Many factors can push a wild animal population to the brink of collapse and ecologists have long sought ways to measure the risk of such a collapse.
Last year, MIT physicists demonstrated that they could numerically predict 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.
The same research team writing in Nature now 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.