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Objectives. To examine commonalities and gaps in the content of local US heat action plans (HAPs) designed to decrease the adverse health effects of extreme heat. Methods. We used content analysis to identify common strategies and gaps in extreme heat preparedness among written HAPs in the United States from jurisdictions that serve municipalities with more than 200 000 residents. We reviewed, coded, and analyzed plans to assess the prevalence of key components and strategies. Results. All 21 plans evaluated incorporated data on activation triggers, heat health messaging and risk communication, cooling centers, surveillance activities, and agency coordination, and 95% incorporated information on outreach to at-risk populations. Gaps existed in the specific applications of these broad strategies. Conclusions. Practice-based recommendations as well as future areas of research should focus on increasing targeted strategies for at-risk individuals and expanding the use of surveillance data outside of situational awareness. (Am J Public Health. 2023;113(5):559–567. https://doi.org/10.2105/AJPH.2022.307217 )

Earthquake early warning (EEW) systems are relatively new technologies having first emerged as regional systems in the 1990s. Japan was the first nation to develop and implement a nationwide system in October 2007, and in the United States, ShakeAlert® became available on the entire length of the US West Coast in May 2021. Assessing how EEW is perceived and utilized by alert recipients is considered essential. Such assessments are necessary to evaluate whether alert recipients are taking advantage of alert messages to initiate protective actions upon receipt of an alert, how they regard the usefulness of alerts, desirable thresholds for issuing alerts, and other aspects of these systems. Having information from users will also facilitate assessments of the success of earthquake preparedness educational programs such as the ShakeOut and whether annual drills which include information on EEW systems are resulting in behavioral response consistent with the content of these programs. Finally, information on EEW utilization will provide data useful to social scientists who study hazards to advance our understanding of behavioral response to warnings. Survey research in the aftermath of a significant earthquake in which an EEW has been issued is one obvious method of achieving these objectives and there already exist a number of survey instruments for this purpose. A related strategy and the goal of the present research is to develop a brief questionnaire, consistent with those already developed, as a supplement to the United States Geological Survey’s “Did You Feel It?” questionnaire that has provided earthquake intensities and information on behavioral response in earthquakes, both domestic and international, since 2004. Having the intensity level at each respondent’s location is essential for relating their perspectives and actions to the shaking they experienced.

We introduce the National Science Foundation (NSF) AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). This AI institute was funded in 2020 as part of a new initiative from the NSF to advance foundational AI research across a wide variety of domains. To date AI2ES is the only NSF AI institute focusing on environmental science applications. Our institute focuses on developing trustworthy AI methods for weather, climate, and coastal hazards. The AI methods will revolutionize our understanding and prediction of high-impact atmospheric and ocean science phenomena and will be utilized by diverse, professional user groups to reduce risks to society. In addition, we are creating novel educational paths, including a new degree program at a community college serving underrepresented minorities, to improve workforce diversity for both AI and environmental science.

As tropical cyclone threats evolve, broadcast meteorologists and emergency managers rely on timely forecast information to help them communicate risk with the public and protect public safety. This study aims to improve the usability and applicability of National Weather Service (NWS) forecast information in the context of these NWS core partners’ decisions during tropical cyclone threats. The research collected and analyzed data from in-depth interviews with broadcast meteorologists and emergency managers in three coastal U.S. states. These data were used to analyze broadcast meteorologists’ and emergency managers’ tropical cyclone decision and action timelines, their use of tropical cyclone information during different phases of threats, and gaps in forecast information for decision-making. Based on these findings, several opportunities for improving tropical cyclone risk communication were identified. Recommendations to address gaps in the NWS tropical cyclone product suite include designing improved ways to communicate storm-specific storm surge risk at greater than 48 h of lead time, expanding the use of concise highlights that help people quickly extract and understand key information, and improving product understandability and usability by more comprehensively integrating users’ perspectives into product research and development. Broader strategic recommendations include developing new approaches for informing broadcast meteorologists about major forecast updates, presenting forecast information in ways that enable locally relevant interpretation, and supporting human forecasters’ contributions to the effectiveness of NWS products and services. These findings and recommendations can help NOAA prioritize ways to modernize the current NWS tropical cyclone product suite as well as motivate research to enable longer-term high-priority improvements. Significance Statement Tropical cyclones pose significant risks to coastal and inland U.S. populations. This project aims to improve creation, communication, and use of tropical cyclone forecast and warning information by studying broadcast meteorologists’ and emergency managers’ information needs for decision-making during different phases of tropical cyclone threats. We identify several priority areas for improvement, including advancing longer-lead-time storm surge forecast communication, enhancing dissemination of forecast updates, and increasing use of concise text highlights. Additional findings include the importance of locally interpretable forecast information, the value of human forecasters in weather risk communication, and the need for iterative, user-informed forecast product development. These findings can help NOAA and the research community improve forecast communication and invest in research that facilitates continued improvements.

