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Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation
For the tipping elements in the Earth’s climate system, the most important issue to address is how stable is the desirable state against random perturbations. Extreme biotic and climatic events pose severe hazards to tropical rainforests. Their local effects are extremely stochastic and difficult to...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5571188/ https://www.ncbi.nlm.nih.gov/pubmed/28839285 http://dx.doi.org/10.1038/s41598-017-07686-8 |
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author | Serdukova, Larissa Zheng, Yayun Duan, Jinqiao Kurths, Jürgen |
author_facet | Serdukova, Larissa Zheng, Yayun Duan, Jinqiao Kurths, Jürgen |
author_sort | Serdukova, Larissa |
collection | PubMed |
description | For the tipping elements in the Earth’s climate system, the most important issue to address is how stable is the desirable state against random perturbations. Extreme biotic and climatic events pose severe hazards to tropical rainforests. Their local effects are extremely stochastic and difficult to measure. Moreover, the direction and intensity of the response of forest trees to such perturbations are unknown, especially given the lack of efficient dynamical vegetation models to evaluate forest tree cover changes over time. In this study, we consider randomness in the mathematical modelling of forest trees by incorporating uncertainty through a stochastic differential equation. According to field-based evidence, the interactions between fires and droughts are a more direct mechanism that may describe sudden forest degradation in the south-eastern Amazon. In modeling the Amazonian vegetation system, we include symmetric α-stable Lévy perturbations. We report results of stability analysis of the metastable fertile forest state. We conclude that even a very slight threat to the forest state stability represents L´evy noise with large jumps of low intensity, that can be interpreted as a fire occurring in a non-drought year. During years of severe drought, high-intensity fires significantly accelerate the transition between a forest and savanna state. |
format | Online Article Text |
id | pubmed-5571188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55711882017-09-01 Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation Serdukova, Larissa Zheng, Yayun Duan, Jinqiao Kurths, Jürgen Sci Rep Article For the tipping elements in the Earth’s climate system, the most important issue to address is how stable is the desirable state against random perturbations. Extreme biotic and climatic events pose severe hazards to tropical rainforests. Their local effects are extremely stochastic and difficult to measure. Moreover, the direction and intensity of the response of forest trees to such perturbations are unknown, especially given the lack of efficient dynamical vegetation models to evaluate forest tree cover changes over time. In this study, we consider randomness in the mathematical modelling of forest trees by incorporating uncertainty through a stochastic differential equation. According to field-based evidence, the interactions between fires and droughts are a more direct mechanism that may describe sudden forest degradation in the south-eastern Amazon. In modeling the Amazonian vegetation system, we include symmetric α-stable Lévy perturbations. We report results of stability analysis of the metastable fertile forest state. We conclude that even a very slight threat to the forest state stability represents L´evy noise with large jumps of low intensity, that can be interpreted as a fire occurring in a non-drought year. During years of severe drought, high-intensity fires significantly accelerate the transition between a forest and savanna state. Nature Publishing Group UK 2017-08-24 /pmc/articles/PMC5571188/ /pubmed/28839285 http://dx.doi.org/10.1038/s41598-017-07686-8 Text en © The Author(s) 2017 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 Serdukova, Larissa Zheng, Yayun Duan, Jinqiao Kurths, Jürgen Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation |
title | Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation |
title_full | Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation |
title_fullStr | Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation |
title_full_unstemmed | Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation |
title_short | Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation |
title_sort | metastability for discontinuous dynamical systems under lévy noise: case study on amazonian vegetation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5571188/ https://www.ncbi.nlm.nih.gov/pubmed/28839285 http://dx.doi.org/10.1038/s41598-017-07686-8 |
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