ARTICLE
https://doi.org/10.1038/s43247-023-00703-x OPEN
Global survey shows planners use widely varying
sea-level rise projections for coastal adaptation
Daniella Hirschfeld 1✉, David Behar2, Robert J. Nicholls 3, Niamh Cahill 4,5, Thomas James 6,
Benjamin P. Horton 7,8, Michelle E. Portman9, Rob Bell 10,11, Matthew Campo 12, Miguel Esteban 13,
Bronwyn Goble14, Munsur Rahman15, Kwasi Appeaning Addo 16, Faiz Ahmed Chundeli 17,
Monique Aunger18, Orly Babitsky9, Anders Beal19, Ray Boyle20, Jiayi Fang 21, Amir Gohar22,
Susan Hanson 3,23, Saul Karamesines1, M. J. Kim 24, Hilary Lohmann25, Kathy McInnes 26,
Nobuo Mimura 27, Doug Ramsay28, Landis Wenger1 & Hiromune Yokoki29
Including sea-level rise (SLR) projections in planning and implementing coastal adaptation is
crucial. Here we analyze the first global survey on the use of SLR projections for 2050 and
2100. Two-hundred and fifty-three coastal practitioners engaged in adaptation/planning from
49 countries provided complete answers to the survey which was distributed in nine lan-
guages – Arabic, Chinese, English, French, Hebrew, Japanese, Korean, Portuguese and
Spanish. While recognition of the threat of SLR is almost universal, only 72% of respondents
currently utilize SLR projections. Generally, developing countries have lower levels of utili-
zation. There is no global standard in the use of SLR projections: for locations using a
standard data structure, 53% are planning using a single projection, while the remainder are
using multiple projections, with 13% considering a low-probability high-end scenario.
Countries with histories of adaptation and consistent national support show greater assim-
ilation of SLR projections into adaptation decisions. This research provides new insights about
current planning practices and can inform important ongoing efforts on the application of the
science that is essential to the promotion of effective adaptation.
1 Department of Landscape Architecture and Environmental Planning, Utah State University, 4005 Old Main Hill, Logan, UT 84322-4005, USA. 2 San
Francisco Public Utilities Commission, San Francisco, CA, USA. 3 Tyndall Centre for Climate Change Research, University of East Anglia, Norwich, UK.
4Department of Mathematics and Statistics, National University of Ireland, Maynooth, Ireland. 5 Irish Climate Analysis and Research UnitS (ICARUS),
Maynooth University, Kildare, Ireland. 6Geological Survey of Canada, Natural Resources Canada, Victoria, Canada. 7 Earth Observatory of Singapore,
Nanyang Technological University, Singapore, Singapore. 8 Asian School of the Environment, Nanyang Technological University, Singapore, Singapore.
9MarCoast Ecosystems Integration Lab, Technion – Israel Institute of Technology, Haifa 32000, Israel. 10 Bell Adapt Ltd, Hamilton 3210, New Zealand.
11 Environmental Planning Programme, School of Social Sciences, University of Waikato, Te Whare Wananga o Waikato, Hamilton, New Zealand. 12 Edward J.
Bloustein School of Planning & Public Policy, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA. 13 Department of Civil and Environmental
Engineering, Waseda University, Tokyo, Japan. 14 The Oceanographic Research Institute, Durban, South Africa. 15 Institute of Water and Flood Management
(IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh. 16 University of Ghana, Accra, Ghana. 17 School of Planning
and Architecture, Vijayawada, Andhra Pradesh, India. 18 Geological Survey of Canada, Lands and Minerals Sector, Natural Resources Canada 601 Booth
Street, Ottawa, ON, Canada. 19Woodrow Wilson International Center for Scholars, Washington, DC, USA. 20 College of Environmental Design, University of
California Berkeley, Berkeley California, USA. 21 Institute of Remote Sensing and Earth Sciences, School of Information Science and Technology, Hangzhou
Normal University, Hangzhou 311121, China. 22 University of the West of England, Bristol, UK. 23 Faculty of Engineering and Physical Sciences, University of
Southampton, Boldrewood Campus, Burgess Road, Southampton, UK. 24Ministry of Oceans and Fisheries affairs, Busan, Republic of Korea. 25Department of
Planning and Natural Resources, St. Croix, USVI, USA. 26 Climate Change Research Centre, UNSW Australia, Sydney, NSW, Australia. 27Global and Local
Environment Co-creation Institute, Ibaraki University, Ibaraki, Japan. 28 National Institute for Water and Atmospheric Research, Auckland, New Zealand.
