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Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science
There are several conceptual definitions of resilience pertaining to environmental systems and, even if resilience is clearly defined in a particular context, it is challenging to quantify. We identify four characteristics of the response of a system function to disturbance that relate to “resilienc...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4916505/ https://www.ncbi.nlm.nih.gov/pubmed/27329053 http://dx.doi.org/10.1038/srep28426 |
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author | Todman, L. C. Fraser, F. C. Corstanje, R. Deeks, L. K. Harris, J. A. Pawlett, M. Ritz, K. Whitmore, A. P. |
author_facet | Todman, L. C. Fraser, F. C. Corstanje, R. Deeks, L. K. Harris, J. A. Pawlett, M. Ritz, K. Whitmore, A. P. |
author_sort | Todman, L. C. |
collection | PubMed |
description | There are several conceptual definitions of resilience pertaining to environmental systems and, even if resilience is clearly defined in a particular context, it is challenging to quantify. We identify four characteristics of the response of a system function to disturbance that relate to “resilience”: (1) degree of return of the function to a reference level; (2) time taken to reach a new quasi-stable state; (3) rate (i.e. gradient) at which the function reaches the new state; (4) cumulative magnitude of the function (i.e. area under the curve) before a new state is reached. We develop metrics to quantify these characteristics based on an analogy with a mechanical spring and damper system. Using the example of the response of a soil function (respiration) to disturbance, we demonstrate that these metrics effectively discriminate key features of the dynamic response. Although any one of these characteristics could define resilience, each may lead to different insights and conclusions. The salient properties of a resilient response must thus be identified for different contexts. Because the temporal resolution of data affects the accurate determination of these metrics, we recommend that at least twelve measurements are made over the temporal range for which the response is expected. |
format | Online Article Text |
id | pubmed-4916505 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49165052016-06-27 Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science Todman, L. C. Fraser, F. C. Corstanje, R. Deeks, L. K. Harris, J. A. Pawlett, M. Ritz, K. Whitmore, A. P. Sci Rep Article There are several conceptual definitions of resilience pertaining to environmental systems and, even if resilience is clearly defined in a particular context, it is challenging to quantify. We identify four characteristics of the response of a system function to disturbance that relate to “resilience”: (1) degree of return of the function to a reference level; (2) time taken to reach a new quasi-stable state; (3) rate (i.e. gradient) at which the function reaches the new state; (4) cumulative magnitude of the function (i.e. area under the curve) before a new state is reached. We develop metrics to quantify these characteristics based on an analogy with a mechanical spring and damper system. Using the example of the response of a soil function (respiration) to disturbance, we demonstrate that these metrics effectively discriminate key features of the dynamic response. Although any one of these characteristics could define resilience, each may lead to different insights and conclusions. The salient properties of a resilient response must thus be identified for different contexts. Because the temporal resolution of data affects the accurate determination of these metrics, we recommend that at least twelve measurements are made over the temporal range for which the response is expected. Nature Publishing Group 2016-06-22 /pmc/articles/PMC4916505/ /pubmed/27329053 http://dx.doi.org/10.1038/srep28426 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Todman, L. C. Fraser, F. C. Corstanje, R. Deeks, L. K. Harris, J. A. Pawlett, M. Ritz, K. Whitmore, A. P. Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science |
title | Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science |
title_full | Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science |
title_fullStr | Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science |
title_full_unstemmed | Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science |
title_short | Defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science |
title_sort | defining and quantifying the resilience of responses to disturbance: a conceptual and modelling approach from soil science |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4916505/ https://www.ncbi.nlm.nih.gov/pubmed/27329053 http://dx.doi.org/10.1038/srep28426 |
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