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Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations

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Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations. / Mambuca, Andrea Marcello; Cammarota, Chiara; Neri, Izaak.

In: Physical Review E, Vol. 105, No. 1, 014305, 13.01.2022.

Research output: Contribution to journalArticlepeer-review

Harvard

Mambuca, AM, Cammarota, C & Neri, I 2022, 'Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations', Physical Review E, vol. 105, no. 1, 014305. https://doi.org/10.1103/PhysRevE.105.014305

APA

Mambuca, A. M., Cammarota, C., & Neri, I. (2022). Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations. Physical Review E, 105(1), [014305]. https://doi.org/10.1103/PhysRevE.105.014305

Vancouver

Mambuca AM, Cammarota C, Neri I. Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations. Physical Review E. 2022 Jan 13;105(1). 014305. https://doi.org/10.1103/PhysRevE.105.014305

Author

Mambuca, Andrea Marcello ; Cammarota, Chiara ; Neri, Izaak. / Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations. In: Physical Review E. 2022 ; Vol. 105, No. 1.

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@article{a8d845a6411c4834b1acbc31e65d0eaa,
title = "Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations",
abstract = "We analyze the stability of linear dynamical systems defined on sparse, random graphs with predator-prey, competitive, and mutualistic interactions. These systems are aimed at modeling the stability of fixed points in large systems defined on complex networks, such as ecosystems consisting of a large number of species that interact through a food web. We develop an exact theory for the spectral distribution and the leading eigenvalue of the corresponding sparse Jacobian matrices. This theory reveals that the nature of local interactions has a strong influence on a system's stability. We show that, in general, linear dynamical systems defined on random graphs with a prescribed degree distribution of unbounded support are unstable if they are large enough, implying a tradeoff between stability and diversity. Remarkably, in contrast to the generic case, antagonistic systems that contain only interactions of the predator-prey type can be stable in the infinite size limit. This feature for antagonistic systems is accompanied by a peculiar oscillatory behavior of the dynamical response of the system after a perturbation, when the mean degree of the graph is small enough. Moreover, for antagonistic systems we also find that there exist a dynamical phase transition and critical mean degree above which the response becomes nonoscillatory.",
keywords = "Complex Systems, Random Matrix Theory, Random graph, Theoretical Ecology, Network Stability",
author = "Mambuca, {Andrea Marcello} and Chiara Cammarota and Izaak Neri",
year = "2022",
month = jan,
day = "13",
doi = "10.1103/PhysRevE.105.014305",
language = "English",
volume = "105",
journal = "Physical review. E",
issn = "2470-0045",
publisher = "American Physical Society",
number = "1",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations

AU - Mambuca, Andrea Marcello

AU - Cammarota, Chiara

AU - Neri, Izaak

PY - 2022/1/13

Y1 - 2022/1/13

N2 - We analyze the stability of linear dynamical systems defined on sparse, random graphs with predator-prey, competitive, and mutualistic interactions. These systems are aimed at modeling the stability of fixed points in large systems defined on complex networks, such as ecosystems consisting of a large number of species that interact through a food web. We develop an exact theory for the spectral distribution and the leading eigenvalue of the corresponding sparse Jacobian matrices. This theory reveals that the nature of local interactions has a strong influence on a system's stability. We show that, in general, linear dynamical systems defined on random graphs with a prescribed degree distribution of unbounded support are unstable if they are large enough, implying a tradeoff between stability and diversity. Remarkably, in contrast to the generic case, antagonistic systems that contain only interactions of the predator-prey type can be stable in the infinite size limit. This feature for antagonistic systems is accompanied by a peculiar oscillatory behavior of the dynamical response of the system after a perturbation, when the mean degree of the graph is small enough. Moreover, for antagonistic systems we also find that there exist a dynamical phase transition and critical mean degree above which the response becomes nonoscillatory.

AB - We analyze the stability of linear dynamical systems defined on sparse, random graphs with predator-prey, competitive, and mutualistic interactions. These systems are aimed at modeling the stability of fixed points in large systems defined on complex networks, such as ecosystems consisting of a large number of species that interact through a food web. We develop an exact theory for the spectral distribution and the leading eigenvalue of the corresponding sparse Jacobian matrices. This theory reveals that the nature of local interactions has a strong influence on a system's stability. We show that, in general, linear dynamical systems defined on random graphs with a prescribed degree distribution of unbounded support are unstable if they are large enough, implying a tradeoff between stability and diversity. Remarkably, in contrast to the generic case, antagonistic systems that contain only interactions of the predator-prey type can be stable in the infinite size limit. This feature for antagonistic systems is accompanied by a peculiar oscillatory behavior of the dynamical response of the system after a perturbation, when the mean degree of the graph is small enough. Moreover, for antagonistic systems we also find that there exist a dynamical phase transition and critical mean degree above which the response becomes nonoscillatory.

KW - Complex Systems

KW - Random Matrix Theory

KW - Random graph

KW - Theoretical Ecology

KW - Network Stability

UR - http://www.scopus.com/inward/record.url?scp=85123534961&partnerID=8YFLogxK

U2 - 10.1103/PhysRevE.105.014305

DO - 10.1103/PhysRevE.105.014305

M3 - Article

VL - 105

JO - Physical review. E

JF - Physical review. E

SN - 2470-0045

IS - 1

M1 - 014305

ER -

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