Many of our generation’s most pressing environmental science problems are wicked problems, which means they cannot be cleanly isolated and solved with a single ‘correct’ answer (e.g., Rittel 1973; Wirz 2021). The NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) seeks to address such problems by developing synergistic approaches with a team of scientists from three disciplines: environmental science (including atmospheric, ocean, and other physical sciences), AI, and social science including risk communication. As part of our work, we developed a novel approach to summer school, held from June 27-30, 2022. The goal of this summer school was to teach a new generation of environmental scientists how to cross disciplines and develop approaches that integrate all three disciplinary perspectives and approaches in order to solve environmental science problems. In addition to a lecture series that focused on the synthesis of AI, environmental science, and risk communication, this year’s summer school included a unique Trust-a-thon component where participants gained hands-on experience applying both risk communication and explainable AI techniques to pre-trained ML models. We had 677 participants from 63 countries register and attend online. Lecture topics included trust and trustworthiness (Day 1), explainability and interpretability (Day 2), data and workflows (Day 3), and uncertainty quantification (Day 4). For the Trust-a-thon we developed challenge problems for three different application domains: (1) severe storms, (2) tropical cyclones, and (3) space weather. Each domain had associated user persona to guide user-centered development.

Earthquake early warning (EEW) systems are becoming increasingly available or are in development throughout the world. As these systems develop, it is important to provide evidence-based recommendations for protective action so people know how to protect themselves when they receive an alert. However, many factors need to be considered when developing contextually relevant and appropriate recommendations. We have reviewed earthquake injury reports, protective action and communication theories, and behavioral research to determine what factors can guide inquiry and decision making when developing protective action guidelines. Factors that emerge from relevant literature include: (1) social, cultural, and environmental context, such as which people are present, what their social roles are, and in what type of building they are located when an earthquake happens, (2) demographic and experiential variables, such as gender and age as well as previous history with earthquakes; and (3) magnitude and intensity that influence the duration and impacts of the earthquake itself. Although we examine data from around the world, we focus largely on evidence-based recommendations for the U.S. system, ShakeAlert, because it provides a timely case study for understanding how people receive and respond to EEW messages. In addition to synthesizing relevant literature, we recommend pathways forward for this interdisciplinary research community that explores EEW and its application around the world. Consistency in collecting and reporting injury data globally may assist in aligning this fragmented literature to develop a richer understanding of how demographic, cultural, seismic, engineering, and technological issues can be addressed to reduce human suffering due to earthquakes.

Background App‐based drivers face work disruptions and infection risk during a pandemic due to the nature of their work, interactions with the public, and lack of workplace protections. Limited occupational health research has focused on their experiences. Methods We surveyed 100 app‐based drivers in Seattle, WA to assess risk perceptions, supports, and controls received from the company that employs them, sources of trust, stress, job satisfaction, COVID‐19 infection status, and how the pandemic had changed their work hours. Data were summarized descriptively and with simple regression models. We complemented this with qualitative interviews to better understand controls and policies enacted during COVID‐19, and barriers and facilitators to their implementation. Results Drivers expressed very high levels of concern for exposure and infection (86%–97% were “very concerned” for all scenarios). Only 31% of drivers reported receiving an appropriate mask from the company for which they drive. Stress (assessed via PSS‐4) was significantly higher in drivers who reported having had COVID‐19, and also significantly higher in respondents with lower reported job satisfaction. Informants frequently identified supports such as unemployment benefits and peer outreach among the driver community as ways to ensure that drivers could access available benefits during COVID‐19. Conclusions App‐based drivers received few protections from the company that employed them, and had high fear of exposure and infection at work. There is increased need for health‐supportive policies and protections for app‐based drivers. The most effective occupational and public health regulations would cover employees who may not have a traditional employer–employee relationship.

