natural disasters research task

METHODS article

Research needs, challenges, and strategic approaches for natural hazards and disaster reconnaissance.

• 1 RAPID Facility, Department of Civil & Environmental Engineering, University of Washington, Seattle, WA, United States
• 2 Evans School of Public Policy & Governance, University of Washington, Seattle, WA, United States
• 3 Department of Human-Centered Design and Engineering, University of Washington, Seattle, WA, United States
• 4 Geomatics Lab, School of Civil and Construction Engineering, Oregon State University, Corvallis, OR, United States
• 5 Department of Civil and Coastal Engineering, University of Florida, Gainesville, FL, United States
• 6 Center for Coastal Studies and Department of Civil & Environmental Engineering, Virginia Tech, Blacksburg, VA, United States
• 7 Applied Physics Laboratory, University of Washington, Seattle, WA, United States
• 8 Formerly, RAPID Facility, Department of Civil & Environmental Engineering, University of Washington, Seattle, WA, United States

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.

Introduction

Natural hazards and disaster reconnaissance investigations have led to important discoveries that have greatly improved our scientific understanding of hazards and their physical, social, and environmental consequences. For example, findings from one of the earliest field reconnaissance missions in the United States, the Lawson and Reid (1908) investigation of the 1906 ∼M7.9 San Francisco earthquake, led to the development of the landmark theory of elastic rebound ( Reid, 1910 ), among other significant scientific and engineering advancements ( Ellsworth, 1990 ). More recently, post-event reconnaissance investigations have provided new, fundamental knowledge essential for the development of computational models to simulate the physical and socioeconomic impacts of natural hazards, and for identifying ways that communities can restore their infrastructure, rebuild their built environment, and recover their socioeconomic capital (e.g., Xiao and Van Zandt, 2012 ; Xiao and Peacock, 2014 ; Cong et al., 2018 ; Kang et al., 2018 ; Nejat et al., 2019 ). Far from an uncaring or indifferent data-gathering exercise in the face of tragedy, reconnaissance campaigns are at their core “a humanitarian mission in the broadest sense” ( Kaplan, 2010 ).

Natural hazards, such as wind events (i.e., tornadoes and coastal storms, including wind-generated waves and surges), earthquakes (and secondary effects such as shaking-induced damage to buildings and infrastructure, soil liquefaction and co-seismic landslides, and tsunamis), landslides, and volcanic eruptions, produce an extraordinary volume and quality of data that can inform our preparation and response to future events ( Nature Geoscience, 2017 ). Such data are often highly ephemeral or “perishable” since they may be altered or removed during rescue and recovery activities, or by natural agents such as precipitation or wind following an event. Therefore, reconnaissance data must be collected soon after an event occurs. These data are also unique because they inherently include the real-world complexities (e.g., the interplay between natural, human, and built systems) that allow us to better understand and quantify the socio-technical dimensions related to damage, restoration, and resiliency of the built environment; such data are difficult to duplicate in a traditional laboratory setting. Reconnaissance data, once collected, processed, curated, and archived ( Rathje et al., 2017 ), may be used and reused for a range of purposes, including (i) making discoveries and gaining fresh insights, (ii) testing and verifying models, (iii) reducing uncertainties in probabilistic models, and (iv) inspiring new simulation models, including new data-driven methods (e.g., Loggins et al., 2019 ).

In the past, reconnaissance investigators collected data and documented field observations using conventional recording and measurement tools, such as photography, note-taking, and surveying ( Geotechnical Extreme Events Reconnaissance [GEER], 2014 ). Today, the availability of state-of-the-art instrumentation, mobile data collection technologies (e.g., RApp; Miles and Tanner, 2018 ; Berman et al., in press ), training, and field support services, such as those provided by the Natural Hazards Engineering Research Infrastructure (NHERI) Natural Hazards Reconnaissance Facility (known as the RAPID) ( Wartman et al., 2018 ; Berman et al., in press ), has significantly advanced the ability of field investigation teams to capture perishable data in post-disaster settings.

This article briefly reviews the current state of natural hazards and disaster reconnaissance, including highlights from recent missions, difficulties teams face, and opportunities for progress. It then examines the grand challenges facing the natural hazards community and presents new approaches to meet these challenges through the strategic design, planning, and execution of reconnaissance campaigns. Many of the ideas presented in the article were developed with input from key stakeholders, including participants of a 2-day reconnaissance workshop, previous and current users of RAPID facility instrumentation, and other disciplinary experts in the professional, government, and academic sectors.

Natural Hazards and Disaster Reconnaissance

The history of natural hazard and disaster investigations spans many centuries. Interest in natural hazards, frequently by religious scholars, gathered momentum during the Renaissance and Reformation (14th to 16th centuries) when authorities began systematically cataloging earthquakes and other rare events such as plagues ( Schenk, 2007 ; Tülüveli, 2015 ). Scholars often used these data in an attempt to reconcile extreme events with spiritual beliefs and religious concepts. Lawson and Reid (1908) comprehensive, two-volume report on the San Francisco, California earthquake ( Figure 1 ) is one of the first rigorous scientific field studies of a major natural hazard ( Ellsworth, 1990 ). A decade later, Prince (1920) conducted one of the first social sciences investigations of an extreme event, the Halifax, Nova Scotia, Canada explosion of a munitions ship in the city harbor. Social sciences studies of disasters became more systematic and formalized in the 1940s through the 1960s, largely due to work at the Disaster Research Center (Ohio State University), which was initially supported by the U.S. Office of Civil Defense to inform cold war civil defense efforts (e.g., Knowles, 2012 ). Earthquake Engineering Research Institute [EERI] (1971) conducted one of the first in-depth multidisciplinary investigations of a natural hazard event, the San Fernando, California earthquake.

Figure 1. The Lawson and Reid (1908) reconnaissance investigation of the 1906 San Francisco earthquake led to significant scientific and engineering advancements. (A) Reconnaissance photograph showing fence offset by earthquake surface fault rupture near Bolinas, Marin County, CA, United States. This observation led to the development of the theory of elastic rebound ( Reid, 1910 ). (B) Excerpt of “Map of San Francisco showing apparent intensity of the earthquake shock” ( Lawson and Reid, 1908 ) showing area of high intensity shaking revealing the modern engineering concept of non-linear site response and effects (Gray and green tones depict areas of highest local shaking intensity). Both images are reproduced from Lawson and Reid (1908) .

