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Rate of recovery from perturbations as a means to forecast future stability of living systems
Anticipating critical transitions in complex ecological and living systems is an important need because it is often difficult to restore a system to its pre-transition state once the transition occurs. Recent studies demonstrate that several indicators based on changes in ecological time series can...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6006279/ https://www.ncbi.nlm.nih.gov/pubmed/29915262 http://dx.doi.org/10.1038/s41598-018-27573-0 |
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author | Ghadami, Amin Gourgou, Eleni Epureanu, Bogdan I. |
author_facet | Ghadami, Amin Gourgou, Eleni Epureanu, Bogdan I. |
author_sort | Ghadami, Amin |
collection | PubMed |
description | Anticipating critical transitions in complex ecological and living systems is an important need because it is often difficult to restore a system to its pre-transition state once the transition occurs. Recent studies demonstrate that several indicators based on changes in ecological time series can indicate that the system is approaching an impending transition. An exciting question is, however, whether we can predict more characteristics of the future system stability using measurements taken away from the transition. We address this question by introducing a model-less forecasting method to forecast catastrophic transition of an experimental ecological system. The experiment is based on the dynamics of a yeast population, which is known to exhibit a catastrophic transition as the environment deteriorates. By measuring the system’s response to perturbations prior to transition, we forecast the distance to the upcoming transition, the type of the transition (i.e., catastrophic/non-catastrophic) and the future equilibrium points within a range near the transition. Experimental results suggest a strong potential for practical applicability of this approach for ecological systems which are at risk of catastrophic transitions, where there is a pressing need for information about upcoming thresholds. |
format | Online Article Text |
id | pubmed-6006279 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-60062792018-06-26 Rate of recovery from perturbations as a means to forecast future stability of living systems Ghadami, Amin Gourgou, Eleni Epureanu, Bogdan I. Sci Rep Article Anticipating critical transitions in complex ecological and living systems is an important need because it is often difficult to restore a system to its pre-transition state once the transition occurs. Recent studies demonstrate that several indicators based on changes in ecological time series can indicate that the system is approaching an impending transition. An exciting question is, however, whether we can predict more characteristics of the future system stability using measurements taken away from the transition. We address this question by introducing a model-less forecasting method to forecast catastrophic transition of an experimental ecological system. The experiment is based on the dynamics of a yeast population, which is known to exhibit a catastrophic transition as the environment deteriorates. By measuring the system’s response to perturbations prior to transition, we forecast the distance to the upcoming transition, the type of the transition (i.e., catastrophic/non-catastrophic) and the future equilibrium points within a range near the transition. Experimental results suggest a strong potential for practical applicability of this approach for ecological systems which are at risk of catastrophic transitions, where there is a pressing need for information about upcoming thresholds. Nature Publishing Group UK 2018-06-18 /pmc/articles/PMC6006279/ /pubmed/29915262 http://dx.doi.org/10.1038/s41598-018-27573-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ghadami, Amin Gourgou, Eleni Epureanu, Bogdan I. Rate of recovery from perturbations as a means to forecast future stability of living systems |
title | Rate of recovery from perturbations as a means to forecast future stability of living systems |
title_full | Rate of recovery from perturbations as a means to forecast future stability of living systems |
title_fullStr | Rate of recovery from perturbations as a means to forecast future stability of living systems |
title_full_unstemmed | Rate of recovery from perturbations as a means to forecast future stability of living systems |
title_short | Rate of recovery from perturbations as a means to forecast future stability of living systems |
title_sort | rate of recovery from perturbations as a means to forecast future stability of living systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6006279/ https://www.ncbi.nlm.nih.gov/pubmed/29915262 http://dx.doi.org/10.1038/s41598-018-27573-0 |
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