29Department of Civil, Architectural, and Environmental Engineering, Ibaraki University, Ibaraki, Japan. ✉email: Daniella.hirschfeld@usu.edu
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The appropriate use of sea-level rise (SLR) projections in under their jurisdiction, the science behind SLR projections usedcoastal decision-making is critical but challenging. The in policy, and how practitioners apply SLR projections. Throughscenarios used and their application will have profound quantitative and qualitative analyses, we found spatial relation-
impacts on our social, ecological, and economic coastal ships between global coastal regions and the degree of use of sea-
systems1–3. Hundreds of millions of people currently living in level science in plans. We found surprisingly that most coastal
coastal zones face significant risks due to SLR, and the imple- managers are using a single SLR projection rather than con-
mentation of proactive adaptation measures would be prudent4. sidering a range of possible SLR values to account for uncertainty.
Coastal ecosystems are already under stress from ocean warming, We also learned that a wide range of future projections are in use
acidification, and SLR, compounded by human interventions, and revealing that there is no globally standardized approach to
expected responses over this century include habitat contractions, selecting and using SLR projections.
translocation, and loss of biodiversity and functionality5. Recent
estimates suggest that coastal adaptation costs for the developing
world will range from $26–89 billion a year by 2040 s6. Hence, the Results
SLR scenarios used by decision-makers have substantial cost and Uneven distribution of the application of sea-level science. We
risk implications, with the danger of overinvestment for unne- gained important insights at the global, continental, regional, and
cessary protection7 or underinvestment, leading to escalating country scales about whether and to what degree coastal man-
inundation risk and emergency response challenges for vulner- agers are using SLR projections in their coastal planning.
able communities8,9. Working closely with partners and using a snowball sampling
Sea-level science is a well-developed field of study with decades approach42 253 coastal managers completed our questionnaire.
of scientific experience with increasing sophistication and new This sample represents the first global data collection on SLR use
modeling platforms providing a deeper understanding of future in decision making43 (Supplementary Table 1, Supplementary
sea levels and associated uncertainties2,10. The Intergovernmental Table 2 and Supplementary Fig. 1). Our respondents all identified
Panel on Climate Change (IPCC) has released six major assess- as planners working primarily (89%) for local governments (e.g.,
ments, based on an extensive body of literature2,11. Researchers cities, councils, municipalities, towns, and native settlements) and
have broadened work from a focus on median SLR estimates to sub-national governments (e.g., districts, provinces, regions,
the consideration of high-end SLR scenarios, including increasing states, and territories). Our analysis focuses on the information
frequency of flooding, changing storm events, and waves, to provided by our respondents about the use of sea-level science,
capture the widening uncertainty2,11–15. Global emissions in the not on the number of respondents per region. The distribution of
coming decades and the sensitivity and tipping points of various responses in our samples, however, is clearly geographically
SLR components drive uncertainty in projections, especially for uneven, which contributes to the fact that we did not note a
the Greenland and Antarctic ice sheets16–18. This widening strong correlation between the use of future sea levels in planning
uncertainty challenges decision analysis14,19. Assimilation by and country-level covariates including GDP, education levels, and
practitioners, managers, and decision-makers of long-term SLR the human development index. That is not to say that no rela-
requires recognition and a clear understanding of the range of tionship exists but rather that further research with a different
uncertainties and how they can be articulated in planning20–22. sampling approach and a greater number of respondents could
Coastal and estuarine environments are highly dynamic, and better explore such relationships.