The EERI was one of the first professional organizations to formalize regular reconnaissance investigations of major seismic events by establishing the Learning from Earthquakes (LFE) program in 1973. Largely multidisciplinary in its approach, the LFE program deploys teams of geoscientists, engineers, and social scientists to investigate and observe the damaging effects of significant earthquakes worldwide. Recently, the LFE program has expanded to include a virtual earthquake reconnaissance teams, or “VERT,” that conduct rapid “virtual” (i.e., non-field based) assessments within 48 h of an earthquake ( Fischer and Hakhamaneshi, 2019 ).

With the support of the U.S. National Science Foundation (NSF), the Geotechnical Extreme Events Reconnaissance (GEER) Association was formed in 1999 to conduct reconnaissance investigations of the geotechnical aspects of significant earthquakes in the U.S. and abroad ( Bray et al., 2019 ). In 2011, GEER’s scope was expanded to include the study of the geotechnical aspects of other natural hazard events such as hurricanes, floods, and landslides (e.g., Dashti et al., 2014 ; Wartman et al., 2016 ; Hughes and Morales Vélez, 2017 ; Gallant et al., 2020 ; Montgomery et al., 2020 ). GEER authorizes research missions based upon (i) the opportunity to learn about new scientific hypotheses or engineering models, (ii) the availability of additional field data (e.g., ground motion recordings) to supplementary data gathered in the reconnaissance, and (iii), for international (non-U.S.) events, the potential for a similar event to occur in the future in the U.S ( Geotechnical Extreme Events Reconnaissance [GEER], 2014 ). During the past several years, NSF began supporting other similar “extreme event reconnaissance (or research),” or EER, organizations including StEER (Structural Extreme Events Reconnaissance), OSEEER (Operations and Systems Engineering Extreme Events Research), SSEER (Social Science Extreme Events Research), ISEEER (Interdisciplinary Science and Engineering Extreme Events Research), NEER (Nearshore Extreme Events Reconnaissance), and SUstainable Material Management Extreme Events Reconnaissance (SUMMEER). These EER organizations are coordinated by CONVERGE ( Peek et al., 2020 ), which seeks to advance ethically-grounded ( Gaillard and Peek, 2019 ), scientifically rigorous, disciplinary, and interdisciplinary extreme events research.

There are other natural hazards reconnaissance organizations based at professional societies worldwide. The Earthquake Engineering Field Investigation Team (EEFIT), based in the United Kingdom, supports earthquake reconnaissance missions with the goals of making technical assessments, collecting geological and seismological data, assessing the effectiveness of earthquake protection systems, and investigating disaster management procedures and socioeconomic impacts ( Stone et al., 2017 ). Italy hosts two organizations that have organized earthquake reconnaissance missions and conducted follow-on seismic policy analyses (e.g., Mazzoni et al., 2018 ), the Italian Network of University Laboratories for Earthquake Engineering (ReLUIS), and the European Centre for Training and Research in Earthquake Engineering (Eucentre). Elsewhere, the New Zealand Society for Earthquake Engineering (NZSEE) has supported reconnaissance investigations of earthquakes and major tsunamis worldwide for six decades ( Wood P. R. et al., 2017 ). In Asia, the Asian Technical Committee (ATC3) “Geotechnology for Natural Hazards” has conducted reconnaissance missions following natural hazard events. Other organizations, such as the Nepalese Engineering Society, the Building Research Institute of Japan, among others, also conduct investigations in the region. Similarly, the American Society of Civil Engineers (ASCE) has supported reconnaissance missions in the U.S. and abroad through the primary society (e.g., Silva-Tulla and Nicholson, 2007 ) or its disciplinary institutes (e.g., Wartman et al., 2013 ).

In addition to these organizations, self-organized teams sometimes form in the aftermath of an event, often with a focused hypothesis-driven research question or inquiry, to collect data. Table 1 summarizes the objectives and outcomes of recent reconnaissance investigations of several representative natural hazard events. Figures 2 through 5 present field data collected during several of the missions highlighted in Table 1 .

Table 1. Examples of reconnaissance approach, objectives, and outcomes from several recent earthquake and wind hazard missions ( Figure 2 ).

Figure 2. Assessing the performance of buildings using lidar data collected during reconnaissance. (A) Lidar-derived 3D model of Nyatapola Temple following the 2015 Ghorka Nepal Earthquake (B) Earthquake-induced crack (designated as “C1”) seen in a color point cloud (left) and detected defects shown in red (right). Reproduced from Wood P. R. et al. (2017) .

Figure 3. Reconnaissance investigation of the impact of rockfalls on dwellings during the 2011 Christchurch, New Zealand, earthquakes. (A) Lidar data was collected inside and outside buildings, geo-registered, then fusing into a single 3D model. (B) Field data reveals a direct correlation between rockfall impact energy and rock penetration into buildings. Modified from Grant et al. (2018) .

Figure 4. Diagram depicting damage features, secondary effects, and human and societal impacts that commonly result from an extreme wind event. The diagram is similar to Figure 7 , illustrating the commonalities between seismic and wind natural hazard events. Diagrams and inset images are as noted in Figure 7 .

Figure 5. Diagram illustrating damage features, secondary effects, and human and societal impacts that often result from a significant earthquake (blue illustrations and accompanying text). Superimposed above this hypothetical post-event landscape are annotations linking instrumentation (shown with inset photographs) and data collections activities and products (shown in red) to event features.

Reconnaissance Instrumentation and Natural Hazard Simulation

By enabling the prompt collection of high-resolution data sets, advanced reconnaissance instrumentation now plays a central role in providing the academic, research, and professional communities with an unprecedented volume of high-quality, open-source, engineering, geophysical, social, and behavioral data. In addition, new software and cyberinfrastructure tools allow complex data sets to be archived, integrated, explored, and visualized ( Rathje et al., 2017 ). These computational resources facilitate collaboration among experts across different fields to support advancements at the intersections of the natural hazards specialty disciplines. A unique aspect of the RAPID Facility is its portfolio of geospatial, image-centric data collection instrumentation. High-resolution georeferenced laser, image, and video data collected from full fields of view (i.e., top to bottom; inside and outside) of infrastructure within affected regions support the development of 3D post-event models ( Berman et al., in press ). Such models can be safely interrogated to extensive detail by geographically distributed research teams—an aspect that allows investigators the time and vision to collaboratively continue to discover new and important aspects of the impact of the surveyed event ( Olsen and Kayen, 2013 ; Olsen et al., 2015 ). These types of terrestrial data sets are increasingly being fused with broader scale satellite imagery to appreciate the regional context for damage at a specific site (e.g., Yamazaki and Matsuoka, 2007 ; Eguchi et al., 2008 ; Rathje and Franke, 2016 ; Gallant et al., 2020 ).

