Resilience assessment in complex natural systems
Ecological resilience is the capability of an ecosystem to maintain the same structure and function and avoid crossing catastrophic tipping points (i.e. undergoing irreversible regime shifts). While fundamental for management, concrete ways to estimate and interpret resilience in real ecosystems are...
Published in: | Proceedings of the Royal Society B: Biological Sciences |
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crroyalsociety:10.1098/rspb.2024.0089 2024-06-23T07:51:05+00:00 Resilience assessment in complex natural systems Sguotti, Camilla Vasilakopoulos, Paraskevas Tzanatos, Evangelos Frelat, Romain H2020 Research and Innovation Program Bundesministerium für Bildung und Forschung HORIZON EUROPE Marie Sklodowska-Curie Actions 2024 http://dx.doi.org/10.1098/rspb.2024.0089 https://royalsocietypublishing.org/doi/pdf/10.1098/rspb.2024.0089 https://royalsocietypublishing.org/doi/full-xml/10.1098/rspb.2024.0089 en eng The Royal Society http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ Proceedings of the Royal Society B: Biological Sciences volume 291, issue 2023 ISSN 1471-2954 journal-article 2024 crroyalsociety https://doi.org/10.1098/rspb.2024.0089 2024-06-04T06:23:04Z Ecological resilience is the capability of an ecosystem to maintain the same structure and function and avoid crossing catastrophic tipping points (i.e. undergoing irreversible regime shifts). While fundamental for management, concrete ways to estimate and interpret resilience in real ecosystems are still lacking. Here, we develop an empirical approach to estimate resilience based on the stochastic cusp model derived from catastrophe theory. The cusp model models tipping points derived from a cusp bifurcation. We extend cusp in order to identify the presence of stable and unstable states in complex natural systems. Our Cusp Resilience Assessment (CUSPRA) has three characteristics: (i) it provides estimates on how likely a system is to cross a tipping point (in the form of a cusp bifurcation) characterized by hysteresis, (ii) it assesses resilience in relation to multiple external drivers and (iii) it produces straightforward results for ecosystem-based management. We validate our approach using simulated data and demonstrate its application using empirical time series of an Atlantic cod population and marine ecosystems in the North Sea and the Mediterranean Sea. We show that Cusp Resilience Assessment is a powerful method to empirically estimate resilience in support of a sustainable management of our constantly adapting ecosystems under global climate change. Article in Journal/Newspaper atlantic cod The Royal Society Proceedings of the Royal Society B: Biological Sciences 291 2023 |
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The Royal Society |
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crroyalsociety |
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English |
description |
Ecological resilience is the capability of an ecosystem to maintain the same structure and function and avoid crossing catastrophic tipping points (i.e. undergoing irreversible regime shifts). While fundamental for management, concrete ways to estimate and interpret resilience in real ecosystems are still lacking. Here, we develop an empirical approach to estimate resilience based on the stochastic cusp model derived from catastrophe theory. The cusp model models tipping points derived from a cusp bifurcation. We extend cusp in order to identify the presence of stable and unstable states in complex natural systems. Our Cusp Resilience Assessment (CUSPRA) has three characteristics: (i) it provides estimates on how likely a system is to cross a tipping point (in the form of a cusp bifurcation) characterized by hysteresis, (ii) it assesses resilience in relation to multiple external drivers and (iii) it produces straightforward results for ecosystem-based management. We validate our approach using simulated data and demonstrate its application using empirical time series of an Atlantic cod population and marine ecosystems in the North Sea and the Mediterranean Sea. We show that Cusp Resilience Assessment is a powerful method to empirically estimate resilience in support of a sustainable management of our constantly adapting ecosystems under global climate change. |
author2 |
H2020 Research and Innovation Program Bundesministerium für Bildung und Forschung HORIZON EUROPE Marie Sklodowska-Curie Actions |
format |
Article in Journal/Newspaper |
author |
Sguotti, Camilla Vasilakopoulos, Paraskevas Tzanatos, Evangelos Frelat, Romain |
spellingShingle |
Sguotti, Camilla Vasilakopoulos, Paraskevas Tzanatos, Evangelos Frelat, Romain Resilience assessment in complex natural systems |
author_facet |
Sguotti, Camilla Vasilakopoulos, Paraskevas Tzanatos, Evangelos Frelat, Romain |
author_sort |
Sguotti, Camilla |
title |
Resilience assessment in complex natural systems |
title_short |
Resilience assessment in complex natural systems |
title_full |
Resilience assessment in complex natural systems |
title_fullStr |
Resilience assessment in complex natural systems |
title_full_unstemmed |
Resilience assessment in complex natural systems |
title_sort |
resilience assessment in complex natural systems |
publisher |
The Royal Society |
publishDate |
2024 |
url |
http://dx.doi.org/10.1098/rspb.2024.0089 https://royalsocietypublishing.org/doi/pdf/10.1098/rspb.2024.0089 https://royalsocietypublishing.org/doi/full-xml/10.1098/rspb.2024.0089 |
genre |
atlantic cod |
genre_facet |
atlantic cod |
op_source |
Proceedings of the Royal Society B: Biological Sciences volume 291, issue 2023 ISSN 1471-2954 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1098/rspb.2024.0089 |
container_title |
Proceedings of the Royal Society B: Biological Sciences |
container_volume |
291 |
container_issue |
2023 |
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1802642082206056448 |