Abstract:
Early warning signals (EWS) are statistical indicators that a rapid regime shift
may be forthcoming. Their development has given ecologists hope of predicting
rapid regime shifts before they occur. Accurate predictions, however, rely on the
signals being appropriate to the system in question. Most of the EWS commonly
applied in ecology have been studied in the context of one specific type of regime
shift (the type brought on by a saddle-node bifurcation, at which one stable
equilibrium point collides with an unstable equilibrium and disappears) under one
particular perturbation scheme (temporally uncorrelated noise that perturbs the net
population growth rate in a density independent way). Whether and when these
EWS can be applied to other ecological situations remains relatively unknown,
and certainly underappreciated. We study a range of models with different types
of dynamical transitions (including rapid regime shifts) and several perturbation
schemes (density-dependent uncorrelated or temporally-correlated noise) and test
the ability of EWS to warn of an approaching transition. We also test the sensitivity
of our results to the amount of available pre-transition data and various decisions
that must be made in the analysis (i.e. the rolling window size and smoothing
bandwidth used to compute the EWS). We find that EWS generally work well to
signal an impending saddle-node bifurcation, regardless of the autocorrelation or
intensity of the noise. However, EWS do not reliably appear as expected for other
types of transition. EWS were often very sensitive to the length of the pre-transition
time series analyzed, and usually less sensitive to other decisions. We conclude that
the EWS perform well for saddle-node bifurcation in a range of noise environments,
but different methods should be used to predict other types of regime shifts. As a
consequence, knowledge of the mechanism behind a possible regime shift is needed
before EWS can be used to predict it.
