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Temporal dynamics of bird community composition: an analysis of baseline conditions from long-term data

Author

  • Christian Kampichler
  • David G. Angeler
  • Richard T. Holmes
  • Aivar Leito
  • Sören Svensson
  • Henk P. van der Jeugd
  • Tomasz Wesolowski

Summary, in English

Numerous anthropogenic activities threaten the biodiversity found on earth. Because all ecological communities constantly experience temporal turnover due to natural processes, it is important to distinguish between change due to anthropogenic impact and the underlying natural rate of change. In this study, we used data sets on breeding bird communities that covered at least 20 consecutive years, from a variety of terrestrial ecosystems, to address two main questions. (1) How fast does the composition of bird communities change over time, and can we identify a baseline of natural change that distinguishes primeval systems from systems experiencing varying degrees of human impact? (2) How do patterns of temporal variation in composition vary among bird communities in ecosystems with different anthropogenic impacts? Time lag analysis (TLA) showed a pattern of increasing rate of temporal compositional change from large-scale primeval systems to disturbed and protected systems to distinctly successional systems. TLA slopes of < 0.04 were typical for breeding bird communities with natural turnover, while communities subjected to anthropogenic impact were characterised by TLA slopes of > 0.04. Most of the temporal variability of breeding bird communities was explained by slow changes occurring over decades, regardless of the intensity of human impact. In most of the time series, medium- and short-wave periodicity was not detected, with the exception of breeding bird communities subjected to periodic pulses (e.g. caterpillar outbreaks causing food resource peaks).

Department/s

Publishing year

2014

Language

English

Pages

1301-1313

Publication/Series

Oecologia

Volume

175

Issue

4

Document type

Journal article

Publisher

Springer

Topic

  • Ecology

Keywords

  • Community dynamics
  • Long-term datasets
  • Periodicity
  • Primeval forests
  • Time lag analysis
  • Time series

Status

Published

ISBN/ISSN/Other

  • ISSN: 1432-1939