Oecologia

, Volume 156, Issue 2, pp 287–304 | Cite as

Wavelet analysis of ecological time series

  • Bernard Cazelles
  • Mario Chavez
  • Dominique Berteaux
  • Frédéric Ménard
  • Jon Olav Vik
  • Stéphanie Jenouvrier
  • Nils C. Stenseth
Population Ecology - Original Paper
First Online:
Received:
Accepted:

Abstract

Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The versatility and attractiveness of the wavelet approach lie in its decomposition properties, principally its time-scale localization. It is especially relevant to the analysis of non-stationary systems, i.e., systems with short-lived transient components, like those observed in ecological systems. Here, we review the basic properties of the wavelet approach for time-series analysis from an ecological perspective. Wavelet decomposition offers several advantages that are discussed in this paper and illustrated by appropriate synthetic and ecological examples. Wavelet analysis is notably free from the assumption of stationarity that makes most methods unsuitable for many ecological time series. Wavelet analysis also permits analysis of the relationships between two signals, and it is especially appropriate for following gradual change in forcing by exogenous variables.

Keywords

Ecological time series Transient dynamics Non-stationarity Discontinuities Wavelets Wavelet analysis Wavelet Power Spectrum Wavelet coherency Environmental forcing 
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Notes

Acknowledgments

We thank the anonymous referees who helped to improve the quality and the clarity of this work. B. C., F. M. and S. J. are partially supported by the program REMIGE–ANR Biodiversité 2005-011.

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Bernard Cazelles
    • 1
    • 2
  • Mario Chavez
    • 3
  • Dominique Berteaux
    • 4
  • Frédéric Ménard
    • 5
  • Jon Olav Vik
    • 6
  • Stéphanie Jenouvrier
    • 7
  • Nils C. Stenseth
    • 6
  1. 1.Ecole Normale SupérieureCNRS UMR 7625ParisFrance
  2. 2.IRD UR GEODESBondyFrance
  3. 3.CHU Pitié-SalpêtrièreLENA – CNRS UPR 640ParisFrance
  4. 4.Canada Research Chair in Conservation of Northern EcosystemsUniversité du Québec à RimouskiRimouskiCanada
  5. 5.Centre de Recherche Halieutique Méditerrannéen et TropicalIRD, UR 109 THETISSèteFrance
  6. 6.Centre for Ecological and Evolutionary Synthesis (CEES), Department of BiologyUniversity of OsloOsloNorway
  7. 7.Centre d’Etudes Biologiques de ChizéCNRSVilliers en BoisFrance

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