Sensitivity of collective action to uncertainty about climate tipping points

Journal name:
Nature Climate Change
Volume:
4,
Pages:
36–39
Year published:
DOI:
doi:10.1038/nclimate2059
Received
Accepted
Published online

Despite more than two decades of diplomatic effort, concentrations of greenhouse gases continue to trend upwards, creating the risk that we may someday cross a threshold for ‘dangerous’ climate change1, 2, 3. Although climate thresholds are very uncertain, new research is trying to devise ‘early warning signals’ of an approaching tipping point4, 5, 6, 7, 8, 9, 10, 11. This research offers a tantalizing promise: whereas collective action fails when threshold uncertainty is large, reductions in this uncertainty may bring about the behavioural change needed to avert a climate ‘catastrophe’5. Here we present the results of an experiment, rooted in a game-theoretic model, showing that behaviour differs markedly either side of a dividing line for threshold uncertainty. On one side of the dividing line, where threshold uncertainty is relatively large, free riding proves irresistible and trust illusive, making it virtually inevitable that the tipping point will be crossed. On the other side, where threshold uncertainty is small, the incentive to coordinate is strong and trust more robust, often leading the players to avoid crossing the tipping point. Our results show that uncertainty must be reduced to this ‘good’ side of the dividing line to stimulate the behavioural shift needed to avoid ‘dangerous’ climate change.

At a glance

Figures

  1. Probability of catastrophe by treatment.
    Figure 1: Probability of catastrophe by treatment.

    In 150, catastrophe is avoided eight out of ten times. In 145/155, catastrophe is avoided four out of ten times with probability 100% and in the other six cases with probability between 30 and 80%. In 140/160 and 135/165, catastrophe is never avoided. In 100/200, catastrophe occurs nine out of ten times with probability 100% and once with probability 93%.

  2. Treatment means versus predicted values.
    Figure 2: Treatment means versus predicted values.

    Mean contributions are consistent with the predicted values to the left of the dividing line. To the right of the dividing line, mean contributions lie between the full cooperative and the predicted (non-cooperative) values. Mean proposals and mean pledges match the full cooperative values to the left of the dividing line; to the right, a wedge opens up between these values as the uncertainty range widens.

  3. Individual pledges and contributions by treatment.
    Figure 3: Individual pledges and contributions by treatment.

    To the left of the dividing line, pledges and contributions are tightly bunched, more so in 150 than in 145/155. To the right of the dividing line, in 140/160, 135/165 and 100/200, values vary widely, with contributions increasingly falling short of pledges with higher uncertainty. A series of Spearman’s correlation tests gives: n=100, ρ=0.38, p=0.00 in 150; ρ=0.59, p=0.00 in 145/155; ρ=0.33, p=0.00 in 140/160; ρ=−0.01, p=0.93 in 135/165; ρ=0.10, p=0.34 in 100/200. A small noise (2%) has been inserted to make all data points visible.