The goal of the Scientific Session: “Advances of International Collaboration on M9 Disaster Science” at the 2nd World Bosai Forum (WBF) in Sendai in November 2019 was to share progress on research projects and findings related to an M9 mega-disaster event, building on outcomes from a March 2019 collaborative workshop on M9 disaster science between research partners from the International Research Institute of Disaster Science (IRIDeS)/Tohoku University, University of Washington-Seattle (UW), and the Research Center for Integrated Disaster Risk Management (CIGIDEN). This paper reports on the presentations during the WBF Scientific Session, which shared updates and outputs of research collaborations from different disciplines, following the themes of risk-based planning, structural engineering, tsunami observation and early warning, and tsunami simulation and probabilistic tsunami risk assessment. This international and cross-disciplinary collaboration has led to the advancement of a number of specific research projects in different fields, as well as a robust network of researchers in the three countries. Based in coastal regions facing similar risks of massive earthquakes and tsunami in Japan, the United States, and Chile, it is hoped that ongoing and future collaboration within this network will continue to advance knowledge of disaster science and international disaster risk reduction.

Older adults are more susceptible to adverse health outcomes during and after a disaster compared with their younger counterparts. Ageing-in-place organisations such as senior centres and Villages provide social services and programming for older adults and may support older adults’ resilience to disasters. This study examines the role of ageing-in-place organisations in building disaster resilience for older adults. Semi-structured interviews were conducted with a purposive sample of 14 ageing-in-place organisation leaders in King County, Washington in the United States of America. The sample included representatives of five government-run senior centres, seven non-profit senior centres and two Villages. Interviews were audio-recorded and professionally transcribed. We used a combined inductive and deductive approach to code and thematically analyse the data. Ageing-in-place organisation leadership recognise disasters as a threat to older adults’ health and safety, and they see opportunities to provide disaster-related support for older adults, though the type and extent of participation in resilience-building activities reflected each organisation's unique local context. Organisations participate in a variety of disaster-related activities, though respondents emphasised the importance of collaborative and communication-focused efforts. Findings suggest that ageing-in-place organisations may be best equipped to support older adults’ disaster resilience by serving as a trusted source of disaster-related information and providing input on the appropriateness of disaster plans and messages for the unique needs of older adults ageing-in-place.

This article explores whether and how cultural worldviews influence people’s responses to approaching natural hazard threats, using data from a survey that asked residents of coastal Florida, USA, ...

Believing action to reduce the risks of climate change is both possible (self-efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts, according to current risk communication theory. Although the public recognizes the dangers of climate change, and is deluged with lists of possible mitigative actions, little is known about public efficacy beliefs in the context of climate change. Prior efficacy studies rely on conflicting constructs and measures of efficacy, and links between efficacy and risk management actions are muddled. As a result, much remains to learn about how laypersons think about the ease and effectiveness of potential mitigative actions. To bring clarity and inform risk communication and management efforts, we investigate how people think about efficacy in the context of climate change risk management by analyzing unprompted and prompted beliefs from two national surveys (N = 405, N = 1,820). In general, respondents distinguish little between effective and ineffective climate strategies. While many respondents appreciate that reducing fossil fuel use is an effective risk mitigation strategy, overall assessments reflect persistent misconceptions about climate change causes, and uncertainties about the effectiveness of risk mitigation strategies. Our findings suggest targeting climate change risk communication and management strategies to (1) address gaps in people's existing mental models of climate action, (2) leverage existing public understanding of both potentially effective mitigation strategies and the collective action dilemma at the heart of climate change action, and (3) take into account ideologically driven reactions to behavior change and government action framed as climate action.

Communicating the uncertainty associated with forecasts is crucial to effective crisis response management, but it is particularly challenging when time frames are too short to articulate the complexities of the information. However, not communicating uncertainties is problematic. For technical experts, interdependencies amongst event characteristics over time creates evolving uncertainties that may eclipse those associated with modelled outcomes. For the public and emergency decision-makers, the lack of uncertainty awareness may result in future alternative courses of action not being identified and assessed, reducing the efficacy of decisions and action plans. Furthermore, revealing uncertainty can both increase or decrease the credibility and trustworthiness of the communicator. Some individuals will devalue a message when uncertainty is communicated, while others may devalue the message when they expect uncertainty and it has not been communicated. If we are to develop effective ways to communicate uncertainty in a crisis, research needs to understand the reasons for these differences. Key influences include how perceptions of science, its uncertainty, and the scientific process, act as a lens through which scientific information is interpreted. This lens can warp communicated information, particularly when uncertainty is high: during a crisis, people may not take appropriate safety actions based upon scientific advice if the message contradicts or fails to accommodate, their existing perceptions of the science. Forecasts, warnings, and other communication products must address these existing perceptions if they are to be effective. These perceptions are represented in people’s mental models of how they think the world works, including their model of scientific processes, motivations, beliefs, and values, which vary across disciplines and organizations due to epistemic differences. We will report on the initial findings from a study that a) identifies the appropriate methodology to elicit mental models of science in the public and professional populations, and b) uses this to explore how mental models of scientific uncertainty are held by the public, emergency managers, scientists, engineers, and key decision-makers involved in hazard response. Our aim is to identify the shared concepts underlying these mental models, so forecast messaging can be effectively crafted to include uncertainty in a way that aligns with individuals’ mental models. Through this we offer strategies to enhance individual decision-making under uncertainty in ways that develop the trust that the public and decision-makers have in forecasts.