communities living within them have a long history of We found that 181 (72%) respondents are in Group 1, defined
adaptation23,24. Formal efforts to build a shared body of knowl- as having formally adopted guidance materials, reports, or policy
edge including frameworks to address SLR adaptation began with documents that include SLR projections in their coastal planning
the first IPCC assessment and associated guidance in the processes. This group represents areas with nearly half of the
1990s25–30. Regional and local efforts to plan for future climatic world’s coastal population. We also found that 67 (26%)
conditions and implement adaptation measures have been respondents are in Group 2 and are trying to use SLR projections;
undertaken by coastal managers for the last two decades and however, they do not have a formal policy in place yet. Finally,
these efforts are still growing31–33. Increasing knowledge34, public only 5 respondents (2%) are in Group 3 defined as not currently
awareness, and programs to facilitate and promote adaptation35 working with SLR projections in their planning (Supplementary
in some places puts pressure on decision-makers to incorporate Table 3), possibly reflecting in part the non-response of planners
sea-level science into planning efforts and guidance23,36,37. who are not considering SLR to a questionnaire focusing on SLR.
Successful coastal adaptation requires robust science-policy At the continental scale (Fig. 1A and Supplementary Table 4),
integration and well-designed climate services, both built on we found that Europe, Australia/Oceania, and North America
ensuring the usability of scientific information38,39. Building and were the continents with the largest proportions of respondents
designing these systems requires an understanding of how to make using SLR projections in planning. Respectively, they had 87%
science-based decisions in the context of increasing uncertainties (N= 31), 84% (N= 44) and 77% (N= 126) of their respondents
in SLR over time. With a few exceptions40,41, there has been little in Group 1. The continents with the lowest percentages of
assessment of adaptation practice in coastal areas, especially of the respondents in Group 1 are Asia and South America (36%
sea-level scenarios used by practitioners to inform the science- (N= 39) and 33% (N= 3), respectively). Africa is intermediate,
policy interface. Assessment of sea-level adaptation practices and with 50% (N= 10) of respondents in Group 1. Regionally (Fig. 1B
accompanying scenarios will inform the future development of and Supplementary Table 4), we observe important differences
sea-level science and would be accompanied by an improved within continents. In Europe we found that North and West
understanding of how to translate uncertainty in sea-level pro- Europe have 95% (N= 20) of their respondents in Group 1,
jections into the decision environment. compared to only 50% (N= 6) in Southern Europe (Northern
Here we distributed the first global survey on this topic via a Mediterranean). Continentally aggregated data obscures the
confidential questionnaire to coastal practitioners in every North America dichotomy between the United States, where
inhabited continent; we provided the questionnaire in English 80% (N= 95) of respondents are in Group 1, and the Caribbean
and translated it into eight additional languages. The ques- Islands, where only 20% (N= 5) are in Group 1.
tionnaire asked for specific time horizons and projection infor- We found that certain countries are particularly high users
mation currently used in coastal planning materials for areas of SLR projections in their coastal planning processes
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Fig. 1 Study scope and use of sea-level rise projections in planning. Percent of respondents by continent (A) and coastal region (B) who are using sea-level
rise in coastal planning processes and the countries (in gray) that provided responses. See Supplementary Table 2 for a list and details of coastal regions.
