Quantitative analysis of self-organized patterns in ombrotrophic peatlands

We numerically investigate a diffusion-reaction model of an ombrotrophic peatland implementing a Turing instability relying on nutrient accumulation. We propose a systematic and quantitative sorting of the vegetation patterns, based on the statistical analysis of the numbers and filling factor of cl...

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Detalles Bibliográficos
Autores principales: Béguin, Chloé, Brunetti, Maura, Kasparian, Jérôme
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6365544/
https://www.ncbi.nlm.nih.gov/pubmed/30728401
http://dx.doi.org/10.1038/s41598-018-37736-8
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author Béguin, Chloé
Brunetti, Maura
Kasparian, Jérôme
author_facet Béguin, Chloé
Brunetti, Maura
Kasparian, Jérôme
author_sort Béguin, Chloé
collection PubMed
description We numerically investigate a diffusion-reaction model of an ombrotrophic peatland implementing a Turing instability relying on nutrient accumulation. We propose a systematic and quantitative sorting of the vegetation patterns, based on the statistical analysis of the numbers and filling factor of clusters of both Sphagnum mosses and vascular plants. In particular, we define the transition from Sphagnum-percolating to vascular plant-percolating patterns as the nutrient availability is increased. Our pattern sorting allows us to characterize the peatland pattern stability under climate stress, including strong drought.
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spelling pubmed-63655442019-02-08 Quantitative analysis of self-organized patterns in ombrotrophic peatlands Béguin, Chloé Brunetti, Maura Kasparian, Jérôme Sci Rep Article We numerically investigate a diffusion-reaction model of an ombrotrophic peatland implementing a Turing instability relying on nutrient accumulation. We propose a systematic and quantitative sorting of the vegetation patterns, based on the statistical analysis of the numbers and filling factor of clusters of both Sphagnum mosses and vascular plants. In particular, we define the transition from Sphagnum-percolating to vascular plant-percolating patterns as the nutrient availability is increased. Our pattern sorting allows us to characterize the peatland pattern stability under climate stress, including strong drought. Nature Publishing Group UK 2019-02-06 /pmc/articles/PMC6365544/ /pubmed/30728401 http://dx.doi.org/10.1038/s41598-018-37736-8 Text en © The Author(s) 2019 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
Béguin, Chloé
Brunetti, Maura
Kasparian, Jérôme
Quantitative analysis of self-organized patterns in ombrotrophic peatlands
title Quantitative analysis of self-organized patterns in ombrotrophic peatlands
title_full Quantitative analysis of self-organized patterns in ombrotrophic peatlands
title_fullStr Quantitative analysis of self-organized patterns in ombrotrophic peatlands
title_full_unstemmed Quantitative analysis of self-organized patterns in ombrotrophic peatlands
title_short Quantitative analysis of self-organized patterns in ombrotrophic peatlands
title_sort quantitative analysis of self-organized patterns in ombrotrophic peatlands
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6365544/
https://www.ncbi.nlm.nih.gov/pubmed/30728401
http://dx.doi.org/10.1038/s41598-018-37736-8
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