Tipping points cause some important ecosystem surprises.  Examples include collapses of rangelands, water quality, and some fisheries.  The trouble with tipping points is that they are hard to anticipate in advance.  However, tremors may provide an advance warning of some tipping points.

The graphic shows a model of a pastoral system .  There is a tipping point when the stocking level of herbivores is about 5.  Above the tipping point, grassy vegetation disappears and the grazing system collapses.  As the tipping point is approached from low levels of herbivores, the standard deviation of grass biomass rises sharply before the tipping point is reached.  If the herbivore level is rising slowly enough, the rise in standard deviation could provide advance warning of impending collapse.  If the pastoralist was attentive to the warning, sheep numbers could be reduced in time to prevent the collapse.
 

 Thomas Kleinen and colleagues have shown that reddening of the variance spectrum can anticipate rapid climate changes such as those that could result from a breakdown in ocean circulation.  Steve Carpenter and Buz Brock have analyzed water pollution, air pollution, and social systems that tremble before they tip.  They demonstrate increases in variance, which may be more easily detected than reddening of spectra.  Importantly, the variance increases can be detected with simple statistical filters using common time-series data.  No particular knowledge of the actual ecosystem dynamics is required.  Berglund and Gentz compare hard losses of stability in which an attractor vanishes (such as the pastoral system shown here) with soft losses of stability where an attractor divides like a braided river.  Hard losses of stability — the regime shifts that cause resource collapses — may provide stronger advance warnings than soft losses of stability — the regime shifts that gradually and imperceptibly create traps for ecosystem management.  Ludwig, Walker and Holling provide a more general discussion of hard and soft losses of stability in ecosystems.