Modeling and simulation lie at the center of the natural hazard community’s broader goal to understand, simulate, and predict the performance of built, natural, and social systems during and after natural hazards events ( Edge et al., 2020 ). Over the past decade, a portfolio of highly sophisticated natural hazards models has significantly improved our ability to simulate the effects of extreme events across a wide range of spatial and temporal scales (e.g., Roelvink et al., 2009 ; Dietrich et al., 2011 ; LeVeque et al., 2011 ; Pita et al., 2013 ; Mandli and Dawson, 2014 ; Yim et al., 2014 ; Baradaranshoraka et al., 2019 ). These natural hazards models have become increasingly data-driven, requiring comprehensive data sets to capture complex, system-level responses. Examples of such models include performance-based earthquake engineering (PBEE) design methods and resilience-based design methods (e.g., FEMA, 2018 ; McAllister et al., 2019 ), which require fragility data to relate structural, non-structural, and infrastructure systems performance to engineering demand parameters, and stochastic wind hazard loss models ( Hamid et al., 2011 ; Pita et al., 2015 ) that require field data to better calibrate and validate the hazard, infrastructure vulnerability, costing components, and economic impacts of preparedness and mitigation policies.

The RAPID Facility’s principal scientific goal is to inform natural hazards computational simulation models, infrastructure performance assessment, and economic impact analysis by supporting the collection, development, and assessment of high-quality disaster data sets ( Figure 6 ). These data sets help advance our fundamental understanding of natural hazards and their impacts. Examples of reconnaissance data collection required to improve the natural hazards modeling and simulation include the following:

Figure 6. Grand challenges for the natural hazards community require new strategic approaches for reconnaissance data collection utilizing RAPID instrumentation and services. This data collection will produce data products that are needed to meet grand challenges. Central to this cycle is the RAPID Facility’s scientific goal of informing natural hazards computational simulation models, infrastructure performance assessment, and socioeconomic impact analysis by supporting the collection, development, and assessment of high-quality data sets [digital elevation model (DEM)].

1. Lifelines and other elements of the built environments are ultimately socio-technical systems ( Miles et al., 2014 ). That is, there are core social, economic, and behavioral components to the development, operation, and maintenance of all engineered systems. There is a crucial need for research to better unpack and quantify the socio-technical dimensions related to damage, restoration, and reconstruction of elements of the built environment. This research is needed to advance existing socio-technical loss (e.g., Kircher et al., 2006 ) and recovery models ( Miles and Chang, 2011 ), as well as to develop new ones. Most socio-technical modeling efforts to date have focused on modeling losses.

2. Development of high-resolution, geocoded data sets, such as aerial photography, lidar, and ground-based documentation of post-event damage (e.g., Gurley and Masters, 2011 ; Lombardo et al., 2015 ), to reduce uncertainties in stochastic models characterizing the vulnerability of infrastructure to wind and earthquake damage. Modern catastrophe risk models ultimately seek to project damage, loss, and recovery time at the whole-building, infrastructure system, or regional scale; examples modeling tools include FEMA (2018) as well as the community and regional resilience modeling tools such as OpenQuake ( Pagani et al., 2014 ) and those being developed by the Center for Risk-Based Community Resilience Planning ( van de Lindt et al., 2015 ) and the NHERI SimCenter. These tools predict building performance through the aggregation of component failures (e.g., FEMA, 2018 for earthquake hazard and Pita et al., 2015 for wind hazard) or based on building-level models such as those incorporated in FEMA HAZUS-MH ( Kircher et al., 2006 ). These simulation tools include numerous assumptions regarding probabilistic structural component capacities, load paths, the influence of aging, and cascading damage from neighboring structures. Thus, they benefit substantially from refinements to these assumptions informed by detailed geocoded field data stratified by building code and localized hazard intensity.

Provision of appropriate data to test, verify, and calibrate co-seismic landslide displacement models [e.g., the popular and practice-oriented Newmark et al. (1965) sliding model, as well as more advanced coupled (e.g., Rathje and Bray, 2000 ) or finite element formulations]. Specifically, advanced geomatics technologies such as lidar could capture intricate ground deformation patterns and landslide morphological features, eroded quickly after an event. There are relatively few high-quality case histories of co-seismic landslide displacement, which represents a pressing research need in the field of geotechnical earthquake engineering ( Harp et al., 2011 ).

1. Provision of the appropriate data to quantify underlying physical phenomena and to develop, validate, improve, and reduce uncertainty in physics-based, computational modeling of wind, waves, storm surge, tsunami inundation, sediment transport, morphological change, and other related processes representing the inter-related, destructive forcing mechanisms of natural hazards ( Kennedy et al., 2020b and references therein). Specifically, modern reconnaissance instrumentation can capture rare, but critical, perishable data during and following natural hazards, including the quantification of inundation extent, flow speeds, flow depth, wave conditions, wind speeds, soil properties, erosion and accretion, and inundation-related damage to civil infrastructure and the natural environment ( Kennedy et al., 2020a ). These data help improve understanding of, for example, (a) the interplay between the natural landscape (land cover, topographic features), the built environment (critical infrastructure, homes), and hydrodynamics and (b) how and when concurrent multi-hazard components (e.g., wind vs. surge) lead to the functional failure of critical infrastructure—ultimately leading to more resilient communities (e.g., Baradaranshoraka et al., 2017 ).