Natural hazards and disaster reconnaissance investigations have provided many lessons for the research and practice communities and have greatly improved our scientific understanding of extreme events. Yet, many challenges remain for these communities, including improving our ability to model hazards, make decisions in the face of uncertainty, enhance community resilience, and mitigate risk. State-of-the-art instrumentation and mobile data collection applications have significantly advanced the ability of field investigation teams to capture quickly perishable data in post-disaster settings. The NHERI RAPID Facility convened a community workshop of experts in the professional, government, and academic sectors to determine reconnaissance data needs and opportunities, and to identify the broader challenges facing the reconnaissance community that hinder data collection and use. Participants highlighted that field teams face many practical and operational challenges before and during reconnaissance investigations, including logistics concerns, safety issues, emotional trauma, and after-returning, issues with data processing and analysis. Field teams have executed many effective missions. Among the factors contributing to successful reconnaissance are having local contacts, effective teamwork, and pre-event training. Continued progress in natural hazard reconnaissance requires adaptation of new, strategic approaches that acquire and integrate data over a range of temporal, spatial, and social scales across disciplines. U.S. National Science FoundationNational Science Foundation (NSF) [1611820] The U.S. National Science Foundation supported this work under grant number 1611820. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

In 2016, the National Science Foundation (NSF) funded a multi-institution interdisciplinary team to develop and operate the Natural Hazards Reconnaissance Facility (known as the "RAPID") as part of the Natural Hazards Engineering Research Infrastructure (NHERI) program. During the following 2 years, the RAPID facility developed its instrumentation portfolio and operational plan with input from the natural hazards community, the facility's leadership team, and an external steering committee. In September 2018, the RAPID began field operations, which continue today and include instrumentation, software, training, and support services to conduct reconnaissance research before, during, and after natural hazard and disaster events. Over the past 2 years, the RAPID has supported the data collection efforts for over 60 projects worldwide. Projects have spanned a wide range of disciplines and hazards and have also included data collection at large-scale experimental facilities in the United States and abroad. These projects have produced an unprecedented amount of high-quality field data archived on the DesignSafe cyberinfrastructure platform. This paper describes the RAPID facility's development, instrumentation portfolio (including the mobile application RApp), services and capabilities, and training activities. Additionally, overviews of three recent RAPID-supported projects are presented, including descriptions of field data collection workflows, details of the resulting data sets, and the impact of these project deployments on the natural hazard fields. NSFNational Science Foundation (NSF) [1904653, 1904327, CMMI: 1611820]; NSF through GEER [1826118]; Oregon DOT; FHWA [SPR807] The RAPID Facility operates under a cooperative agreement with the NSF under Award No. CMMI: 1611820. Research on the performance of LRLVBs in Hurricane Michael was supported by the NSF under award nos. 1904653 and 1904327. Research on the flow slide during the Palu, Indonesia earthquake was supported by the NSF through GEER under award number 1826118. Any opinions, findings, conclusions, and recommendations presented in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation. Funding for the Hooskadaden Landslide case study were provided by Oregon DOT and FHWA (SPR807).

Developing trustworthy artificial intelligence for weather and ocean forecasting, as well as for long-term environmental sustainability, requires integrating collaborative efforts from many sources.

Judgment, decision making, and risk researchers have learned a great deal over the years about how people prepare for and react to global risks. In recent years, risk scholars have increasingly foc...

This benefit-cost analysis (BCA) assesses the economic value of the implementation and operation of an earthquake early warning system (EEWS) over a 50-year period in the state of Washingto...

