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Defining Chaos for Real, Noisy Data: Local Lyapunov Exponents and Sensitive Response to Perturbations

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Chaos in Real Data

Part of the book series: Population and Community Biology Series ((PCBS,volume 27))

Abstract

It’s a noisy world after all. A recent literature survey Hairston et al. 1996) found that recruitment success of long-lived iteroparous adults could vary from one year to the next by factors of up to 333 in plants, 591 in marine invertebrates, 38 in terrestrial vertebrates and 2200 in birds; that of dormant propagules (seeds or eggs) varied by up to 1150 in plants and 31,600 in terrestrial insects. The optimistic hypothesis that all of this could be deterministic chaos has gradually evolved into the less convenient recognition that various forms of unpredictable “noise” (climate, external disturbance, habitat modification by other species, etc.) coexist with the nonlinearities produced by competition, predation, parasites, pathogens and their potentially complex interactions.

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Authors and Affiliations

  1. Biomathematics Graduate Program, Department of Statistics, North Carolina State University, Raleigh, NC, 27695-8203, USA

    Stephen P. Ellner

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  1. Stephen P. Ellner
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Joe N. Perry Robert H. Smith Ian P. Woiwod David R. Morse

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© 2000 Springer Science+Business Media Dordrecht

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Ellner, S.P. (2000). Defining Chaos for Real, Noisy Data: Local Lyapunov Exponents and Sensitive Response to Perturbations. In: Perry, J.N., Smith, R.H., Woiwod, I.P., Morse, D.R. (eds) Chaos in Real Data. Population and Community Biology Series, vol 27. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-4010-2_1

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  • DOI: https://doi.org/10.1007/978-94-011-4010-2_1

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-5772-1

  • Online ISBN: 978-94-011-4010-2

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