2. Simulation of structural response to ground shaking is validated mainly through comparison with data from experiments in controlled laboratory environments and with data collected from reconnaissance following earthquakes. The structural models may be focused on component behaviors, building behaviors, or even the behavior of entire classes of buildings through the development of fragility functions. Recent examples of field data informing advances in local structural behavior models include Kanvinde et al. (2015) , who investigated fracture of eccentrically braced frame links during the 2011 Christchurch earthquake and used collected field data helped to validate newly developed fracture models employed in detailed finite element analyses. At the macro-level, fragility functions derived from reconnaissance data on the performance of wood-frame buildings have resulted in large-scale loss estimations for San Francisco arising from the soft-story collapse of wood-frame structures and spurred public policy to encourage retrofit ( FEMA, 2012 ). Such observation-based fragility data are also critical to loss estimation software such as FEMA (2018) , FEMA HAZUS-MH ( Kircher et al., 2006 ) and OpenQuake ( Pagani et al., 2014 ), and the regional loss estimation tools being developed by the Center for Risk-Based Community Resilience Planning and the NHERI SimCenter.

Grand Challenges for the Natural Hazards and Disaster Research Communities

In 2011, the National Research Council convened a community workshop to identify grand challenges for earthquake engineering. These challenges served to guide research after the conclusion of the George E. Brown, Jr. Network for Earthquake Engineering Simulation operations ( National Research Council [NRC], 2011 ). While the title of the workshop highlighted earthquake engineering, the NRC steering committee noted that the identified grand challenges (community resilience, decision making, simulation, mitigation, design tools) were broad and also pertained to other natural and anthropogenic hazards. These grand challenges are adopted here as an overarching framework for identifying reconnaissance research opportunities for natural hazards and disaster research communities.

Community Resilience

To better understand the direct and indirect impacts of natural hazards events, a framework is needed to measure, monitor, and evaluate community-level resilience. The lack of historical data on community impacts and recovery following past disasters presents a significant impediment to meeting this goal ( National Research Council [NRC], 2011 ). Advanced reconnaissance instrumentation helps address this challenge by enabling the systematic collection and archiving integrated, interdisciplinary data pertinent to engineering and the natural and social sciences. This knowledge is necessary to evaluate the utility and validity of the range of community resilience frameworks—a significant gap in the state-of-the-art in disaster science and engineering ( Miles, 2015 ).

Hazard and Impact Simulation and Decision Making

Computational simulation and forecasting of the timing and regional distribution of the hazard itself (e.g., Frankel et al., 2018 ), as well as its physical and social impacts and recovery, are essential for decision making, planning, and mitigation. Such simulations—which span a range of temporal scales, including both short-term (e.g., informing electricity restoration with expected damage patterns) and long-term time frames (e.g., identifying local vulnerabilities for risk reduction policy-making)—present a challenge to the professional community ( National Research Council [NRC], 2011 ). New, high-performance computing and software platforms such as the NHERI DesignSafe-CI and SimCenter ( Blain et al., 2020 ) create the opportunity to make significant progress with this challenge. However, such simulations are highly complex and require extensive hypervariable data sets for model development and testing. Since many of these models are inherently data-driven, they also require high-quality data (e.g., initial and boundary conditions) to provide reliable forecasts.

Renewal and retrofit strategies are essential to mitigate hazards posed to infrastructure systems and communities (e.g., water and wastewater supply and distribution systems, power and energy systems, at-risk buildings, and coastal communities) ( National Research Council [NRC], 2011 ). The development of effective mitigation strategies requires computational models (see above), design methods, and construction standards that, when harmonized, are capable of identifying critical vulnerabilities and quantifying the impacts of risk reduction measures. In addition, post-event data are needed to evaluate loss estimation methodologies, such as HAZUS-MH, investigate the efficacy of mitigation approaches (e.g., Gurley and Masters, 2011 ), and provide feedback on state-mandated insurance incentives for homeowners who employ mitigation. New multiscale data collection tools provide the means to address these needs. For example, terrestrial lidar and building survey equipment could be used to collect data on the seismic performance of retrofitted buildings. Similarly, lidar or structure from motion (SfM)/multi view stereo photogrammetry ( Eltner et al., 2016 ; Özyeşil et al., 2017 ) technology can be used in coastal communities after hurricanes to quantify morphological changes, civil infrastructure damage, and ecological damage in detail and on a large scale. Importantly, all of these data sources can be integrated and overlaid with imagery to develop three-dimensional models of impacted regions or damage-affected infrastructure.

Design Tools

Improved capability to characterize uncertainty in the predictive ability of design tools is essential to exploit newer, more sustainable, and resilient building materials. Improved design tools are also needed to capitalize on innovative structural concepts (e.g., self- centering structural systems with replaceable fuses) ( National Research Council [NRC], 2011 ). Performance-based design provides the framework for addressing this challenge, but such design relies on high-quality performance data to define model relationships (e.g., fragility functions). Advanced instrumentation offers a means to meet this challenge. For example, sensors could be installed on structures and earth systems to monitor response to aftershocks ( Geli et al., 1988 ; Zhou et al., 2013 ), and aerial imagery could be used to validate the performance of wind-resistant roof covers.

In 2017, the Network Coordination Office ( Johnson et al., 2020 ) of NHERI convened a task group to prepare a network-wide science plan to guide future research and to focus investigators on keeping the communities and the built environment safe from natural hazards. The NCO’s NHERI network science plan was first published in July 2017 ( Smith et al., 2017 ) and reflected many of the principals of the National Research Council Grand Challenges report ( National Research Council [NRC], 2011 ). The NHERI network science plan highlights the need to (1) identify and quantify the characteristics of natural hazards that are damaging to civil infrastructure and disruptive to communities, (2) evaluate the physical vulnerability of civil infrastructure and the social vulnerability of populations in communities exposed to natural hazards, and (3) create the technologies and engineering tools to design, construct, retrofit, and operate multi-hazard resilient and sustainable infrastructure. The network issued a revised science plan in January 2020 ( Edge et al., 2020 ) that reflects the potential role of several new, rapidly advancing technologies (e.g., advanced computational methods, information science, bio-inspired design, convergence science) in improving community resilience to natural hazards. The revised science plan identifies three grand challenges for the community. These include (1) identifying and quantifying the characteristics of earthquake, windstorm, and associated hazards that are damaging to civil infrastructure and disruptive to communities, (2) assessing the physical vulnerability of civil infrastructure and the social vulnerability of populations in communities, and (3) creating the technologies and engineering tools to design, construct, retrofit, and operate a multi-hazard resilient and sustainable infrastructure. In addition to the NRC workshop report and the NHERI network science plans, other reports suggest specific research activities and tasks to help meet challenges in the fields of earthquake hazard reduction ( National Earthquake Hazards Reduction Program, 2008 ), resilience ( National Research Council [NRC], 2011 ), windstorm and coastal inundation impact reduction ( Coulbourne et al., 2014 ), and disaster risk reduction ( Aitsi-Selmi et al., 2015 ).

