Cargando…

An Approach to Study Species Persistence in Unconstrained Random Networks

The connection between structure and stability of ecological networks has been widely studied in the last fifty years. A challenge that scientists continue to face is that in-depth mathematical model analysis is often difficult, unless the considered systems are specifically constrained. This makes...

Descripción completa

Detalles Bibliográficos
Autores principales: Fischer, Samuel M., Huth, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773691/
https://www.ncbi.nlm.nih.gov/pubmed/31575980
http://dx.doi.org/10.1038/s41598-019-50373-z
_version_ 1783455929558106112
author Fischer, Samuel M.
Huth, Andreas
author_facet Fischer, Samuel M.
Huth, Andreas
author_sort Fischer, Samuel M.
collection PubMed
description The connection between structure and stability of ecological networks has been widely studied in the last fifty years. A challenge that scientists continue to face is that in-depth mathematical model analysis is often difficult, unless the considered systems are specifically constrained. This makes it challenging to generalize results. Therefore, methods are needed that relax the required restrictions. Here, we introduce a novel heuristic approach that provides persistence estimates for random systems without limiting the admissible parameter range and system behaviour. We apply our approach to study persistence of species in random generalized Lotka-Volterra systems and present simulation results, which confirm the accuracy of our predictions. Our results suggest that persistence is mainly driven by the linkage density, whereby additional links can both favour and hinder persistence. In particular, we observed “persistence bistability”, a rarely studied feature of random networks, leading to a dependency of persistence on initial species densities. Networks with this property exhibit tipping points, in which species loss can lead to a cascade of extinctions. The methods developed in this paper may facilitate the study of more general models and thereby provide a step forward towards a unifying framework of network architecture and stability.
format Online
Article
Text
id pubmed-6773691
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-67736912019-10-04 An Approach to Study Species Persistence in Unconstrained Random Networks Fischer, Samuel M. Huth, Andreas Sci Rep Article The connection between structure and stability of ecological networks has been widely studied in the last fifty years. A challenge that scientists continue to face is that in-depth mathematical model analysis is often difficult, unless the considered systems are specifically constrained. This makes it challenging to generalize results. Therefore, methods are needed that relax the required restrictions. Here, we introduce a novel heuristic approach that provides persistence estimates for random systems without limiting the admissible parameter range and system behaviour. We apply our approach to study persistence of species in random generalized Lotka-Volterra systems and present simulation results, which confirm the accuracy of our predictions. Our results suggest that persistence is mainly driven by the linkage density, whereby additional links can both favour and hinder persistence. In particular, we observed “persistence bistability”, a rarely studied feature of random networks, leading to a dependency of persistence on initial species densities. Networks with this property exhibit tipping points, in which species loss can lead to a cascade of extinctions. The methods developed in this paper may facilitate the study of more general models and thereby provide a step forward towards a unifying framework of network architecture and stability. Nature Publishing Group UK 2019-10-01 /pmc/articles/PMC6773691/ /pubmed/31575980 http://dx.doi.org/10.1038/s41598-019-50373-z 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
Fischer, Samuel M.
Huth, Andreas
An Approach to Study Species Persistence in Unconstrained Random Networks
title An Approach to Study Species Persistence in Unconstrained Random Networks
title_full An Approach to Study Species Persistence in Unconstrained Random Networks
title_fullStr An Approach to Study Species Persistence in Unconstrained Random Networks
title_full_unstemmed An Approach to Study Species Persistence in Unconstrained Random Networks
title_short An Approach to Study Species Persistence in Unconstrained Random Networks
title_sort approach to study species persistence in unconstrained random networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773691/
https://www.ncbi.nlm.nih.gov/pubmed/31575980
http://dx.doi.org/10.1038/s41598-019-50373-z
work_keys_str_mv AT fischersamuelm anapproachtostudyspeciespersistenceinunconstrainedrandomnetworks
AT huthandreas anapproachtostudyspeciespersistenceinunconstrainedrandomnetworks
AT fischersamuelm approachtostudyspeciespersistenceinunconstrainedrandomnetworks
AT huthandreas approachtostudyspeciespersistenceinunconstrainedrandomnetworks