Preprints
https://doi.org/10.5194/esdd-6-2507-2015
https://doi.org/10.5194/esdd-6-2507-2015
27 Nov 2015
 | 27 Nov 2015
Status: this preprint was under review for the journal ESD but the revision was not accepted.

Early warning signals in complex ecosystems

I. S. Weaver and J. G. Dyke

Abstract. Given the potential for elements of the Earth system to undergo rapid, hard to reverse changes in state, there is a pressing need to establish robust methods to produce early warning signals of such events. Here we present a conceptual ecosystem model in which a diversity of stable states emerge, along with rapid changes, referred to as critical transitions, as a consequence of external driving and non-linear ecological dynamics. We are able to produce robust early warning signals that precede critical transitions. However, we show that there is no correlation between the magnitude of the signal and magnitude or reversibility of any individual critical transition. We discuss these findings in the context of ecosystem management prior to and post critical transitions. We argue that an understanding of the dynamics of the systems is necessary both for management prior and post critical transitions and the effective interpretation of any early warning signal that may be produced for that system.

I. S. Weaver and J. G. Dyke
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
I. S. Weaver and J. G. Dyke
I. S. Weaver and J. G. Dyke

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Short summary
Many parts of the Earth systems undergo rapid changes from one state to another. A disastrous example being a vivacious lake becoming opaque; an algae-dominated state. We model a generic complex ecosystem, where the coupling between life and important environmental variables drives transitions. We find even small numbers of environmental variables to produce complicated networks of states, and that transitions are preceded by warning signals, a result supporting contemporary empirical research.
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