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A Generalized Spatial Measure for Resilience of Microbial Systems
The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition; that is, a community with diminishing or low resilience may be close to catastrop...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4823267/ https://www.ncbi.nlm.nih.gov/pubmed/27092116 http://dx.doi.org/10.3389/fmicb.2016.00443 |
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author | Renslow, Ryan S. Lindemann, Stephen R. Song, Hyun-Seob |
author_facet | Renslow, Ryan S. Lindemann, Stephen R. Song, Hyun-Seob |
author_sort | Renslow, Ryan S. |
collection | PubMed |
description | The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition; that is, a community with diminishing or low resilience may be close to catastrophic shift in function or an irreversible collapse. Typically, resilience is quantified using recovery time, which may be difficult or impossible to directly measure in microbial systems. A recent study in the literature showed that under certain conditions, a set of spatial-based metrics termed recovery length, can be correlated to recovery time, and thus may be a reasonable alternative measure of resilience. However, this spatial metric of resilience is limited to use for step-change perturbations. Building upon the concept of recovery length, we propose a more general form of the spatial metric of resilience that can be applied to any shape of perturbation profiles (for example, either sharp or smooth gradients). We termed this new spatial measure “perturbation-adjusted spatial metric of resilience” (PASMORE). We demonstrate the applicability of the proposed metric using a mathematical model of a microbial mat. |
format | Online Article Text |
id | pubmed-4823267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-48232672016-04-18 A Generalized Spatial Measure for Resilience of Microbial Systems Renslow, Ryan S. Lindemann, Stephen R. Song, Hyun-Seob Front Microbiol Microbiology The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition; that is, a community with diminishing or low resilience may be close to catastrophic shift in function or an irreversible collapse. Typically, resilience is quantified using recovery time, which may be difficult or impossible to directly measure in microbial systems. A recent study in the literature showed that under certain conditions, a set of spatial-based metrics termed recovery length, can be correlated to recovery time, and thus may be a reasonable alternative measure of resilience. However, this spatial metric of resilience is limited to use for step-change perturbations. Building upon the concept of recovery length, we propose a more general form of the spatial metric of resilience that can be applied to any shape of perturbation profiles (for example, either sharp or smooth gradients). We termed this new spatial measure “perturbation-adjusted spatial metric of resilience” (PASMORE). We demonstrate the applicability of the proposed metric using a mathematical model of a microbial mat. Frontiers Media S.A. 2016-04-07 /pmc/articles/PMC4823267/ /pubmed/27092116 http://dx.doi.org/10.3389/fmicb.2016.00443 Text en Copyright © 2016 Renslow, Lindemann and Song. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Renslow, Ryan S. Lindemann, Stephen R. Song, Hyun-Seob A Generalized Spatial Measure for Resilience of Microbial Systems |
title | A Generalized Spatial Measure for Resilience of Microbial Systems |
title_full | A Generalized Spatial Measure for Resilience of Microbial Systems |
title_fullStr | A Generalized Spatial Measure for Resilience of Microbial Systems |
title_full_unstemmed | A Generalized Spatial Measure for Resilience of Microbial Systems |
title_short | A Generalized Spatial Measure for Resilience of Microbial Systems |
title_sort | generalized spatial measure for resilience of microbial systems |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4823267/ https://www.ncbi.nlm.nih.gov/pubmed/27092116 http://dx.doi.org/10.3389/fmicb.2016.00443 |
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