Experimental effects of climate messages vary geographically

  • Nature Climate Changevolume 8pages370374 (2018)
  • doi:10.1038/s41558-018-0122-0
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Social science scholars routinely evaluate the efficacy of diverse climate frames using local convenience or nationally representative samples1,2,3,4,5. For example, previous research has focused on communicating the scientific consensus on climate change, which has been identified as a ‘gateway’ cognition to other key beliefs about the issue6,7,8,9. Importantly, although these efforts reveal average public responsiveness to particular climate frames, they do not describe variation in message effectiveness at the spatial and political scales relevant for climate policymaking. Here we use a small-area estimation method to map geographical variation in public responsiveness to information about the scientific consensus as part of a large-scale randomized national experiment (n = 6,301). Our survey experiment finds that, on average, public perception of the consensus increases by 16 percentage points after message exposure. However, substantial spatial variation exists across the United States at state and local scales. Crucially, responsiveness is highest in more conservative parts of the country, leading to national convergence in perceptions of the climate science consensus across diverse political geographies. These findings not only advance a geographical understanding of how the public engages with information about scientific agreement, but will also prove useful for policymakers, practitioners and scientists engaged in climate change mitigation and adaptation.

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  1. 1.

    Nisbet, M. C. Communicating climate change: why frames matter for public engagement. Environment 51, 12–23 (2009).

  2. 2.

    Gifford, R. & Comeau, L. A. Message framing influences perceived climate change competence, engagement, and behavioral intentions. Glob. Environ. Change 21, 1301–1307 (2011).

  3. 3.

    Myers, T. A., Nisbet, M. C., Maibach, E. W. & Leiserowitz, A. A. A public health frame arouses hopeful emotions about climate change. Climatic Change 113, 1105–1112 (2012).

  4. 4.

    Wiest, S. L., Raymond, L. & Clawson, R. A. Framing, partisan predispositions, and public opinion on climate change. Glob. Environ. Change 31, 187–198 (2015).

  5. 5.

    Spence, A. & Pidgeon, N. Framing and communicating climate change: the effects of distance and outcome frame manipulations. Glob. Environ. Change 20, 656–667 (2010).

  6. 6.

    Lewandowsky, S., Gignac, G. E. & Vaughan, S. The pivotal role of perceived scientific consensus in acceptance of science. Nat. Clim. Change 3, 399–404 (2013).

  7. 7.

    van der Linden, S. L., Leiserowitz, A. A., Feinberg, G. D. & Maibach, E. W. The scientific consensus on climate change as a gateway belief: experimental evidence. PLoS ONE 10, e0118489 (2015).

  8. 8.

    Ding, D., Maibach, E. W., Zhao, X., Roser-Renouf, C. & Leiserowitz, A. Support for climate policy and societal action are linked to perceptions about scientific agreement. Nat. Clim. Change 1, 462–466 (2011).

  9. 9.

    McCright, A. M., Dunlap, R. E. & Xiao, C. Perceived scientific agreement and support for government action on climate change in the USA. Climatic Change 119, 511–518 (2013).

  10. 10.

    Oreskes, N. The scientific consensus on climate change. Science 306, 1686 (2004).

  11. 11.

    Doran, P. T. & Zimmerman, M. K. Examining the scientific consensus on climate change. Eos 90, 22–23 (2009).

  12. 12.

    IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  13. 13.

    Anderegg, W. R., Prall, J. W., Harold, J. & Schneider, S. H. Expert credibility in climate change. Proc. Natl Acad. Sci. USA 107, 12107–12109 (2010).

  14. 14.

    Cook, J. et al. Consensus on consensus: a synthesis of consensus estimates on human-caused global warming. Environ. Res. Lett. 11, 048002 (2016).

  15. 15.

    Leiserowitz, A, Maibach, E, Roser-Renouf, C, Feinberg, G. & Rosenthal, S. Climate Change in the American Mind: March, 2016 (Yale Univ. and George Mason Univ., New Haven, 2016).

  16. 16.

    Oreskes, N. & Conway, E. M. Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming (Bloomsbury, New York, 2011).

  17. 17.

    Boykoff, M. T. & Boykoff, J. M. Balance as bias: global warming and the US prestige press. Glob. Environ. Change 14, 125–136 (2004).

  18. 18.

    Freudenburg, W. R. & Muselli, V. Global warming estimates, media expectations, and the asymmetry of scientific challenge. Glob. Environ. Change 20, 483–491 (2010).

  19. 19.

    McCright, A. M. & Dunlap, R. E. Anti-reflexivity the American conservative movement’s success in undermining climate science and policy. Theory Cult. Soc. 27, 100–133 (2010).

  20. 20.

    Hmielowski, J. D., Feldman, L., Myers, T. A., Leiserowitz, A. & Maibach, E. An attack on science? Media use, trust in scientists, and perceptions of global warming. Public Underst. Sci. 23, 866–883 (2013).

  21. 21.

    Koehler, D. J. Can journalistic "false balance" distort public perception of consensus in expert opinion?. J. Exp. Psychol. Appl. 22, 24–38 (2016).

  22. 22.

    van der Linden, S., Leiserowitz, A., Rosenthal, S. & Maibach, E. Inoculating the public against misinformation about climate change. Global Chall. 1, 1600008 (2017).

  23. 23.

    Aklin, M. & Urpelainen, J. Perceptions of scientific dissent undermine public support for environmental policy. Environ. Sci. Policy 38, 173–177 (2014).

  24. 24.

    Van der Linden, S. L., Clarke, C. E. & Maibach, E. W. Highlighting consensus among medical scientists increases public support for vaccines: evidence from a randomized experiment. BMC Public Health 15, 1207 (2015).

  25. 25.

