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Early warning signals of extinction in deteriorating environments

Author

Listed:
  • John M. Drake

    (Odum School of Ecology, University of Georgia)

  • Blaine D. Griffen

    (University of South Carolina, Columbia, South Carolina 29208, USA)

Abstract

Extinction: when the end is nigh At some stage, populations that become extinct because of environmental degradation pass a critical point beyond which extinction is inevitable. There are obvious advantages to being able to predict such tipping points in advance, and according to 'critical transitions' theory, that should be possible for dynamical systems of many types — including ecosystems, financial markets and climate (for a summary, see http://go.nature.com/uHi555 ). In experiments with laboratory populations of the water flea Daphnia magna, John Drake and Blaine Griffen identify a point they call 'critical slowing down' in the underlying growth equations of populations that are destined to fail. The results of these experiments indicate when, where and how to most sensitively detect this slowing down in nature, suggesting new techniques for assessing population viability.

Suggested Citation

  • John M. Drake & Blaine D. Griffen, 2010. "Early warning signals of extinction in deteriorating environments," Nature, Nature, vol. 467(7314), pages 456-459, September.
    • Handle: RePEc:nat:nature:v:467:y:2010:i:7314:d:10.1038_nature09389
    DOI: 10.1038/nature09389
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    Citations

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    Cited by:

    1. Richter, Andries & Dakos, Vasilis, 2015. "Profit fluctuations signal eroding resilience of natural resources," Ecological Economics, Elsevier, vol. 117(C), pages 12-21.
    2. Peng, Xiaoyi & Zhao, Yi & Small, Michael, 2020. "Identification and prediction of bifurcation tipping points using complex networks based on quasi-isometric mapping," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    3. Pascal Peduzzi, 2019. "The Disaster Risk, Global Change, and Sustainability Nexus," Sustainability, MDPI, vol. 11(4), pages 1-21, February.
    4. Duncan A. O’Brien & Smita Deb & Gideon Gal & Stephen J. Thackeray & Partha S. Dutta & Shin-ichiro S. Matsuzaki & Linda May & Christopher F. Clements, 2023. "Early warning signals have limited applicability to empirical lake data," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    5. Yang, Anji & Wang, Hao & Yuan, Sanling, 2023. "Tipping time in a stochastic Leslie predator–prey model," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    6. William A. Brock & Steven N. Durlauf, 2015. "On Sturdy Policy Evaluation," The Journal of Legal Studies, University of Chicago Press, vol. 44(S2), pages 447-473.
    7. Martin Lindegren & Vasilis Dakos & Joachim P Gröger & Anna Gårdmark & Georgs Kornilovs & Saskia A Otto & Christian Möllmann, 2012. "Early Detection of Ecosystem Regime Shifts: A Multiple Method Evaluation for Management Application," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    8. Yayla Özgür & Keskin Emrah & Keles Hüseyin, 2022. "The Relationship Between Environmental Sensitivity, Ecological Attitude, and the Ecological Product purchasing Behaviour of Tourists," European Journal of Tourism, Hospitality and Recreation, Sciendo, vol. 12(1), pages 31-45, December.
    9. Chengyi Tu & Paolo DOdorico & Samir Suweis, 2018. "Critical slowing down associated with critical transition and risk of collapse in cryptocurrency," Papers 1806.08386, arXiv.org, revised Nov 2019.
    10. Vasilis Dakos & Stephen R Carpenter & William A Brock & Aaron M Ellison & Vishwesha Guttal & Anthony R Ives & Sonia Kéfi & Valerie Livina & David A Seekell & Egbert H van Nes & Marten Scheffer, 2012. "Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-20, July.
    11. Manuel F G Weinkauf & Fabian G W Bonitz & Rossana Martini & Michal Kučera, 2019. "An extinction event in planktonic Foraminifera preceded by stabilizing selection," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-21, October.
    12. Christian Meisel & Andreas Klaus & Christian Kuehn & Dietmar Plenz, 2015. "Critical Slowing Down Governs the Transition to Neuron Spiking," PLOS Computational Biology, Public Library of Science, vol. 11(2), pages 1-20, February.
    13. Trisha L Spanbauer & Craig R Allen & David G Angeler & Tarsha Eason & Sherilyn C Fritz & Ahjond S Garmestani & Kirsty L Nash & Jeffery R Stone, 2014. "Prolonged Instability Prior to a Regime Shift," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-7, October.
    14. Tobias Brett & Marco Ajelli & Quan-Hui Liu & Mary G Krauland & John J Grefenstette & Willem G van Panhuis & Alessandro Vespignani & John M Drake & Pejman Rohani, 2020. "Detecting critical slowing down in high-dimensional epidemiological systems," PLOS Computational Biology, Public Library of Science, vol. 16(3), pages 1-19, March.
    15. Ryan D Batt & Tarsha Eason & Ahjond Garmestani, 2019. "Time scale of resilience loss: Implications for managing critical transitions in water quality," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-19, October.
    16. William A Brock & Stephen R Carpenter, 2012. "Early Warnings of Regime Shift When the Ecosystem Structure Is Unknown," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-10, September.
    17. Bhowmick, Amiya Ranjan & Saha, Bapi & Chattopadhyay, Joydev & Ray, Santanu & Bhattacharya, Sabyasachi, 2015. "Cooperation in species: Interplay of population regulation and extinction through global population dynamics database," Ecological Modelling, Elsevier, vol. 312(C), pages 150-165.
    18. Tatiana Baumuratova & Simona Dobre & Thierry Bastogne & Thomas Sauter, 2013. "Switch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-12, December.
    19. Zvonko Kostanjcar & Stjepan Begusic & H. E. Stanley & Boris Podobnik, 2015. "Estimating Tipping Points in Feedback-Driven Financial Networks," Papers 1509.04952, arXiv.org.
    20. Tobias S Brett & Eamon B O’Dea & Éric Marty & Paige B Miller & Andrew W Park & John M Drake & Pejman Rohani, 2018. "Anticipating epidemic transitions with imperfect data," PLOS Computational Biology, Public Library of Science, vol. 14(6), pages 1-18, June.
    21. Mohammed, M.M.A. & Landi, P. & Minoarivelo, H.O. & Hui, C., 2018. "Frugivory and seed dispersal: Extended bi-stable persistence and reduced clustering of plants," Ecological Modelling, Elsevier, vol. 380(C), pages 31-39.
    22. Kiran D’Souza & Bogdan I Epureanu & Mercedes Pascual, 2015. "Forecasting Bifurcations from Large Perturbation Recoveries in Feedback Ecosystems," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-19, September.
    23. Maarten C Boerlijst & Thomas Oudman & André M de Roos, 2013. "Catastrophic Collapse Can Occur without Early Warning: Examples of Silent Catastrophes in Structured Ecological Models," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-6, April.
    24. Manfred Füllsack & Daniel Reisinger & Marie Kapeller & Georg Jäger, 2022. "Early warning signals from the periphery," Journal of Computational Social Science, Springer, vol. 5(1), pages 665-685, May.
    25. Orozco-Fuentes, S. & Griffiths, G. & Holmes, M.J. & Ettelaie, R. & Smith, J. & Baggaley, A.W. & Parker, N.G., 2019. "Early warning signals in plant disease outbreaks," Ecological Modelling, Elsevier, vol. 393(C), pages 12-19.

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