A growing body of research demonstrates that believing action to reduce the risks of climate change is both possible (self-efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts. Despite this potentially critical role of efficacy beliefs, measures and their use vary wildly in climate change risk perception and communication research, making it hard to compare and learn from efficacy studies. To address this problem and advance our understanding of efficacy beliefs, this article makes three contributions. First, we present a theoretically motivated approach to measuring climate change mitigation efficacy, in light of diverse proposed, perceived, and previously researched strategies. Second, we test this in two national survey samples (Amazon's Mechanical Turk N = 405, GfK Knowledge Panel N = 1,820), demonstrating largely coherent beliefs by level of action and discrimination between types of efficacy. Four additive efficacy scales emerge: personal self-efficacy, personal response efficacy, government and collective self-efficacy, and government and collective response efficacy. Third, we employ the resulting efficacy scales in mediation models to test how well efficacy beliefs predict climate change policy support, controlling for specific knowledge, risk perceptions, and ideology, and allowing for mediation by concern. Concern fully mediates the relatively strong effects of perceived risk on policy support, but only partly mediates efficacy beliefs. Stronger government and collective response efficacy beliefs and personal self-efficacy beliefs are both directly and indirectly associated with greater support for reducing the risks of climate change, even after controlling for ideology and causal beliefs about climate change.

This paper examines the societal dimensions of warning decisions during extreme weather events in one of the most hurricane-prone areas in the U.S., Miami-Dade County, Florida. With the aim of informing improvements in the hurricane forecast and warning system, and better understanding warning decisions in extreme weather events, we explore how members of the public obtain and use hurricane forecasts and warnings in decision making. Results from in depth mental models interviews with members of the public (N = 28) and survey data from three counties in Florida (N = 460) show that a large majority of respondents have some hurricane experience, which influences their thinking about storm impacts, individual actions to mitigate the hazard, and vulnerability to the hazard. Comparison with results from previous research with warning system professionals (National Weather Service forecasters, media broadcasters, and public officials) indicates several gaps between professionals and laypeople including different perceptions of hurricane risks overall and related to flooding from storm surge. The findings suggest several areas for improvements in the hurricane forecast and warning system.

Both Sendai City in Japan and Seattle-King County (hereafter referred to as “Seattle”) in Washington State in the United States are in seismically active areas with high earthquake risks. An Earthquake Early Warning (EEW) system has been publicly available in Japan since 2007. The ShakeAlert system on the U.S. West Coast is still being developed and was at the time of this study being rolled out to provide earthquake early warning to institutional and public users. Given the high costs, concomitant need for public funding, and protective behavior aims of EEW systems, a better understanding of how society and individuals perceive the system and how they react to alerts is crucial to maximize the benefits of EEW. In this study, we compared how Sendai and Seattle residents perceived earthquake risk and EEW effectiveness, as well as their willingness to pay (WTP) for an improved (Sendai) or newly adopted (Seattle) EEW system. Similarities in the risks of megaquakes and the differences in recent events and earthquake early warning implementation enabled us to test the extent to which associations between earthquake risk perceptions, risk preparedness, and support for government policies to reduce earthquake risks can be generalized across these contrasting conditions. We found that risk perceptions and perceived effectiveness of EEW in personal protection were significant determinants of WTP for an (improved) EEW system in both regions. However, the association of “fear” with earthquakes was a significant predictor of WTP only in the Seattle survey. One possible explanation for this is that emotional reactions to earthquakes were more varied in the Seattle sample than Sendai, likely due to the much milder earthquakes that have occurred in the Pacific Northwest of the US in recent decades than in Japan. In contrast, most Sendai respondents reported that they felt danger and fear in their recent earthquake experiences.

Many people visit or live in areas that are exposed to natural or technological hazards but lack sufficient information to protect themselves when a disaster threatens. Hazard and emergency managers in federal, state, local and tribal government, as well as scientists and educators in tsunami warning centers, try to meet this need by providing essential information about hazards and appropriate protective actions. To date, however, there has been limited guidance for the preparation of hazard education products such as maps and brochures. Accordingly, this article reviews research on hazard education, warning systems, and warning response, as well as research findings on the communication of textual, numeric, graphic, and cartographic information in risk messages. This review produced an evaluation rubric comprising eight criteria—1) general evaluation criteria, 2) hazard-specific content, 3) environmental cues content, 4) hazard warning (sources/channels/messages) content, 5) preparedness actions content, 6) response actions content, 7) numeric information, and 8) maps. These criteria are illustrated by four experts’ evaluations of six tsunami evacuation products (TEPs—brochures and standalone maps). Although the small samples of raters and TEPs limit the generalizability of the results, this evaluation shows how hazard and emergency managers can assess the quality of preliminary TEP designs before conducting more scientifically rigorous evaluations using experimental or quasi-experimental designs.

