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Catastrophic Collapse Can Occur without Early Warning: Examples of Silent Catastrophes in Structured Ecological Models

Overview of attention for article published in PLOS ONE, April 2013
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Title
Catastrophic Collapse Can Occur without Early Warning: Examples of Silent Catastrophes in Structured Ecological Models
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0062033
Pubmed ID
Authors

Maarten C. Boerlijst, Thomas Oudman, André M. de Roos

Abstract

Catastrophic and sudden collapses of ecosystems are sometimes preceded by early warning signals that potentially could be used to predict and prevent a forthcoming catastrophe. Universality of these early warning signals has been proposed, but no formal proof has been provided. Here, we show that in relatively simple ecological models the most commonly used early warning signals for a catastrophic collapse can be silent. We underpin the mathematical reason for this phenomenon, which involves the direction of the eigenvectors of the system. Our results demonstrate that claims on the universality of early warning signals are not correct, and that catastrophic collapses can occur without prior warning. In order to correctly predict a collapse and determine whether early warning signals precede the collapse, detailed knowledge of the mathematical structure of the approaching bifurcation is necessary. Unfortunately, such knowledge is often only obtained after the collapse has already occurred.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 4%
United Kingdom 3 2%
Brazil 1 <1%
Italy 1 <1%
Netherlands 1 <1%
Spain 1 <1%
Taiwan 1 <1%
Venezuela, Bolivarian Republic of 1 <1%
Luxembourg 1 <1%
Other 0 0%
Unknown 152 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 46 27%
Researcher 37 22%
Student > Master 19 11%
Student > Bachelor 13 8%
Professor 6 4%
Other 24 14%
Unknown 24 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 27%
Environmental Science 40 24%
Engineering 10 6%
Earth and Planetary Sciences 8 5%
Physics and Astronomy 7 4%
Other 25 15%
Unknown 34 20%