(Supplementary Table 4), such as New Zealand (90% of a firm guidance to local governments when they revise the basic
respondents, N= 10). This reflects the availability of SLR plan for coastal protection and land use. Other places, such as
scenarios in clearly articulated guidance for practitioner use Western Africa, where none of our respondents said that SLR is
created at the national level37. In another example, we found that part of planning, could be hindered by a lack of capacity for long-
in the United Kingdom, which has a long history of including term planning (e.g., 2100 and beyond) and rather focus on the
relative SLR in infrastructure design pre-dating climate change near term (i.e., next 10–20 years). These findings suggest that lack
concerns (e.g., Gilbert & Horner44, 1984), 100% of respondents of capacity and competing priorities could both be playing a role
(N= 8) use SLR projections in their planning processes. We infer in areas with limited use of future SLR projections.
from these examples that robust national guidance and a longer
history of SLR integration in planning contribute to the ongoing The data structures used by planners to depict sea-level rise
use of SLR projections in current coastal planning. futures. We asked coastal managers if SLR projections fell under
In contrast, we found certain regions and countries to have a four formal data structures (A, B, C, D) for both 2050 and 2100.
low use of SLR projections (Supplementary Table 4). Japan, where Of the 143 respondents (56% of the original sample) that indi-
80% of respondents (N= 5) reported not using SLR projections cated use of these formal structures, the most common structure
in planning has an extreme tsunami risk as demonstrated in (A) is a singular estimate, which is used by 76 (53.1%) respon-
201145. This extreme risk and recent experience, including dents (Fig. 2). A low, intermediate, and high estimate was the
rebuilding and adapting to tsunami risk, may overpower concerns second most common structure (C) used by 28 (19.6%) respon-
about smaller SLR projections of between 1 and 2 meters. dents, while 20 (14.0%) respondents used a low and high estimate
However, tsunami risk greatly increases with SLR and therefore (B). The least common structure (D), with 19 (13.3%) respon-
SLR ought not to be ignored46. Note that coastal management dents, was the structure with a low, intermediate, high, and high-
policies change over time. Japan’s coastal management policy has end estimate. The latter was defined as the highest future sea-level
changed since the survey for this study was performed. The estimate based on extreme but plausible information, which in
Ministry of Land, Infrastructure, Transport, and Tourism revised some jurisdictions is referred to as H++47. In addition to these
the Basic Policy for Coastal Conservation under the Coastal Act four common structures, forty respondents (16.0% of the original
in November 2020 to incorporate SLR. The new Basic Policy gives sample), are using unique structures tailored to their locations.
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Fig. 2 Structures of sea-level rise projections used globally. Respondents formally structure the use of sea-level rise projections for planning purposes in
four ways: A is a singular estimate, B is a low and a high estimate, C is a low, intermediate, and high estimate, and D is a low, intermediate, high, and high-
end estimate. Shown are aggregated responses for five distinct geographical regions and the globe.
Notably, of the respondents that rely on these formal We observe an interesting difference between Canada and the
structures, Structure A is used by the majority on every continent. USA. In Canada 16 places (84%) are using a single future estimate
Not all 143 respondents that use the formal structures gave a (A) and 3 places (16%) are using low, intermediate, and high (C)
projection for 2100. The total in 2100= 135 (which is what the SLR projections. Conversely, in the United States, there is a much
numbers in Supplementary Table 5 sum to). In Oceania, Asia, wider range of approaches: 14 places (24%) are using a single
and Africa Structure A is used by 78.6%, 72.7%, and 66.7%, future estimate (A), 11 places (19%) are using a low and high
respectively. This finding contrasts both with some guidance on estimate (B), 16 places (28%) are using a low, intermediate, and
planning for future SLR14,19,37,48,49 and with the work of the high estimates (C), and 17 places (29%) are using a low,
scientific community to refine and clarify the range of future sea intermediate, high, and high-end estimate (D). This difference is
levels and associated uncertainties2. However, a single number is likely the result of national and regional guidance that emphasizes
eventually needed in many contexts, especially by engineers or de-emphasizes high-end estimates. For example, the State of
designing coastal infrastructure. This number should arise out of California explicitly calls attention to the H++ scenario of 3
careful consideration of a range of projections during the asset life meters in 2100 and recommends its use in extreme risk-averse
cycle including high-end estimates for risk-averse decisions50 and decision contexts53. In contrast, British Columbia, where the
timing windows to exceed design thresholds51. We recognize that majority of Canadian respondents work, recommends considera-
the use case52 of our respondents would shed further light on the tion of 1 meter of sea-level rise at 2100 and 2 meters at 2200,
structures and selected projections. In our study, we find that adjusted for vertical land motion54.
