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Unintended consequences of using maps to communicate sea-level rise

Nature Sustainability (2024)Cite this article

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Abstract

Sea-level rise caused by climate change poses enormous social and economic costs, yet governments and coastal residents are still not taking the mitigation and adaptation steps necessary to protect their communities and property. In response, advocates have attempted to raise threat salience by disseminating maps of projected sea-level rise. We test the efficacy of this ubiquitous communication tool using two high spatial-resolution survey experiments (n = 1,243). Our first experiment, in US coastal communities across four US states, exposes households on either side of projected sea-level rise boundaries to individually tailored risk maps. We find this common risk communication approach has the unintended consequence of reducing concern about future sea-level rise, even among households projected to experience flooding this century. In a second experiment on our sample (n = 737) of San Francisco Bay Area coastal residents, direct communications about impacts on traffic patterns does increase concern about future climate impacts. Map-based risk information increases support for collective spending on climate adaptation, but it does not increase individual intentions to contribute. Our results demonstrate the importance of empirically testing messaging campaigns for climate adaptation.

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Fig. 1: Respondents believe SLR is a threat to others, not themselves, even when they live in a projected SLR zone.
Fig. 2: Example maps shown to treated respondents just outside or just inside the projected SLR boundary zone.
Fig. 3: SLR maps reduce perceptions that SLR will harm respondents, regardless of whether home is located inside or outside the projected flood zone.
Fig. 4: Effect of map treatment does not vary significantly around SLR cut point.
Fig. 5: SLR maps increase support for select adaptation policies among respondents projected to experience flooding.
Fig. 6: Information about projected traffic delays due to SLR increases perceived personal risks, perceived risk to distant groups and support for flood controls.

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Data availability

The underlying data used in this article have been deposited in a Harvard Dataverse repository at https://doi.org/10.7910/DVN/1QCDCG.

Code availability

The code and replication scripts necessary to generate the figures, tables and analysis reported has been deposited in a Harvard Dataverse repository at https://doi.org/10.7910/DVN/1QCDCG.

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Acknowledgements

We acknowledge seminar participants at the University of Pennsylvania, the University of California Santa Barbara and Rutgers University and the American Shore and Beach Preservation Associate Annual Conference for feedback on earlier drafts of this paper. This project was funded, in part, by the US Coastal Research Program (USCRP) contract W912HZ-18-C-0031 (M.M., J.R.M.) as administered by the US Army Corps of Engineers (USACE), Department of Defense. The content of the information provided in this publication does not necessarily reflect the position or the policy of the government, and no official endorsement should be inferred. The authors acknowledge the USACE and USCRP’s support of their effort to strengthen coastal academic programmes and address coastal community needs in the United States.

Author information

Authors and Affiliations

  1. Department of Political Science, University of California, Santa Barbara, CA, USA

    Matto Mildenberger

  2. Department of Political Science, University of North Carolina, Chapel Hill, NC, USA

    Alexander Sahn

  3. Public Sector Consulting, Gallup, Santa Barbara, CA, USA

    Chris Miljanich

  4. Department of Civil Engineering, University of Texas, Arlington, TX, USA

    Michelle A. Hummel

  5. Department of Environmental Science and Policy, University of California, Davis, CA, USA

    Mark Lubell

  6. School of the Environment, Yale University, New Haven, CT, USA

    Jennifer R. Marlon

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Contributions

M.M. participated in all stages of this study, including design, data collection, analysis and writing. A.S. participated in analysis and writing. J.R.M. and M.A.H. participated in design and writing. C.M. participated in data collection. M.L. participated in design.

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Correspondence to Matto Mildenberger.

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Competing interests

The authors declare no competing interests.

Ethics statement

This study was reviewed and approved by the University of California Office of Research as Protocol 15-19-0108. Respondent participation in our survey was voluntary, and respondents provided informed consent before taking the survey.

Peer review

Peer review information

Nature Sustainability thanks Tracy Kijewski-Correa, Craig Landry and Aaron Sparks for their contribution to the peer review of this work.

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Sea-level rise maps decrease personal concern for residents of all states; only FL and NJ residents decrease concern for local community and distant groups.

Figure shows treatment effects of being shown an individually-tailored sea-level rise map, including an indicator for the respondent’s house, on the threat that sea-level rise poses to diverse categories of people, for respondents in four sample states. Bars show 95% confidence intervals. Respondents whose addresses are projected to experience flooding under a 1-m sea-level rise scenario are labeled as ‘Live Within SLR Zone’. Respondents whose addresses are projected to remain outside the sea-level rise zone under a 1 m sea-level rise scenario are listed as: ‘Live Outside of SLR Zone’. Points show regression coefficient and line segments show 95% confidence intervals, computed with HC1 standard errors. CA n = 737; FL n = 116; NJ n = 177; VA n = 212.

Extended Data Fig. 2 Sea-level rise maps decrease personal concern for residents of CA only.

Figure shows treatment effects of being shown an individually-tailored sea-level rise map, including an indicator for the respondent’s house, on the threat that sea-level rise poses to diverse categories of people, for respondents in four sample states. Bars show 95% confidence intervals. Respondents whose addresses are projected to experience flooding under a 1 m sea-level rise scenario are labeled as ‘Live Within SLR Zone’. Respondents whose addresses are projected to remain outside the sea-level rise zone under a 1 m sea-level rise scenario are listed as: ‘Live Outside of SLR Zone’ (n = 737).

