Flickering gives early warning signals of a critical transition to a eutrophic lake state : Letter

R. Wang, J. Dearing, P.G. Langdon, E. Zhang, X. Yang, V. Dakos, M. Scheffer

Research output: Contribution to journalArticleAcademicpeer-review

243 Citations (Scopus)

Abstract

There is a recognized need to anticipate tipping points, or critical transitions, in social–ecological systems1, 2. Studies of mathematical3, 4, 5 and experimental6, 7, 8, 9 systems have shown that systems may ‘wobble’ before a critical transition. Such early warning signals10 may be due to the phenomenon of critical slowing down, which causes a system to recover slowly from small impacts, or to a flickering phenomenon, which causes a system to switch back and forth between alternative states in response to relatively large impacts. Such signals for transitions in social–ecological systems have rarely been observed11, not the least because high-resolution time series are normally required. Here we combine empirical data from a lake-catchment system with a mathematical model and show that flickering can be detected from sparse data. We show how rising variance coupled to decreasing autocorrelation and skewness started 10–30 years before the transition to eutrophic lake conditions in both the empirical records and the model output, a finding that is consistent with flickering rather than critical slowing down4, 12. Our results suggest that if environmental regimes are sufficiently affected by large external impacts that flickering is induced, then early warning signals of transitions in modern social–ecological systems may be stronger, and hence easier to identify, than previously thoug
Original languageEnglish
Pages (from-to)419-422
JournalNature
Volume492
DOIs
Publication statusPublished - 2012

Keywords

  • aquatic ecology
  • surface water quality
  • lakes
  • eutrophication
  • algae
  • change of state
  • transition elements
  • interactions
  • china
  • ecosystem services
  • regime shifts
  • climate-change
  • tipping point
  • resilience
  • systems
  • science
  • time

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