respondents are applying the structures and the projections in
many use cases (Supplementary Fig. 2). We also find that our
respondents rely on many criteria to determine the right No global standard. Our findings indicate that a wide range of
projections for their land-use (Supplementary Fig. 3) and future projections are used by coastal managers to plan for SLR in
infrastructure planning (Supplementary Fig. 4). Thus, we are both 2050 (Supplementary Fig 6 and Supplementary Table 5) and
not able to discern a relationship between the application type 2100 (Fig. 3 and Supplementary Table 5). Here we focus on the sea-
and the projections or structures used. level rise projections for 2100 used by 135 respondents in the four
Some coastal managers in the United States, Northern/ scenario structures defined above. We report numbers rounded to
Western Europe, New Zealand/Australia, and Northern Africa the nearest centimeter. The Supplementary Tables provide more
are using a high-end SLR scenario (Structure D) (Supplementary precise numbers. For Structure A (N= 71) the median is 0.90m,
Fig. 5). No other coastal regions in our sample are using this with a minimum of 0 m in eight locations globally and a maximum
structure. The United States has the greatest use of high-end SLR of 2.03m in Hayward, California in the United States. For Structure
scenarios, with 17 locations across the country using this type of B (N= 19) the median low value is 0.61 m and the median high
scenario. The use of high-end SLR scenarios in plans provides an value is 1.40m. For Structure C (N= 26) the median low value is
opportunity to understand the uncertainty, consider plausible 0.42 m, the median intermediate value is 0.71m, and the median
high-end scenarios, and stress-test long-term adaptation options high value is 1.21 m. For the 19 respondents using Structure D the
to better bracket and plan adaptation and avoid maladaptation11. median low value is 0.53m, the median intermediate value is
Conversely, adoption of this extreme value in planning can lead 1.19 m, the median high value is 1.91 m, and the median high-end
the public and policy makers to mistakenly anticipate more value is 3.05m.We observe that the values for those using Structure
expensive and socially disruptive adaptation measures than may A cover almost the full range of values from structures B and C,
be necessary37,41,48. To navigate these advantages and disadvan- indicating that this approach is not limited to median or low-end
tages to high-end SLR use, practitioners would benefit from more estimates. Finally, we did not find a robust statistical difference
guidance concerning the use of high-end scenarios (see van de between the structure used and median projections; however, those
Wal, et al. 202250). using Structure D do have a higher median for their high estimate
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Fig. 3 Comparison of sea-level rise projections in planning and available science. Left: The SLR projections (in meters) for 2100, which respondents use
in their coastal plans and guidance documents. Projections are grouped by the four projection structures (A to D) shown in Fig. 2 and shown as box plots
with median values as the dark center line, the box representing the 25th to 75th percentiles, and the whiskers showing the full range of survey responses.
Right: The IPCC Fifth Assessment Report (AR5)1 and Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC)5 global projections
show the “likely” ranges between the 17th and 83rd percentile.
and have adopted a median high-end estimate that exceeds pro- providers including boundary organizations and government
jections used in Structures A, B, and C. actors56,57.