Research Needs, Challenges, and Opportunities for Natural Hazards Reconnaissance

Methodology.

In January 2017, the RAPID Facility convened a 2-day workshop to determine natural hazards and disaster reconnaissance data needs and opportunities and identify the broader challenges facing the reconnaissance community that encumber data collection and use. The workshop attendees—individuals having expertise across a range of natural hazards (e.g., wind events, earthquakes, and their secondary effects) and disciplines (engineering, and the natural and social sciences)—participated in three types of activities (also see Supplementary Material ).

(1) Informational presentations to provide background material to help stimulate later discussion in activity groups

(2) Guided “brainstorming-type” small group activities

(3) Responding to open-ended questions posed on poster boards placed in the break area during the first day of the workshop

During the brainstorming activities, participants were asked to first reflect on questions individually and later to share, discuss, and synthesize their ideas in small, pre-assigned groups. For some disciplinary-focused activities, groups were organized by specialty, while in other activities, groups were intentionally interdisciplinary to allow cross-fertilization of ideas between sciences and engineering domains. The ideas developed during the individual sessions and group discussions were attached to poster boards using sticky notes. Each group reported the general themes to all of the workshop participants. Over 1,600 ideas, comments, and replies recorded on sticky notes during the workshop. After the workshop, each of these notes was assigned a unique identifier code, cataloged, and then read and transcribed to a comprehensive database, which is included as Supplementary Material to this article. The workshop organizers then synthesized and analyzed the database of workshop comments and transcriptions to identify significant themes on needs, challenges, and opportunities for natural hazards and disaster reconnaissance.

Many of the workshop participants were seasoned reconnaissance investigators with the collective experience of dozens of reconnaissance missions following natural hazard events and other disasters—both natural and anthropogenic in origin. The participants responded to questions about the practical and operational challenges they have faced before, during, and after reconnaissance investigations. They also provided feedback about what went well (i.e., their “successes”) during reconnaissance missions. As noted in Table 2 , major challenges before deploying for reconnaissance mainly involve logistics in the compressed time frames intrinsic to extreme event investigations. During field missions, many of the challenges relate to the on-the-ground realities of working in a disaster zone, including safety concerns and emotional trauma. The difficulties after reconnaissance missions primarily pertain to data processing, analysis, and archiving. The participants reported a range of common themes about pre- and during deployment successes ( Table 3 ), including having previously established local contacts in the affected region, teamwork and camaraderie, and prior training on instrumentation reconnaissance methods, and safety. Successes after reconnaissance missions mainly pertain to the production of unique data products, improved fundamental knowledge, and positive impacts on policy and practice.

Table 2. Synthesis of key themes in workshop participant responses to questions about challenges and successes before, during, and after reconnaissance missions (see Supplementary Material for complete list).

Table 3. Synthesis of High Priority Reconnaissance Data Needs to address Grand Challenges for the natural hazards and disaster research communities (see Supplementary Material for complete list).

The workshop participants were also asked to identify reconnaissance data needed to support the four National Research Council [NRC] (2011) grand challenges (i.e., community resilience framework, hazard and impact simulation and decision making, mitigation, and design tools). As indicated in Table 3 , the responses, which form the basis of our recommended strategic approaches for natural hazards and disaster reconnaissance, are broadly themed on concepts of cross-scale, multidisciplinary data collection.

Strategic Approaches for Natural Hazards and Disaster Reconnaissance

Post-disaster reconnaissance investigations have historically often involved the collection and development of data sets by disciplinary teams following natural hazard events. These data sets have usually been collected over limited geospatial scales (e.g., at the site or neighborhood scales) with little supporting metadata. As a result, such data sets can be challenging, if not impossible, to integrate. Meeting community challenges and accomplishing the scientific goal of improving simulation models requires new strategic approaches for reconnaissance investigations that acquire and integrate data over a range of temporal, spatial, and social scales across disciplines. Figures 7 , 8 illustrate links between the strategic approaches for natural hazard reconnaissance data collection, instrumentation, and resulting data products, for a hypothetical earthquake and wind event, respectively.

Figure 7. UAVs with high-resolution cameras are well-suited capture perishable data (e.g., roof cover damage, debris field), and provide complementary datasets for ground-based damage surveys. The areal perspective of UAVs reveals structural damage that is hidden from the view of ground-based damage surveyors. Photograph by Kwasi Oerry was acquired under sponsorship from the Florida Building Commission.

Figure 8. Observed time series of water level anomaly during Hurricane Ike (2008) along the open coasts of Louisiana and Texas (top-to-bottom show easternmost locations to westernmost locations). Data shown include rapidly installed pressure sensors (R-Z) by A. Kennedy (University of Notre Dame) and NOAA stations (8760922, 8761724, 8762075, 8764227, 8766072, 8768094). Line 1 shows the location of Hurricane Ike, while Line 2 shows the propagation of the forerunner wave. Reproduced from Kennedy et al. (2011) with permission of the publisher.

Temporal Scales

Resilience is the central, unifying goal of the natural hazards and disaster research communities (e.g., National Research Council [NRC], 2011 ; National Research Council, 2012 ). The term refers to an impacted community’s ability to resist, absorb, accommodate, adapt to, transform and ultimately recover and move on from the effects of a hazard in a timely and efficient manner ( United Nations, 2017 ). A path toward better upstanding, assessing, and improving resilience involves collecting and analyzing data over time frames representing conditions and states before, during, and after significant natural hazard events. Data on pre-event or “before” conditions are essential for understanding the pre-existing factors that influence, shape, and define a community’s response to a natural hazard event. With its emphasis on post-event response, the collection of pre-event data is largely outside the scope of the traditional reconnaissance community; however, much of this data currently exists or is being collected by governmental agencies and authorities, non- governmental organizations, and the private sector.

