SOC defeats chaos: a new population-dynamical model

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Although ecologists have been aware for almost twenty years that population densities may show chaotic temporal evolution, the evidence for chaos in natural populations is completely unsatisfying. The lack of convincing evidence may result from the great technical difficulties caused by environmental noise, but it may also reflect natural regulation processes. In this work we present a new metapopulation-dynamical model, in which the nearest neighbor local population fragments interact by applying a threshold condition. Namely, each local population follows its own temporal evolution until a critical population density is reached, which initiates dispersal (migration) events to the neighbors. This interaction type is common to the self-organized critical (SOC) cellular automation models. The main observation is that the global behavior refers to noisy dynamics with many degrees of freedom, periodical, quasiperiodical or stable-point like collective temporal evolution, depending on the threshold level, but low dimensional chaos does not occur. Moreover, self-organized criticality with power law distribution functions emerges if the threshold level is low enough.

Original languageEnglish
Title of host publicationIFIP Transactions A
Subtitle of host publicationComputer Science and Technology
PublisherPubl by Elsevier Science Publishers B.V.
Pages341-348
Number of pages8
EditionA-41
ISBN (Print)0444816283
Publication statusPublished - Jan 1 1994
EventProceedings of the 2nd IFIP Working Conference on Fractals in the Natural and Applied Sciences - London, UK
Duration: Sep 7 1993Sep 10 1993

Conference

ConferenceProceedings of the 2nd IFIP Working Conference on Fractals in the Natural and Applied Sciences
CityLondon, UK
Period9/7/939/10/93

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Scheuring, I., Janosi, I. M., Csilling, A., & Pasztor, G. (1994). SOC defeats chaos: a new population-dynamical model. In IFIP Transactions A: Computer Science and Technology (A-41 ed., pp. 341-348). Publ by Elsevier Science Publishers B.V..