We compared the projections provided in the survey with Our sample spans the globe with respondents from every
IPCC Fifth Assessment Report (AR5)1 and Special Report on the habitable continent; however, we acknowledge that our responses
Ocean and Cryosphere in a Changing Climate (SROCC)5, which do not align with global populations and are dominated by North
are trusted global sources of SLR relevant to the timing of the American (49.8%) respondents. This imbalance could be an
survey (Fig. 3). Interestingly, many of the reported future sea indication of location-specific factors inhibiting responses such as
levels for planning out to 2100 are lower or significantly higher cultural and privacy differences in responding to questionnaires
than the range provided by AR51 and SROCC5. In total, we and lack of resources to respond58. Another contributor to
received 119 responses above the RCP8.5 scenario of 0.98 m response rates could be different vulnerabilities4, with some pla-
across all scenario types (see Supplementary Table 7). This ces overwhelmed by existing threats unable to respond and other
variation may reflect respondents following regional guidance places not perceiving their future vulnerabilities and thus not
that suggests higher (or lower) SLR than the global IPCC motivated to respond. Future work is required to increase sample
projections based on the timing of the guidance, known regional diversity, to better understand harder-to-reach parts of the globe,
variations, the use of relative SLR, or the inclusion of larger and to support adaptation in vulnerable communities possibly
amounts of projected sea-level rise that were given low confidence disadvantaged by capacity issues.
by the IPCC. The decision context of the practitioners we surveyed could
be a significant driver of the differences we observed52. For
example, practitioners could be responsible for the construction
Discussion of expensive long-lived infrastructure and therefore would more
We present evidence from the first global survey of coastal likely be risk averse. On the other hand, they could be
managers on the use of SLR projections in planning that practi- responsible for designing a public park and could be less risk-
tioners are incorporating SLR projections in decision making. averse. These two different risk scenarios would warrant dif-
However, we find evidence of a potential overreliance on singular ferent selections of SLR projections. Similarly, some respon-
estimates and highly inconsistent approaches to the selection of dents could be focused on short-term decisions, such as beach
SLR projections. Singular estimates are appropriate and even nourishment, while others could be responsible for long-term
necessary at the later stages of planning; however, it is currently land-use decisions. These two groups would be using different
best practice for SLR planning to include multiple scenarios, SLR values. Respondents in the application section of our sur-
generally corresponding to different possible climate futures vey identified most use cases (Supplementary Fig. 2) and many
(climate scenarios), combined with advice on risk-based robust different criteria for differentiating between projections (Sup-
adaptation methods14,19,37,48,49. We also acknowledge that plementary Fig. 3 and Supplementary Fig. 4). Thus, we cannot
developing best-practice multiple SLR scenarios may pose a match their use cases with the projections they provided. Survey
challenge for some jurisdictions with less adaptive capacity55 and design improvements would allow us to better link specific
therefore recognize the important role played by climate service decisions with standardized structures and future SLR
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projections. Future research should focus on understanding the high-end SLR scenarios, which are well suited to constrain
decision contexts with a particular focus on risk and planning adaptation options and understand the uncertainty but can be
horizon concerns. misapplied and lead to more expensive and socially disruptive
Another possible driver of the differences we observed is the adaptation measures than may be necessary. The literature indi-
source of the SLR projections used by different practitioners. For cates that high-quality translation services and peer learning
example, some practitioners could be relying on state guidance through collaborative organizations improve practitioner use of
that is particularly risk-averse and uses a high-end value, and sea-level science20,61. As the implementation of SLR adaptation
others could be relying on research that is focused on clarifying strategies is becoming more prevalent, we hope that this assess-
mean values. In our survey, we asked practitioners how the SLR ment triggers similar and improved studies on the application of
projections in their plans were developed? Respondents identified SLR science. The insights will create better bridges and shared
three primary sources: (1) selected from projections developed by understanding between science and coastal managers. Further
a higher level of government; (2) co-produced between scientists improved surveys of the type described here are essential to
and practitioners; and (3) generated as guidance by an authority inform and assess these efforts.