Moreover, there exists an opportunity for the natural hazards and disaster communities to lead organized efforts to catalog, organize, and synthesize such data, making it possible to link them with reconnaissance data. Data on the direct impacts of an event (“during event data”) are the traditional focus of reconnaissance investigations. These data provide critical information on the character of the loadings and the consequent physical response of the built environment, the immediate social, economic and public health impacts on communities, and interactions between these. These data also represent the starting point for recovery from natural hazard events. After an event, data collected are critical for understanding the response, recovery, and evolution of communities following events. Collecting data representing during and after events conditions requires both traditional rapid response reconnaissance investigations and follow-up data-gathering efforts. These longer-term data gathering investigations may span periods of weeks, months, or years, depending on the nature of the event and the characteristics of the affected communities.

Geospatial Scales

Natural hazard events often impact areas spanning 100s-to-1000s of square kilometers. Their widespread geographic distribution makes them, by definition, regional-scale events. The resulting damage and impact patterns reflect the fundamental nature of the hazard and the characteristics of the communities and built systems within affected regions. Over the past several decades, the ability to analyze the effects of natural hazards at the site- and building-scales has significantly improved, leading to better modeling tools, new building technologies, and robust building codes. In recent years the natural hazards and disaster communities have shown a growing interest in regional-scale impact modeling. A key advantage of regional-scale models is their ability to forecast the distribution of hazard impacts and thus capture system-level performance and propagation of risk across a region. Such models are particularly important when considering the impact of hazards on geographically distributed critical infrastructure systems.

Improving our understanding of hazard impacts and advancing regional scale modeling requires collection and synthesis of data over spatial scales spanning multiple orders of magnitude (i.e., from the site-specific to the regional scales; ∼m 2 to ∼km 2 ). This necessitates a portfolio of instrumentation that can facilitate the acquisition of fine-grained, high-resolution “site-specific” data and also support the collection in a practical manner of data from a much broader area. This also requires reconnaissance investigations to be conducted at both local and regional scales. Acquiring multiscale data enables the local impacts of a hazard to be understood in the broader context of regional-scale loading patterns and community characteristics. Equally important, this data can support the information necessary to bridge site-specific and regional scale models, which improves the ability to simulate the consequences of an extreme event across a vast region.

Social Scales

Natural hazard events can have immensely varying impacts and consequences at all social scales, from individuals and households to neighborhoods and communities; organizations, businesses, and governments; and up to and including countries, cultures, and global consequences (e.g., Oliver-Smith, 1996 ; Paton and Johnston, 2001 ; Quarantelli, 2003 ; Boon et al., 2012 ). As the Covid-19 pandemic wreaks havoc on individual lives, senior centers, vulnerable communities, nations, and the global economy, inequities and the heterogeneity of hazard effects at different social scales have commanded renewed attention (e.g., Adams-Prassl et al., 2020 ). Differences in natural and built environments contribute to potentially predictable variation in hazard impacts on society and individuals and can interact with societal responses ( Paton and Johnston, 2001 ). Infrastructure damages can hinder immediate and longer-term responses, including emergency responses, evacuation, and sheltering, but also communications and governance. Direct hazard effects on the physical environment, such as flooding, landslides, and fire, are not only potentially deadly to individuals but can also cause longer-term mental harm and disrupt social and economic activities at multiple scales. However, the lack of population-representative fine-scaled data on damages and human exposures for natural hazards and disasters continues to be called out (e.g., Bakkensen and Mendelsohn, 2016 ).

Assessing hazard exposures and consequences across these domains and social scales requires instrumentation and data collection sensitive to and associated with social, built, and natural environmental conditions, as well as temporal and spatial scales. Data collection processes that are multi-scalar and consider the social processes that can make people hard to reach will have a better chance of representing minority populations most likely to be among the most vulnerable to the majority of hazard events ( Shaghaghi et al., 2011 ). Data can be contextualized with the appropriate metadata, but also improved by designing direct data collections—such as observations, interviews, and surveys—to address these contextual factors and link geophysical, engineering, and social data. Social scientists have long acknowledged interactions across social scales (e.g., Bronfenbrenner and Morris, 2006 ). New technologies, analytical approaches, and data sources—such as biophysical and EEG (electroencephalogram) measurement tools (e.g., Bailey et al., 2017 ), crowdsourcing (e.g., Cobb et al., 2014 ), social media (e.g., Chae et al., 2014 ; Spence et al., 2016 ; Wang and Taylor, 2018 ), and satellite observations of night lights and other forms of evidence of human activities and interventions at larger scales (e.g., Ehrlich et al., 2009 ; Ceola et al., 2014 )—can enable researchers to examine these interactions in new ways. They can also support insights into and simulations of how individual responses and behaviors contribute to or are shaped by responses and events at larger social scales.

Multidisciplinary Data Sets

A disaster is a severe disruption of the functioning of a community or a society at any scale due to hazardous events interacting with conditions of exposure, vulnerability, and capacity leading to human, material, economic and environmental losses and/or impacts ( United Nations, 2020 ). A better understanding of the complicated relationship between hazards, the built environment, and communities requires that the physical and socioeconomic factors leading to disasters be untangled. Accomplishing this requires the reconnaissance community to collect and synthesize multidisciplinary data sets. In addition to improving our fundamental understanding of disasters, these data can play a critical role in establishing relationships between hazards and their broad consequences, ultimately leading to an improved ability to model, manage, and mitigate risk to communities.

Natural hazard events provide extraordinary opportunities to improve our fundamental understanding of disasters and their consequences. This understanding is critical for reducing the growing human and capital losses arising from extreme events (e.g., Coronese et al., 2019 ). To minimize losses, the natural hazard and disaster research and practice communities must meet several key challenges related to improving modeling and design making, community resilience, and hazard mitigation (e.g., National Research Council [NRC], 2011 ). Reconnaissance data, which captures real-world complexities of events (e.g., the interplay between natural, human, and built systems), plays an increasingly important role in meeting these challenges. The recent availability of state-of-the-art instrumentation and mobile data collection applications has dramatically improved the quality and increased the quantity of disaster data, paving the way toward a new era of natural hazards reconnaissance. However, to fully realize the potential of these advancements, we must employ new strategic approaches for natural hazards reconnaissance that acquire and integrate data over a range of temporal, spatial, and social scales across disciplines. Specifically, this involves the following.

(1) Data collection over time frames representing conditions and states before, during, and after significant natural hazard events.

(2) The collection and synthesis of data over spatial scales spanning multiple orders of magnitude (i.e., from the site-specific to the regional scales; ∼m 2 to ∼km 2 ).