Public support for carbon emissions mitigation is crucial to motivate action to address global issues like climate change and ocean acidification (OA). Yet in the public sphere, carbon emissions mitigation policies are typically discussed in the context of climate change and rarely in the context of OA or other global change outcomes. In this paper, we advance research on OA and climate change perceptions and communication, by (i) examining causal beliefs about ocean acidification, and (ii) measuring support for mitigation policies from individuals presented with one of five different policy frames (climate change, global warming, carbon pollution, air pollution, and ocean acidification). Knowledge about OA causes and consequences is more widespread than we anticipated, though still generally low. Somewhat surprisingly, an “air pollution” mitigation frame elicits the highest degree of policy support overall, while “carbon pollution” performs no better than “climate change” or “global warming.” Framing effects are in part contingent on prior knowledge and attitudes, and mediated by concern. Perhaps due to a lack of OA awareness, the OA frame generates the least support overall, although it seems to close the gap in support associated with political orientation: the OA frame increases support among those (few) conservatives who report having heard of OA before the survey. These findings complement previous work on climate change communication and suggest the need for further research into OA as an effective way to engage conservatives in carbon emissions mitigation policy. Potentially even more promising is the air pollution framing.

Prior research demonstrates widespread persistence of beliefs about climate change causes and risks that are arguably misconceptions. They include believing pollution causes climate change, believing ozone depletion causes climate change, the combination of these two "green beliefs," referred to as environmental problems, and believing natural climate variation significantly contributes to current climate trends. Each of these causal beliefs has the potential to weaken or divert support away from effective climate change risk mitigation policies. To assess this potential, we explore the nature and prevalence of these beliefs in the United States with a national sample of interviews (N = 77) and two national surveys (N = 1,013, N = 1,820), and apply regression and mediation analyses to explore whether they explain any of the variation in individuals' concern or support for policy to mitigate climate change. Adherence to these beliefs-which reflect a variety of misconceptions illustrated in the interviews-differs by political ideology but is common, with over a third of interviewees mentioning one or more. Controlling for general knowledge, political ideology, and other factors, misconceptions about environmental problems are still associated directly with support for climate change policies. On average adherence to the belief that environmental problems cause climate change is associated with a 25% higher probability of policy support. In contrast, believing natural climate variability is a major recent cause of climate change is associated with a 7% lower probability of supporting climate policy, even after controlling for political ideology and other knowledge about climate change.

Tallis, Heather; Kreis, Katharine; Olander, Lydia; Ringler, Claudia; Ameyaw, David; Borsuk, Mark E.; Fletschner, Diana; Game, Edward; Gilligan, Daniel O.; Jeuland, Marc; Kennedy, Gina; Masuda, Yuta J.; Mehta, Sumi; Miller, Nicholas; Parker, Megan; Pollino, Carmel; Rajaratnam, Julie; Wilkie, David; Zhang, Wei; Ahmed, Selena; Ajayi, Oluyede C.; Alderman, Harold; Arhonditsis, George; Azevedo, Ines; Badola, Ruchi; Bailis, Rob; Balvanera, Patricia; Barbour, Emily; Bardini, Mark; Barton, David Nicholas; Baumgartner, Jill; Benton, Tim G.; Bobrow, Emily; Bossio, Deborah; Bostrom, Ann; Braimoh, Ademola; Brondizio, Eduardo; Brown, Joe; Bryant, Benjamin P.; Calder, Ryan S.D.; Chaplin-Kramer, Becky; Cullen, Alison; DeMello, Nicole; Dickinson, Katherine L.; Ebi, Kristie L.; Eves, Heather E.; Fanzo, Jessica; Ferraro, Paul J.; Fisher, Brendan; Frongillo, Edward A.; Galford, Gillian; Garrity, Dennis; Gatere, Lydiah; Grieshop, Andrew P.; Grigg, Nicola J.; Groves, Craig; Gugerty, Mary Kay; Hamm, Michael; Hou, Xiaoyue; Huang, Cindy; Imhoff, Marc; Jack, Darby; Jones, Andrew D.; Kelsey, Rodd; Kothari, Monica; Kumar, Ritesh; Lachat, Carl; Larsen, Ashley; Lawrence, Mark; DeClerck, Fabrice; Levin, Phillip S.; Mabaya, Edward; Gibson, Jacqueline MacDonald; McDonald, Robert I.; Mace, Georgina; Maertens, Ricardo; Mangale, Dorothy I.; Martino, Robin; Mason, Sara; Mehta, Lyla; Meinzen-Dick, Ruth; Merz, Barbara; Msangi, Siwa; Murray, Grant; Murray, Kris A.; Naude, Celeste E.; Newlands, Nathaniel K.; Nkonya, Ephraim; Peterman, Amber; Petruney, Tricia; Possingham, Hugh; Puri, Jyotsna; Remans, Roseline; Remlinger, Lisa; Ricketts, Taylor H.; Reta, Bedilu; Robinson, Brian E.; Roe, Dilys; Rosenthal, Joshua; Shen, Guofeng; Shindell, Drew; Stewart-Koster, Ben; Sunderland, Terry; Sutherland, William J.; Tewksbury, Josh; Wasser, Heather; Wear, Stephanie; Webb, Chris; Whittington, Dale; Wilkerson, Marit; Wittmer, Heidi; Wood, Benjamin D.K.; Wood, Stephen; Wu, Joyce; Yadama, Gautam; Zobrist, Stephanie. Aligning evidence generation and use across health, development, and environment. Current Opinion in Environmental Sustainability 2019 ;Volum 39. s. 81-93