(Supplementary Fig. 7). We recognize that practitioners could be
relying on regional or local projections rather than the global-
mean projections and this could lead to differences. For example, Methods
the Atlantic coast of the United States is more vulnerable than Recruitment and sample. To understand the nature and extend of sea-level sci-
ence assimilation into decisions on adaptation for coastal lowlands (e.g., land-use
other parts of the country due to subsidence from glacial isostatic planning, infrastructure design, managed retreat), we recruited coastal managers
adjustment59. Subsequent work is needed to more carefully from every habitable continent using a combination of two sampling methods.
examine the sources used by practitioners and the relationship Two-hundred and fifty-three managers responded.
between those sources and the original scienti c research. We used a snowball sampling approach to reach as many geographic locationsfi
as possible. This sampling technique is ideally suited to circumstances where it can
Our findings reflect the respondents’ interpretation of the be difficult to adequately define the sampling frame62. We asked collaborating
questions we posed. We asked for sea-level rise values used for researchers and climate change specialists at national and regional levels to provide
planning purposes. Respondents could have understood these names and contacts at more localized jurisdictions that were known to be involved
values to include additional water height contributors such as in sea-level rise (SLR) planning. We also identified cities conducting SLR planning
storm surge, regional sea differences, and vertical land motion or and then targeted relevant contacts directly within the city. To identify cities weused previous publications about SLR plans and websites (e.g., Climate Adaptation
they could have understood the value to be the global value that Knowledge Exchange, U.S Resilience Tool Kit, etc.) that provide case studies on
was then adjusted to local conditions. Thus, for some cases, we SLR planning and design applications. For each location, one point of contact was
may be comparing differing realizations of flood levels to the identified from the official website or personnel database for that city. Some of the
projections of mean sea-level change provided in the IPCC participants initially identified were not appropriate contacts due to organizationaldifferences, retirement, or other factors. In these cases, the person usually provided
reports. However, here we consider what coastal managers replacement contacts.
understand to be the future projections for which they are To improve sample diversity, we used all five of the methodological
designing and planning. Investigation of the documents provided recommendations articulated in Kirchherr & Charles63. First, the team relied
by survey respondents could provide further insight. Future heavily on personal contacts with each regional lead sending the same requesting
email to their contact list requesting coastal managers at the local and regional
versions of this survey should structure questions in such a way as scale. Second, we had a diverse seeding process reaching out to multiple contacts in
to get greater clarity from survey respondents. A future survey a single region. For example, in the United States we reached out to both state-level
could request, in addition to sea-level guidance used by the officials at both the coastal zone manage agency and at the sea grant offices. Third,
respondent, plans that were developed based on the guidance, we worked hard to develop trust with individuals to get referrals for respondents.
60 We made personal phone calls to certain contacts to help gain explain the research(e.g., The Bangladesh Delta Plan ). This would provide further and enable their participation. Fourth, we were very persistent sending contacts
information on guidance usage. multiple emails from both the online survey tool and the personal contact directly.
A further step in this line of research could be to assess whether Additionally, in some cases we worked with a team of contacts in a place to help
and how certain larger-scale SLR guidance is assimilated into ensure that the survey was completed. Fifth, we had two sampling waves and did a
decisions. Specifically, does the design and regulatory environ- focused follow-up with people in regions that were hard to reach. Beyond these fivemethodologies, we also allowed for a range of ways to respond. Although we
ment of national guidance directly influence the local (i.e., city/ emphasized the online survey tool, we also allowed people to complete a PDF
county) level SLR planning? For example, does the national questionnaire at their office or over the phone with a researcher. Despite these
guidance in New Zealand, based on a dynamic adaptation path- efforts, we acknowledge that our sample has gaps and lacks the diversity we aspired
way planning approach37, provide local practitioners with more to. Future research would benefit from greater reliance on alternative datacollection methods to a survey instrument. Interviews would likely yield a greater
usable information? Additionally, more work is needed to sample diversity and more responses from regions where surveys and emails are
understand the reasons behind the different approaches and unfamiliar and hesitation to participate is high.
