence or absence of disease among insect populations. These models can closely approximate the average length of time between outbreaks, but they fail to explain the relatively irregular timing with which outbreaks tend to occur.

The other camp has focused on the role of "generalist" predators, such as spiders and birds. When the density of these generalists declines the insects they feed on quickly explode in numbers. But recent studies have found that generalists are
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Contact: John Easton
jeaston@uchospitals.edu
773-702-6241
University of Chicago Medical Center
14-Jul-2004


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