Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1038/s41598-019-50373-z
Lizenz creative commons licence
Titel (primär) An approach to study species persistence in unconstrained random networks
Autor Fischer, S.M.; Huth, A.
Quelle Scientific Reports
Erscheinungsjahr 2019
Department OESA; iDiv
Band/Volume 9
Seite von art. 14110
Sprache englisch
Supplements https://static-content.springer.com/esm/art%3A10.1038%2Fs41598-019-50373-z/MediaObjects/41598_2019_50373_MOESM1_ESM.pdf
Abstract 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.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=22360
Fischer, S.M., Huth, A. (2019):
An approach to study species persistence in unconstrained random networks
Sci. Rep. 9 , art. 14110 10.1038/s41598-019-50373-z