What magnets tell us about nature’s ‘flash mobs’
http://www.futurity.org/magnets-flash-mobs-895302/
How does an acorn know to fall when the other acorns do? What triggers insects, or disease, to suddenly break out over large areas? Why do fruit trees have boom and bust years?
The question of what generates such synchronous, ecological “flash mobs” over long distances has long perplexed population ecologists. Part of the answer has to do with something seemingly unrelated: what makes a magnet a magnet.
A study by scientists at the University of California, Davis, found that the same mathematical model that’s been used to study how magnets work—a well-known concept in physics called the Ising model—can be applied to understanding what causes events to occur at the same time over long distances, despite the absence of an external, disruptive force.
The name of the University of California paper:
Emergent long-range synchronization of oscillating ecological populations without external forcing described by Ising universality
http://www.nature.com/ncomms/2015/15040 ... s7664.html
Abstract:
Understanding the synchronization of oscillations across space is fundamentally important to many scientific disciplines. In ecology, long-range synchronization of oscillations in spatial populations may elevate extinction risk and signal an impending catastrophe. The prevailing assumption is that synchronization on distances longer than the dispersal scale can only be due to environmental correlation (the Moran effect). In contrast, we show how long-range synchronization can emerge over distances much longer than the length scales of either dispersal or environmental correlation. In particular, we demonstrate that the transition from incoherence to long-range synchronization of two-cycle oscillations in noisy spatial population models is described by the Ising universality class of statistical physics. This result shows, in contrast to all previous work, how the Ising critical transition can emerge directly from the dynamics of ecological populations.