(3) Data collection is sensitive to and associated with social, built, and natural environmental conditions, and considers the social processes that can make populations hard to reach.

(4) The collection and synthesis of multidisciplinary data sets to establish relationships between hazard events, their antecedents, and their broad consequences, ultimately leading to an improved ability to model, manage, and mitigate disaster risk to communities.

Data Availability Statement

All datasets generated for this study are included in the article/ Supplementary Material .

Author Contributions

JW, JB, AB, SM, MO, KG, JI, LL, TT, and JD developed the RAPID Facility science plan reported in this article. SM and AB designed the community workshop and later worked in close collaboration with JW and JB to interpret the result and develop findings. MG, AL, and JP work with members of the reconnaissance community users to implement the science plan into field missions. All authors contributed to manuscript drafting and revision, and read and approved the submitted version.

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.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank the many experts (see the list in Supplementary Material ) who participated in the January 2017 reconnaissance workshop in Seattle and engaged in thoughtful discussions that led to many of the ideas expressed in this article. A portion of the content if this manuscript has been published as part of the RAPID Facility Science Plan ( RAPID Facility, 2017 ).

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fbuil.2020.573068/full#supplementary-material

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Keywords : natural hazard, disaster, reconnaissance, instrumentation, simulation, data

Citation: Wartman J, Berman JW, Bostrom A, Miles S, Olsen M, Gurley K, Irish J, Lowes L, Tanner T, Dafni J, Grilliot M, Lyda A and Peltier J (2020) Research Needs, Challenges, and Strategic Approaches for Natural Hazards and Disaster Reconnaissance. Front. Built Environ. 6:573068. doi: 10.3389/fbuil.2020.573068

Received: 16 June 2020; Accepted: 28 September 2020; Published: 10 November 2020.

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Copyright © 2020 Wartman, Berman, Bostrom, Miles, Olsen, Gurley, Irish, Lowes, Tanner, Dafni, Grilliot, Lyda and Peltier. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Joseph Wartman, [email protected]

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• Published: 07 August 2023

Harbingers of decades of unnatural disasters

• Friederike E. L. Otto   ORCID: orcid.org/0000-0001-8166-5917 1 &
• Emmanuel Raju   ORCID: orcid.org/0000-0002-2348-1850 2  

Communications Earth & Environment volume  4 , Article number:  280 ( 2023 ) Cite this article

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• Attribution
• Climate-change impacts

Extreme weather events and their impacts have dominated headlines throughout 2021 and 2022. The emphasis on the weather in reports of the events, often discussed in the context of climate change, has led many to believe that these disasters would not have happened without human-induced warming. However, our compilation of severe weather-related hazards and the most severe related disasters in those two years reveals that ultimately, all the listed disasters resulted from existing vulnerabilities and compounding stresses on social systems. Climate change often made the hazard worse, but much of the damage could have been prevented. We emphasise that the reporting of disasters should routinely address not only the weather-related hazards and humans’ role in changing the odds, but also vulnerability in order to guide disaster risk reduction and avoid risk creation processes.

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Introduction.

Climate change is not happening at some point in the future. Instead past and present burning of fossil fuels is contributing to disasters that kill people and destroy livelihoods here and now. 2021 brought not only devastating extreme events across the globe (see Fig.  1 ). But with the publication of the sixth assessment report of the Intergovernmental Panel on Climate Change (IPCC) also brought the clearest scientific evidence of what is causing these hazards 1 . 2022 brought further extreme weather (see Fig.  2 ) but also political reactions, most noticeably in the form of a decision to establish a loss and damage fund at the 27th Conference of the Party (COP 27) in Sharm El Sheik.

The most impactful weather events are shown as symbols. Events which can be clearly attributed to human-induced climate change are shown in red, events for which no studies but enough background literature exists are shown in yellow and events indicated in black have either been studied, but no link to climate change has been found or no literature exists. The symbols are placed approximately in the area of the occurrence of the event. The assessment is based on published literature either of the event itself (events in red) or an event off the same category in the same region (events in yellow). The references for each individual event can be found in Table  S1 .

As Fig.  1 but for events occurring in 2022.

These hazards are, in many cases, not purely natural anymore, as a result of anthropogenic climate change. Nevertheless, also unnatural hazards only become disasters when they interact with exposure and vulnerability. The latter is constructed by socio-political processes, e.g. colonial structures leading to dysfunctional governments 2 and poorly designed developmental projects 3 , and are in general not global but national or sub-national processes 4 . A fact that is often missing from the public discussions and even the summary for policy makers of the synthesis report of the IPCC 6th assessment report mention vulnerability only once (paragraph A2.2) in the context of current impacts but not at all with respect to adaptation.

A focus solely on climate and hazard in the context of disasters creates a discourse that deflects responsibility from the human actions that produce vulnerability and often also exposure. On the other hand, ignoring the context of climate change deflects responsibility from nations and corporations in the Global North and risks ignoring potentially dramatic shifts in the hazards that have the potential to undo any developmental gains 4 .

Working on the example of extremes in the years 2021 and 2022, we show how the complex interplays between the natural world and human societies have led to some of the most devastating disasters. Many of the impacts of the extreme events we list could have been avoided 5 . Some of them have made global headlines; others have been completely ignored by the global media.

The aim of our synthesis is twofold: firstly, we provide a review of the most impactful weather and climate-related hazards and resulting disasters of the last 2 years in the context of climate change and vulnerability. Secondly, we argue that establishing a mechanism recording these types of disasters on an ongoing basis in the way suggested here, including information on the role of climate change alongside humanitarian impacts, would lead to better reporting and ultimately better responses to weather-related hazards and resulting disasters by neither ignoring the role of climate change nor the role of vulnerability.