References

  1. Alley, R. B. et al. Abrupt climate change. Science 299, 20052010 (2003).
  2. Lenton, T. M. et al. Tipping elements in the earth’s climate system. Proc. Natl Acad. Sci. USA 105, 17861793 (2008).
  3. Kriegler, E., Hall, J. W., Held, H., Dawson, R. & Schellnhuber, H. J. Imprecise probability assessment of tipping points in the climate system. Proc. Natl Acad. Sci. USA 106, 50415046 (2009).
  4. Dakos, V. et al. Slowing down as an early warning signal for abrupt climate change. Proc. Natl Acad. Sci. USA 105, 1430814312 (2008).
  5. Biggs, R., Carpenter, S. R. & Brock, W. A. Turning back from the brink: Detecting an impending regime shift in time to avert it. Proc. Natl Acad. Sci. USA 106, 826831 (2009).
  6. Scheffer, M. Critical Transitions in Nature and Society (Princeton Univ. Press, 2009).
  7. Scheffer, M. et al. Early-warning signals for critical transitions. Nature 461, 5359 (2009).
  8. Ditlevsen, P. D. & Johnsen, S. J. Tipping points: Early warning and wishful thinking. Geophys. Res. Lett. 37, L19703 (2010).
  9. Lenton, T. M. Early warning of climate tipping points. Nature Clim. Change 1, 201209 (2011).
  10. Scheffer, M. et al. Anticipating critical transitions. Science 338, 344348 (2012).
  11. Lenton, T. M., Livina, V. N., Dakos, V., van Nes, E. H. & Scheffer, M. Early warning of climate tipping points from critical slowing down: Comparing methods to improve robustness. Phil. Trans. R. Soc. A. 370, 11851204 (2012).
  12. Carpenter, S. R. et al. Early warnings of regime shifts: A whole-ecosystem experiment. Science 332, 10791082 (2011).
  13. Wang, R. et al. Flickering gives early warning signals of a critical transition to a eutrophic lake state. Nature 492, 419422 (2012).
  14. Scheffer, M., Carpenter, S., Foley, J. A., Folke, C. & Walker, B. Catastrophic shifts in ecosystems. Nature 413, 591596 (2001).
  15. Dai, L., Vorselen, D., Korolev, K. S. & Gore, J. Generic indicators for loss of resilience before a tipping point leading to population collapse. Science 336, 11751177 (2012).
  16. May, R. M., Levin, S. A. & Sugihara, G. Complex systems: Ecology for bankers. Nature 451, 893895 (2008).
  17. Lackner, K. S. et al. The urgency of the development of CO2 capture from ambient air. Proc. Natl Acad. Sci. USA 109, 1315613162 (2012).
  18. Allen, M. R. et al. Warming caused by cumulative carbon emissions towards the trillionth tonne. Nature 458, 11631166 (2009).
  19. Zickfeld, K., Eby, M., Matthews, H. D. & Weaver, A. J. Setting cumulative emissions targets to reduce the risk of dangerous climate change. Proc. Natl Acad. Sci. USA 106, 1612916134 (2009).
  20. Barrett, S. Climate treaties and approaching catastrophes. J. Environ. Econ. Manage. 66, 235250 (2013).
  21. Barrett, S. & Dannenberg, A. Climate negotiations under scientific uncertainty. Proc. Natl Acad. Sci. USA 109, 1737217376 (2012).
  22. Ledyard, J. O. in Handbook of Experimental Economics (eds Kagel, J. H. & Roth, A. E.) 111194 (Princeton Univ. Press, 1995).
  23. Rockström, J. et al. A safe operating safe for humanity. Nature 461, 472475 (2009).
  24. Lenton, T.M. & Ciscar, J-C. Integrating tipping points into climate impact assessments. Climatic Change 117, 585597.
  25. Robinson, A., Calov, R. & Ganopolski, A. Multistability and critical thresholds of the Greenland ice sheet. Nature Clim. Change 2, 429432 (2012).
  26. Hawkins, E. et al. Bistability of the Atlantic overturning circulation in a global climate model and links to ocean freshwater transport. Geophys. Res. Lett. 38, L10605 (2011).
  27. Drijfhout, S.S., Weber, S.L. & van der Swaluw, E. The stability of the MOC as diagnosed from model projections for pre-industrial, present and future climates. Clim. Dynam. 37, 15751586 (2010).
  28. Hastings, A. & Wysham, D. B. Regime shifts in ecological systems can occur with no warning. Ecol. Lett. 13, 464472 (2010).
  29. Ostrom, E. Governing the Commons: The Evolution of Institutions for Collective Action (Cambridge Univ. Press, 1990).
  30. Barrett, S. Environment and Statecraft: The Strategy of Environmental Treaty-Making (Oxford Univ. Press, 2003).

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Affiliations

  1. Earth Institute and School of International and Public Affairs, Columbia University, New York, New York 10027, USA

    • Scott Barrett
  2. Princeton Institute for International and Regional Studies, Princeton University, Princeton, New Jersey 08544, USA

    • Scott Barrett
  3. Earth Institute, Columbia University, New York, New York 10027, USA

    • Astrid Dannenberg
  4. University of Gothenburg, Gothenburg 405 30, Sweden

    • Astrid Dannenberg

Contributions

S.B. and A.D. contributed equally to this work. They both designed and performed the research and analysed the data and wrote the paper.

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The authors declare no competing financial interests.

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