    Dixon, G. Applying the gateway belief model to genetically modified food perceptions: new insights and additional questions. J. Commun. 66, 888–908 (2016).

  26. 26.

    McCright, A. M. & Dunlap, R. E. The politicization of climate change and polarization in the American public’s views of global warming, 2001–2010. Sociol. Q. 52, 155–194 (2011).

  27. 27.

    Bolsen, T. & Druckman, J. N. Counteracting the politicization of science. J. Commun. 65, 745–769 (2015).

  28. 28.

    Kahan, D. M., Jenkins-Smith, H. & Braman, D. Cultural cognition of scientific consensus. J. Risk Res. 14, 147–174 (2011).

  29. 29.

    Corner, A. & Clarke, J. Talking Climate: From Research to Practice in Public Engagement (Springer, London, 2016).

  30. 30.

    Hill, J. L. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20, 217–240 (2011).

  31. 31.

    Green, D. P. & Kern, H. L. Modeling heterogeneous treatment effects in survey experiments with Bayesian additive regression trees. Public Opin. Q. 76, 491–511 (2012).

  32. 32.

    Wager, S. & Athey, S. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. https://doi.org/10.1080/01621459.2017.1319839 (2017).

  33. 33.

    Athey, S. & Imbens, G. Recursive partitioning for heterogeneous causal effects. Proc. Natl. Acad. Sci. USA 113, 7353–7360 (2015).

  34. 34.

    Rentfrow, P. J., Gosling, S. D. & Potter, J. A theory of the emergence, persistence, and expression of geographic variation in psychological characteristics. Perspect. Psychol. Sci. 3, 339–369 (2008).

  35. 35.

    Rentfrow, P. J. Geographical Psychology: Exploring the Interaction of Environment and Behavior (American Psychological Association, Washington, DC, 2014).

  36. 36.

    Motyl, M., Iyer, R., Oishi, S., Trawalter, S. & Nosek, B. A. How ideological migration geographically segregates groups. J. Exp. Soc. Psychol. 51, 1–14 (2014).

  37. 37.

    Howe, P. D., Mildenberger, M., Marlon, J. R. & Leiserowitz, A. Geographic variation in opinions on climate change at state and local scales in the USA. Nat. Clim. Change 5, 596–603 (2015).

  38. 38.

    Mildenberger, M. et al. The distribution of climate change public opinions in Canada. PLoS ONE 11, e0159774 (2016).

  39. 39.

    Mildenberger, M., Marlon, J. R., Howe, P. D. & Leiserowitz, A. The spatial distribution of Republican and Democratic climate opinions at state and local scales. Climatic Change 145, 539–548 (2017).

  40. 40.

    Lax, J. R. & Phillips, J. H. Gay rights in the States: public opinion and policy responsiveness. Am. Polit. Sci. Rev. 103, 367–386 (2009).

  41. 41.

    Lax, J. R. & Phillips, J. H. The democratic deficit in the States. Am. J. Pol. Sci. 56, 148–166 (2012).

  42. 42.

    Cook, J., Lewandowsky, S. & Ecker, U. K. Neutralizing misinformation through inoculation: exposing misleading argumentation techniques reduces their influence. PLoS ONE 12, e0175799 (2017).

  43. 43.

    van der Linden, S., Leiserowitz, A. & Maibach, E. Scientific agreement can neutralize politicization of facts. Nat. Hum. Behav. 2, 2–3 (2018).

  44. 44.

    Bolsen, T., Druckman, J. N. & Cook, F. L. The influence of partisan motivated reasoning on public opinion. Polit. Behav. 36, 235–262 (2014).

  45. 45.

    Krosnick, J. & MacInnis, B. in Social Psychology and Politics (eds Forgas, J. P. et al.) 75–90 (Psychology Press, New York, 2015).

  46. 46.

    Jost, J. T., van der Linden, S., Panagopoulos, C. & Hardin, C. D. Ideological asymmetries in conformity, desire for shared reality, and the spread of misinformation. Curr. Opin. Psychol. 23, 77–83 (2018).

  47. 47.

    Rentfrow, P. J. Statewide differences in personality: toward a psychological geography of the United States. Am. Psychol. 65, 548–558 (2010).

  48. 48.

    Gerber, A. S., Huber, G. A., Doherty, D., Dowling, C. M. & Ha, S. E. Personality and political attitudes: relationships across issue domains and political contexts. Am. Polit. Sci. Rev. 104, 111–133 (2010).

  49. 49.

    Greenland, S. Principles of multilevel modelling. Int. J. Epidemiol. 29, 158–167 (2000).

  50. 50.

    Pacheco, J. Using national surveys to measure dynamic U.S. state public opinion: a guideline for scholars and an application. State Polit. Policy Q. 11, 415–439 (2011).

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Author information


  1. Department of Political Science, Yale University, New Haven, CT, USA

    • Baobao Zhang
  2. Department of Psychology, University of Cambridge, Cambridge, UK

    • Sander van der Linden
  3. Department of Political Science, University of California Santa Barbara, Santa Barbara, CA, USA

    • Matto Mildenberger
  4. School of Forestry & Environmental Studies, Yale University, New Haven, CT, USA

    • Jennifer R. Marlon
    •  & Anthony Leiserowitz
  5. Department of Environment and Society, Utah State University, Logan, UT, USA

    • Peter D. Howe


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B.Z., M.M., P.D.H. and J.R.M. developed and implemented the model. S.v.d.L. and A.L. collected the data and designed the national experiment and survey with input from all authors. B.Z., S.v.d.L. and M.M. drafted a first version of the manuscript. P.D.H., J.R.M. and A.L. all provided critical input to the writing and results and approved the final version of the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Baobao Zhang.

Supplementary information

  1. Supplementary Information

    Supplementary Tables 1–3, Supplementary Figures 1–7 and Supplementary References