With the anticipated boom in the ‘blue economy’ and associated increases in industrialization across the world’s oceans, new and complex risks are being introduced to ocean ecosystems. As a result, conservation and resource management increasingly look to factor in potential interactions among the social, ecological and economic components of these systems. Investigation of these interactions requires interdisciplinary frameworks that incorporate methods and insights from across the social and biophysical sciences. Risk assessment methods, which have been developed across numerous disciplines and applied to various real-world settings and problems, provide a unique connection point for cross-disciplinary engagement. However, research on risk is often conducted in distinct spheres by experts whose focus is on narrow sources or outcomes of risk. Movement toward a more integrated treatment of risk to ensure a balanced approach to developing and managing ocean resources requires cross-disciplinary engagement and understanding. Here, we provide a primer on risk assessment intended to encourage the development and implementation of integrated risk assessment processes in the emerging blue economy. First, we summarize the dominant framework for risk in the ecological/biophysical sciences. Then, we discuss six key insights from the long history of risk research in the social sciences that can inform integrated assessments of risk: (1) consider the subjective nature of risk, (2) understand individual social and cultural influences on risk perceptions, (3) include diverse expertise, (4) consider the social scales of analysis, (5) incorporate quantitative and qualitative approaches, and (6) understand interactions and feedbacks within systems. Finally, we show how these insights can be incorporated into risk assessment and management, and apply them to a case study of whale entanglements in fishing gear off the United States west coast.

Hazard maps are used to communicate complex scientific data with many audiences during volcanic unrest crises, but it is unclear how common hazard visualisation styles affect cognition, behaviour, and decision-making. Here we use eye-gaze tracking and questionnaires to explore how 81 people near a volcano in New Zealand read and make decisions with hazard maps for a hypothetical eruption. We find that greater mental effort is required to read early-stage hazard maps associated with higher uncertainty, and that showing integrated zones of low to high hazard can result in 1) higher perceived threat, 2) limited visual attention to the maps, and 3) more risk-averse decisions under pressure compared to visualising discrete hazard footprints. People with high prior risk perceptions demonstrate less attention to map content overall. The results show how map visualisation can influence cognition, decision-making, and behaviour, and have implications for crisis communication. For example, in the early stages of a volcanic event, integrated hazard zones may help capture audience attention by facilitating a high-level assessment of risk. As the event evolves, discrete footprints of individual hazard processes may help better inform high-stakes decisions for which detailed hazard knowledge is needed. Additionally, we find that providing simple tasks for the audience to carry out using the maps, and showing safe areas alongside hazardous areas, may encourage map reading. We discuss the implications of these findings, and present four evidence-based points for scientists to consider across a range of fields where hazard maps are used to communicate with non-specialist audiences.