progress in different communities. Interviews with practitioners Our respondents represent the first global data collection on SLR use in decision
across the globe would provide signi cant insights into the bar- making. Though they were not evenly divided, no single continent represented overfi
50% of respondents (Supplementary Table 1). They comprised 10 (4.0%) from
riers encountered and opportunities available. More research is Africa, 39 (15.4%) from Asia, 31 (12.3%) from Europe, 126 (49.8%) from North
needed on how these policy and guidance documents inform the America, 44 (17.4%) from Australia/Oceania, and 3 (1.2%) from South America. At
physical infrastructure and land-use planning decisions made by the regional scale, North America Atlantic Ocean and North America Pacific
coastal managers. Ocean had the greatest representation with 78 (30.7%) and 42 (16.6%) of the
respondents, respectively. Pacific Ocean Large Islands, which include New Zealand
As global sea levels continue to rise, planning, designing, and and Australia, East Asia, North and West Europe, and Pacific Ocean Small Islands
building resilient communities will become a more pressing represented between 7.9% and 14.6% of respondents. Africa Atlantic Ocean, Baltic
societal challenge. Our research provides global data on how Sea, Caribbean Islands, Northern Mediterranean, South Asia, and Southern
coastal practitioners use sea-level science in the adaptation Mediterranean made up between 2.0% and 3.2% of the respondents. The South-
planning of coastal lowlands. Consistent with past research on east Asia, South America Pacific Ocean, Africa Indian Ocean, South AmericaAtlantic Ocean, and Gulf states had the fewest respondents, each with less than 1%.
climate services, we find significant reliance on singular estimates At the national scale, we received responses from people in 49 different
(Fig. 2) and highly inconsistent approaches to assimilating sea- countries. In forty of the countries we had between one and four respondents. In
level science into decision-making (Fig. 3). This persistent dis- nine countries we had higher participation. China, Israel, and Japan each had 5
connect raises concerns about coastal managers’ ability to respondents and together they represent 6% of our respondents. In the middle wasthe United Kingdom, New Zealand, and South Korea with 8, 10, 13 respondents,
translate complex and uncertain futures into adaptation deci- respectively. Australia, Canada, and the United States had the greatest number of
sions. This is particularly true when coastal managers are using respondents (26, 26, and 94, respectively). Within the broader context illuminated
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COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-023-00703-x ARTICLE
by the present analysis, we aim to conduct subsequent research activities to better estimates across structures B, C, and D. An example of external consistency would
investigate regions such as the Caribbean and Latin America, Africa, and South- be seeing that projection ranges within the different structures align with IPCC or
east Asia, which were less represented in this research process. SROCC projections (Fig. 3).
Respondents represented a variety of jurisdictional scales but tended towards a
local scale that afforded a unique and tangible perspective on climate adaptation Reporting summary. Further information on research design is available in the Nature
efforts undertaken to directly address SLR threats. 163 respondents (65%) were
Portfolio Reporting Summary linked to this article.
from local governments (for example, cities, councils, municipalities, towns, and
native settlements) with three (1.2%) from infrastructure-specific settings (for
example ports, airports, and ferries), and 60 (24.0%) respondents were from sub-
national governments (for example districts, provinces, states, and territories). Data availability
Only 24 (9.6%) of our respondents were from national governments. Sixteen (66%) The data files for producing the maps, tables, and graphs of this manuscript are deposited
of the national respondents were from island nations such as Nauru in Oceania and in the public repository of Utah State University at https://digitalcommons.usu.edu/all_
Trinidad and Tobago in the Caribbean while eight (33%) were from continental datasets/198/.
settings such as Bangladesh in Asia and Liberia in Africa. The high representation
from local and sub-national respondents aligns with our objective of understanding
the use of climate science by those with direct decision-making authority on Received: 21 June 2022; Accepted: 3 February 2023;
infrastructure design and land use.
Respondents represent places that account for over 1 billion people. The places
respondents answered for range widely in population. At the local government
scale, Monhegan, Maine in the United States is the smallest place that we had a
respondent from, with a population of 69. At the other end of the size spectrum, we
had a local government response from Tianjin, China with a population of over 13 References
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