Extended Data Fig. 3 Linear Decline in Support for Policies Does Not Vary by Treatment Conditions.

Figure shows slopes on willingness to pay for climate policies under different treatment conditions in map (CA, FL, NJ, VA) and traffic (CA only) experiments. Slopes are calculated by regressing policy support on randomly varied price of policy. Bars show 95% confidence intervals. Regressions include fixed effect for policy outcome. Respondents whose addresses are projected experience flooding under a 1 m sea-level rise scenario are labeled as ‘Live Within SLR Zone’. Respondents whose addresses are projected to remain outside the sea-level rise zone under a 1 m sea-level rise scenario are listed as: ‘Live Outside of SLR Zone.’ Treatment respondents are shown a map; control respondents are not. For traffic experiment, control respondents are not shown traffic vignette; treatment respondents are shown vignette and are here split into respondents whose treatment was below and above the median traffic increase time of 15 minutes (Map experiment n = 1,243. Traffic experiment n = 737).

Extended Data Fig. 4 Linear Decline in Support Does Not Vary by Policy.

Figure shows slopes on willingness to pay for four climate policies. Sample is pooled across all four study sites. Slopes are calculated by regressing policy support on randomly varied price of policy. Bars show 95% confidence intervals (n = 1,243).

Extended Data Fig. 5 Sea-level rise maps decrease personal concern for Democrats and Republicans equally; only Republicans decrease concern for local community and distant groups.

Figure shows treatment effects of being shown an individually-tailored sea-level rise map, including an indicator for the respondent’s house, on the threat that sea-level rise poses to diverse categories of people, for self-identified Democrats and Republicans (including leaners), and pure Independents. Bars show 95% confidence intervals. All regressions contain fixed effects for location (CA, FL, NJ, VA). Policy support is measured on a 7-point scale. Respondents whose addresses are projected to experience flooding under a 1 m sea-level rise scenario are labeled as ‘Live Within SLR Zone’. Respondents whose addresses are projected to remain outside the sea-level rise zone under a 1 m sea-level rise scenario are listed as: ‘Live Outside of SLR Zone’. The United States, developing countries, and future generations are collapsed into ‘Distant Groups.’ (Democrats n = 667; Republicans n = 238; Independents n = 192).

Extended Data Fig. 6 Sea-level rise maps decrease personal concern for those who do believe in human activity causing global warming.

Figure shows treatment effects of being shown an individually-tailored sea-level rise map, including an indicator for the respondent’s house, on the threat that sea-level rise poses to diverse categories of people, for respondents who believe in human-caused climate change, and those who either do not believe the planet is warming or that it is not human-caused. Bars show 95% confidence intervals. Respondents whose addresses are projected to experience flooding under a 1 m sea-level rise scenario are labeled as ‘Live Within SLR Zone’. Respondents whose addresses are projected to remain outside the sea-level rise zone under a 1 m sea-level rise scenario are listed as: ‘Live Outside of SLR Zone’ (Human Activity n = 925; No GW n = 317).

Extended Data Fig. 7 Sea-level rise maps decrease personal concern for homeowners and renters equally; only renters decrease their sense of harm to local community.

Figure shows treatment effects of being shown an individually-tailored sea-level rise map, including an indicator for the respondent’s house, on the threat that sea-level rise poses to diverse categories of people, for self-identified homeowners and renters. Bars show 95% confidence intervals. Results pool CA, NJ, FL, and VA respondents. Respondents whose addresses are projected to experience flooding under a 1 m sea-level rise scenario are labeled as ‘Live Within SLR Zone’. Respondents whose addresses are projected to remain outside the sea-level rise zone under a 1 m sea-level rise scenario are listed as: ‘Live Outside of SLR Zone’ (Own n = 970; Rent n = 191).

Extended Data Fig. 8 Homeowners increase perceived concern when shown traffic information; renters do not.

Figure shows treatment effects of projected 1 minute increase in zipcode-level traffic due to SLR for 5 separate regressions of traffic treatment on levels of perceived harm (4-point scale). Points show regression coefficient and line segments show 95% confidence intervals, computed with robust standard errors. Regressions control for whether respondents received map treatment. Sample includes only California respondents (Own n = 290; Rent n = 98.).

Extended Data Fig. 9 Sea-level rise maps decrease personal concern for residents of high-risk and moderate risk flood zones.

Figure shows treatment effects of being shown an individually-tailored sea-level rise map, including an indicator for the respondent’s house, on the threat that sea-level rise poses to residents of homes in AE (high risk) and X (moderate risk) flood zones. Figure pools respondents from CA, FL, NJ and VA and includes state fixed effects. Respondents whose addresses are projected to experience flooding under a 1 m sea-level rise scenario are labeled as ‘Live Within SLR Zone’. Respondents whose addresses are projected to remain outside the sea-level rise zone under a 1 m sea-level rise scenario are listed as: ‘Live Outside of SLR Zone.’ Points show regression coefficient and line segments show 95% confidence intervals, computed with HC1 standard errors. AE n = 272; X n = 744.

Extended Data Table 1 Respondents on Either Side of Sea Level Rise Boundary Similar on Observed Characteristics; Whites, College Graduates, Homeowners Overrepresented in Sample Relative to Population
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Mildenberger, M., Sahn, A., Miljanich, C. et al. Unintended consequences of using maps to communicate sea-level rise. Nat Sustain (2024). https://doi.org/10.1038/s41893-024-01380-0

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