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Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example

Growth of critical fluctuations prior to catastrophic state transition is generally regarded as a universal phenomenon, providing a valuable early warning signal in dynamical systems. Using an ecological fisheries model of three populations (juvenile prey J, adult prey A and predator P), a recent st...

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Autores principales: Negahbani, Ehsan, Steyn-Ross, D. Alistair, Steyn-Ross, Moira L., Aguirre, Luis A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025176/
https://www.ncbi.nlm.nih.gov/pubmed/27631984
http://dx.doi.org/10.1371/journal.pone.0163003
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author Negahbani, Ehsan
Steyn-Ross, D. Alistair
Steyn-Ross, Moira L.
Aguirre, Luis A.
author_facet Negahbani, Ehsan
Steyn-Ross, D. Alistair
Steyn-Ross, Moira L.
Aguirre, Luis A.
author_sort Negahbani, Ehsan
collection PubMed
description Growth of critical fluctuations prior to catastrophic state transition is generally regarded as a universal phenomenon, providing a valuable early warning signal in dynamical systems. Using an ecological fisheries model of three populations (juvenile prey J, adult prey A and predator P), a recent study has reported silent early warning signals obtained from P and A populations prior to saddle-node (SN) bifurcation, and thus concluded that early warning signals are not universal. By performing a full eigenvalue analysis of the same system we demonstrate that while J and P populations undergo SN bifurcation, A does not jump to a new state, so it is not expected to carry early warning signs. In contrast with the previous study, we capture a significant increase in the noise-induced fluctuations in the P population, but only on close approach to the bifurcation point; it is not clear why the P variance initially shows a decaying trend. Here we resolve this puzzle using observability measures from control theory. By computing the observability coefficient for the system from the recordings of each population considered one at a time, we are able to quantify their ability to describe changing internal dynamics. We demonstrate that precursor fluctuations are best observed using only the J variable, and also P variable if close to transition. Using observability analysis we are able to describe why a poorly observable variable (P) has poor forecasting capabilities although a full eigenvalue analysis shows that this variable undergoes a bifurcation. We conclude that observability analysis provides complementary information to identify the variables carrying early-warning signs about impending state transition.
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spelling pubmed-50251762016-09-27 Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example Negahbani, Ehsan Steyn-Ross, D. Alistair Steyn-Ross, Moira L. Aguirre, Luis A. PLoS One Research Article Growth of critical fluctuations prior to catastrophic state transition is generally regarded as a universal phenomenon, providing a valuable early warning signal in dynamical systems. Using an ecological fisheries model of three populations (juvenile prey J, adult prey A and predator P), a recent study has reported silent early warning signals obtained from P and A populations prior to saddle-node (SN) bifurcation, and thus concluded that early warning signals are not universal. By performing a full eigenvalue analysis of the same system we demonstrate that while J and P populations undergo SN bifurcation, A does not jump to a new state, so it is not expected to carry early warning signs. In contrast with the previous study, we capture a significant increase in the noise-induced fluctuations in the P population, but only on close approach to the bifurcation point; it is not clear why the P variance initially shows a decaying trend. Here we resolve this puzzle using observability measures from control theory. By computing the observability coefficient for the system from the recordings of each population considered one at a time, we are able to quantify their ability to describe changing internal dynamics. We demonstrate that precursor fluctuations are best observed using only the J variable, and also P variable if close to transition. Using observability analysis we are able to describe why a poorly observable variable (P) has poor forecasting capabilities although a full eigenvalue analysis shows that this variable undergoes a bifurcation. We conclude that observability analysis provides complementary information to identify the variables carrying early-warning signs about impending state transition. Public Library of Science 2016-09-15 /pmc/articles/PMC5025176/ /pubmed/27631984 http://dx.doi.org/10.1371/journal.pone.0163003 Text en © 2016 Negahbani et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Negahbani, Ehsan
Steyn-Ross, D. Alistair
Steyn-Ross, Moira L.
Aguirre, Luis A.
Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example
title Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example
title_full Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example
title_fullStr Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example
title_full_unstemmed Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example
title_short Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example
title_sort which system variables carry robust early signs of upcoming phase transition? an ecological example
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025176/
https://www.ncbi.nlm.nih.gov/pubmed/27631984
http://dx.doi.org/10.1371/journal.pone.0163003
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