Sunday, April 14, 2013
Early warning signs of population collapse
MIT News: 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.”
...In their new study, the researchers theorized a new type of indicator that they call “recovery length” — the spatial counterpart to recovery time. This idea is based on the observation that populations living near the boundary of a less hospitable habitat are affected, because the neighboring habitats are connected by migration. Populations further away from the bad region gradually recover to equilibrium, and the spatial scale of this recovery can reveal a population’s susceptibility to collapse, according to the researchers...
Saccharomyces cerevisiae cells in DIC microscopy. This was the subject of the MIT study. Image by Masur, Wikimedia Commons, public domain
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.”
...In their new study, the researchers theorized a new type of indicator that they call “recovery length” — the spatial counterpart to recovery time. This idea is based on the observation that populations living near the boundary of a less hospitable habitat are affected, because the neighboring habitats are connected by migration. Populations further away from the bad region gradually recover to equilibrium, and the spatial scale of this recovery can reveal a population’s susceptibility to collapse, according to the researchers...
Saccharomyces cerevisiae cells in DIC microscopy. This was the subject of the MIT study. Image by Masur, Wikimedia Commons, public domain
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