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Meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal

Invasive species are recognized as a significant threat to biodiversity. The mathematical modeling of their spatio-temporal dynamics can provide significant help to environmental managers in devising suitable control strategies. Several mathematical approaches have been proposed in recent decades to...

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Autores principales: Pepper, Nick, Gerardo-Giorda, Luca, Montomoli, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838098/
https://www.ncbi.nlm.nih.gov/pubmed/31700073
http://dx.doi.org/10.1038/s41598-019-52763-9
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author Pepper, Nick
Gerardo-Giorda, Luca
Montomoli, Francesco
author_facet Pepper, Nick
Gerardo-Giorda, Luca
Montomoli, Francesco
author_sort Pepper, Nick
collection PubMed
description Invasive species are recognized as a significant threat to biodiversity. The mathematical modeling of their spatio-temporal dynamics can provide significant help to environmental managers in devising suitable control strategies. Several mathematical approaches have been proposed in recent decades to efficiently model the dispersal of invasive species. Relying on the assumption that the dispersal of an individual is random, but the density of individuals at the scale of the population can be considered smooth, reaction-diffusion models are a good trade-off between model complexity and flexibility for use in different situations. In this paper we present a continuous reaction-diffusion model coupled with arbitrary Polynomial Chaos (aPC) to assess the impact of uncertainties in the model parameters. We show how the finite elements framework is well-suited to handle important landscape heterogeneities as elevation and the complex geometries associated with the boundaries of an actual geographical region. We demonstrate the main capabilities of the proposed coupled model by assessing the uncertainties in the invasion of an alien species invading the Basque Country region in Northern Spain.
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spelling pubmed-68380982019-11-14 Meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal Pepper, Nick Gerardo-Giorda, Luca Montomoli, Francesco Sci Rep Article Invasive species are recognized as a significant threat to biodiversity. The mathematical modeling of their spatio-temporal dynamics can provide significant help to environmental managers in devising suitable control strategies. Several mathematical approaches have been proposed in recent decades to efficiently model the dispersal of invasive species. Relying on the assumption that the dispersal of an individual is random, but the density of individuals at the scale of the population can be considered smooth, reaction-diffusion models are a good trade-off between model complexity and flexibility for use in different situations. In this paper we present a continuous reaction-diffusion model coupled with arbitrary Polynomial Chaos (aPC) to assess the impact of uncertainties in the model parameters. We show how the finite elements framework is well-suited to handle important landscape heterogeneities as elevation and the complex geometries associated with the boundaries of an actual geographical region. We demonstrate the main capabilities of the proposed coupled model by assessing the uncertainties in the invasion of an alien species invading the Basque Country region in Northern Spain. Nature Publishing Group UK 2019-11-07 /pmc/articles/PMC6838098/ /pubmed/31700073 http://dx.doi.org/10.1038/s41598-019-52763-9 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
Pepper, Nick
Gerardo-Giorda, Luca
Montomoli, Francesco
Meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal
title Meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal
title_full Meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal
title_fullStr Meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal
title_full_unstemmed Meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal
title_short Meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal
title_sort meta-modeling on detailed geography for accurate prediction of invasive alien species dispersal
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838098/
https://www.ncbi.nlm.nih.gov/pubmed/31700073
http://dx.doi.org/10.1038/s41598-019-52763-9
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