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 thought.
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Acknowledgements
A studentship to R.W. was funded through the UK Overseas Research Students Awards Scheme, the Great Britain–China Educational Trust and the University of Southampton. Laboratory analyses and fieldwork were supported by the National Basic Research Program of China (973 program, 2012CB956104). We are grateful to J. Shen and X. Chen for data collection, Y. L. Li for diatom analysis (core EH2), W. L. Xia for radionuclide measurements and Y. X. Zhu for geochemical analyses. V.D. is supported by an NWO-Rubicon and an EU Marie Curie fellowship. M.S. is funded by a Spinoza (NWO) Award and by a European Research Council Advanced Grant. We thank J. Dash and J. Noble for discussions about ARIMA models. This is a Sustainability Science at Southampton publication.
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R.W. designed the research, undertook fieldwork, performed diatom and mathematical analyses, compiled historical data and wrote the paper. J.A.D. and P.G.L. designed and supervised the research and wrote the paper. E.Z. and X.Y. undertook fieldwork, performed and supervised other analyses, and commented on the manuscript. V.D. and M.S. carried out modelling experiments and wrote the paper. All authors discussed the results and commented on the final manuscript.
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This file contains Supplementary Text and Data 1-9, additional references, Supplementary Tables 1-2 and Supplementary Figures 1-7. (PDF 1692 kb)
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Wang, R., Dearing, J., Langdon, P. et al. Flickering gives early warning signals of a critical transition to a eutrophic lake state. Nature 492, 419–422 (2012). https://doi.org/10.1038/nature11655
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DOI: https://doi.org/10.1038/nature11655
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