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Early warning signs of population collapse
Date:4/10/2013

CAMBRIDGE, MA -- Many factors including climate change, overfishing or loss of food supply can push a wild animal population to the brink of collapse. Ecologists have long sought ways to measure the risk of such a collapse, which could help wildlife and fishery managers take steps to protect endangered populations.

Last year, MIT physicists demonstrated that they could measure a population's risk of collapse by monitoring how fast it recovers from small disturbances, such as a food shortage or overcrowding. However, this strategy would likely require many years of data collection by which time it could be too late to save the population.

In a paper appearing in the April 10 online edition of Nature, the same research team describes a new way to predict the risk of collapse, based on variations in population density in neighboring regions. Such information is easier to obtain than data on population fluctuations over time, making it potentially more useful, according to the researchers.

"Spatial data are more accessible," says Lei Dai, an MIT graduate student in physics and lead author of the study. "You can get them by satellite images, or you could just go out and do a survey."

Led by Jeff Gore, an assistant professor of physics, Dai and Kirill Korolev, a Pappalardo Postdoctoral Fellow, grew yeast in test tubes and tracked the populations as they approached collapse. Yeast cells cooperate with other members of the population: Each of the organisms secretes an enzyme that breaks down sucrose in the environment into smaller sugars that it can use as a food source. All of the yeast benefit from this process, so a population is most successful when it maintains a certain density neither too low nor too high.

In last year's study, the researchers found that in populations of yeast that are subjected to increasingly stressful conditions, populations become less and less resilient to new disturbances until they
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Contact: Sarah McDonnell
s_mcd@mit.edu
617-253-8923
Massachusetts Institute of Technology
Source:Eurekalert

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