Earthquake early warning systems can provide seconds to minutes of lead time by alerting people that an earthquake has started and shaking is coming, enabling them to take protective action. To examine how earthquake early warnings might be received on the U.S. West coast, we conducted surveys of residents in the west coast states of Washington, Oregon and California (N=2595) through Google paywall intercept surveys administered in three rounds between September 2014 and September 2015. A majority of residents in all states (61% WA, 54% OR, 70% CA) have personally experienced an earthquake. Those who have experienced an earthquake perceive higher risk and greater potential for effectively reducing that risk with earthquake early warning. Although respondents feel that federal and local government should pay for earthquake early warning, almost two-thirds report being willing to pay something for “an Earthquake Early Alert app on [their] smartphone or personal computer.” Median willingness to pay per month is $1. Perceived risk, perceived effectiveness of earthquake early warning, and anticipated or experienced emotional responses to earthquakes influence judgments of and preferences for earthquake early warning, although personal experience of earthquakes conditions these influences. Further, highly visible mass media communications such as the New Yorker article “The Really Big One” and the movie “San Andreas” increase earthquake risk perceptions. Overall, interest in and support for earthquake early warning on the U.S. West Coast appears strong.

The study reported here explores how to enhance the public value of hurricane forecast and warning information by examining the entire warning process. A mental models research approach is applied to address three risk management tasks critical to warnings for extreme weather events: 1) understanding the risk decision and action context for hurricane warnings, 2) understanding the commonalities and conflicts in interpretations of that context and associated risks, and 3) exploring the practical implications of these insights for hurricane risk communication and management. To understand the risk decision and action context, the study develops a decision-focused model of the hurricane forecast and warning system on the basis of results from individual mental models interviews with forecasters from the National Hurricane Center (n = 4) and the Miami–South Florida Weather Forecast Office (n = 4), media broadcasters (n = 5), and public officials (n = 6), as well as a group decision-modeling session with a subset of the forecasters. Comparisons across professionals reveal numerous shared perceptions, as well as some critical differences. Implications for improving extreme weather event forecast and warning systems and risk communication are threefold: 1) promote thinking about forecast and warning decisions as a system, with informal as well as formal elements; 2) evaluate, coordinate, and consider controlling the proliferation of forecast and warning information products; and 3) further examine the interpretation and representation of uncertainty within the hurricane forecast and warning system as well as for users.

Fisheries are increasingly managed with involvement of fishers and other stakeholders; this approach is believed to create ownership and maximize stakeholder buy-in. Stakeholder involvement is critical where managers lack adequate knowledge, resources to gather additional information, or resources to implement management. Such ‘data-limited’ fisheries are of global import but face challenges to meeting management goals. Sustainable management of data-limited fisheries may be improved by decision support. This paper reports results of a field experiment testing the FishPath interactive decision-support software tool for data-limited fisheries (FishPath) and its influence on stakeholder buy-in to management. In Stage 1, participants were provided a hypothetical fishery that mimicked real-world data limitations, and a tailored shortlist of management options; participants did not interact with FishPath. In Stage 2, participants collectively input the fishery into FishPath; the tool output the same management options seen in Stage 1. In Stage 3, to assess the effect of expert support, participants were randomly assigned to control and treatment groups. The control group explored output without additional support, while the treatment group explored output with support from a FishPath expert. After each stage, participants were asked to rate: 1) their support for formal management of the fishery; 2) how easy or hard they expected management of the fishery to be; and 3) how effective they expected management of the fishery to be. FishPath use increased stakeholder participants’ perceptions of the ease and effectiveness of management at each stage of the experiment, although support for management was unchanged.

As ShakeAlert, the earthquake early warning system for the West Coast of the U.S., begins its transition to operational public alerting, we explore how post-alert messaging might represent system performance. Planned post-alert messaging can provide timely, crucial information to both emergency managers and ShakeAlert operators as well as calibrate expectations among various publics or public user groups and inform their responses to future alerts. There is a concern among the scientists and emergency managers that false alerts may negatively impact trust in the system, so quickly disseminated post-alert messages are necessary. For a new early warning system, such as ShakeAlert, this is particularly relevant given that the potentially affected population is likely to be unfamiliar with this system. We address this concern in six steps: (1) assessment of ShakeAlert performance to date, (2) characterization of human behavior and response to earthquake alerts, (3) presentation of a decision tree for issuing post-alert messages, (4) design of a critical set of post-alert messaging scenarios, (5) elaboration of these scenarios with message templates for a variety of communication channels, and (6) development of a typology of earthquake alerts. We further explore methods for monitoring and evaluating ShakeAlert post-alert messaging, for continuous improvement to the system.