The hazards of 2021/22

The most complete global data base for disasters from a humanitarian point view, em-dat 6 , hosted by the University of Louvain in Belgium, collects and classifies information on disasters as they occur around the world. Next to earthquakes and technological disasters, there are three categories of disasters that are primarily linked to extreme weather events. These are: meteorological events, i.e. heat waves and storms, hydrological, i.e. floods, and climatological, i.e. droughts and wildfires 6 . For the year 2021, all three categories of climate-linked hazard-related disasters combined have 351 separate entries, affecting over 70,000,000 people, leading to 182,479,722,000 US$ reported economic losses and 6920 reported deaths. Figure  1 summarises for each of the three categories the ten entries with most deaths, most affected people and highest economic costs (see also Table  S1 ). As some of the disasters are simultaneously among the 10 deadliest and 10 costliest and also are linked to the same weather and climate-related event, there are fewer than 90 distinct events. We do the same for the disasters of 2022, where overall 42,372,628,000 US$ of losses were reported, 11,376 reported deaths and more than 83,000,000 people affected by disasters. The full lists as well as the tables used to produce Fig.  1 can be found in the SI following the design suggested in Clarke et al. 7 . The events are colour-coded according to the role of climate change in the hazards, with red identifying events that have a clear climate change signal, based on an explicit study (references in Table  S1 ), yellow those that have very likely a climate change signal based on existing studies in the literature on similar types of events (references in Table  S1 ).

In most cases, no dedicated study exists that allows attributing the role of climate change quantitatively for the specific event, however in some cases events of the same type in the same region have been assessed in an attribution study or the IPCC, in which case we are still able to provide an estimate of the role of climate change. For example, hurricanes Ida, Elsa and Fred hit the Caribbean and the US in 2021, killed over 100 people and led to very high economic damages and long-term impacts. There is no attribution study on the specific storms, but many hurricanes in the same area and season have been analysed 8 , 9 with all studies finding an increase in intensity and frequency of the associated rainfall attributable to human caused climate change, including the latest IPCC report where such an increase is assessed with high confidence. Therefore our assessment for hurricane Ida, as well as Fiona is also that climate change did make the impacts worse. For tropical cyclones Odette, Seroja-21, Noru and others costing many more lives in the Pacific we do however not know what the role of climate change is as much fewer studies on pacific storms exists and those that do exist have inconclusive results 10 , 11 .

For the hydrological-related hazards and disasters, i.e. floods, we do have attribution studies, and concrete estimates of the role of climate change in the deadliest flood in the global North, leading to over 250 deaths in Germany, Belgium and the Netherlands. Also, for prominently reported floods in Pakistan and Nigeria in 2022, leading to over 2000 reported deaths. But we do not have similar estimates for the monsoon floods costing more than 1000 Indian lives in 2021 and again in 2022 or for all the other flood-related disasters occurring in the world. Flood attribution is however more difficult than the attribution of other types of extreme events as the local hydrology plays a crucial role in addition to the meteorological event, requiring bespoke models rather than state-of-the-art climate models alone 12 , 13 . Thus, only if studies in the same region and season exist we assess an event as “attribution suspected”, as e.g. for floods on the East coast of Brazil, but not the West in 2022.

The climatological events of the last 2 years are primarily wildfires and droughts. While we often lack concrete studies for wildfires, many studies in recent years have shown that due to the strong increase in hot extremes, the risk of wildfires has also increased due to climate change 14 , 15 . In this case, we assign them “attribution suspected”. Droughts are those events of 2021 and 2022 that have affected most people and they primarily occurred in Africa and the middle East. Attribution studies for events in the middle East do not exist, but for Eastern Africa and Madagascar, where some of the most disastrous events happened, they do, and have consistently found anthropogenic climate change to play a small or negligible role. This is in contrast to droughts in Southern Africa or the Mediterranean. Further, the two deadliest climatological events of 2021 were a different type of event however, so-called GLOFs, Glacier Lake Outburst Floods. Such events do occur naturally from time to time, but with the melting of glaciers strongly attributed to anthropogenic climate change, the increasing risk of such floods has in the past been attributed to human-caused climate change 16 . However, the more impactful of these GLOFs has later been identified as an avalanche that was not connected to a glacier lake outburst 17 . The authors suspect anthropogenic climate change to have played an important role in this avalanche as melting snow and ice destabilises the mountain system overall. How and to what extent and with what consequences is however poorly understood and given the large impacts of these events needs more research. Climatological events, despite the fact that they affect most people are thus still comparably understudied and need more research.

Overall, this analysis of climate and weather-related hazards of the last 2 years that led to disasters reveals a few important patterns, illustrated in Figs.  1 and 2 . First, there is only one heatwave in 2021 that has been classified as such, and that is the one affecting Canada and the north western US 18 underlining the lack of reporting and awareness of heatwaves in the global South, particularly in Africa 19 . Second, there is a huge discrepancy between our knowledge of the role of climate change for events occurring in the global North compared to the global South with many more attribution studies conducted in the former 20 , 21 . Third, floods and droughts are affecting a particularly large number of people compared to, e.g. tropical cyclones in the global North which are however the costliest disasters in terms of known economic damages. There are many countries, in particular in the middle East and Asia, that suffered several floods and droughts in 2021 and in 2022, including Afghanistan and Iran. No attribution studies exist for that part of the world, nor does the IPCC assessment allow for any conclusions on the role of climate change to be drawn, nor have these events received any media attention despite the wide reporting on political events in 2022 in the region.

While no systematic global media analysis exists yet, we observed the extremes that led to disasters in 2021 and 2022 making headlines not only in local and national news, but internationally when they occurred in the global North. This includes events like the drought in Europe in 2022 that is not in the table as humanitarian impacts are small. This is clearly not the case for disasters in the Global South, with one notable exception, the drought in Madagascar and the floods in Pakistan which coincided with the COP 27. Thus, 2021 and 2022 media followed the pattern observed before 22 with a focus on climate change on global North events and with little focus on vulnerability in the global South. Below we provide details about the drought in Madagascar, the tropical cyclone Yaas, that hit India and Bangladesh in 2021 and the heatwave that affected parts of India and Pakistan in 2022, to show that both, vulnerability and climate change are important to understand these disasters and corroborate our hypothesis that we need better reporting on both to ultimately adapt better and avoid further risk creation.

Three disasters, four countries, very different vulnerabilities

Yaas made landfall on the Indian coast in West Bengal and Odisha on the 26th of May, reaching the West coast of Bangladesh in the evening of the same day where it led to particularly high tidal waves of 6–8 feet above normal high tides. The storm also struck areas that were hit by Cyclone Amphan in 2020 and were still struggling with the aftermath and thus not only led to additional damage but impeded the ability to recover 23 , 24 .

A key obstacle in understanding the role of climate change in tropical cyclones is the lack of a clear theoretical understanding of how cyclones change in a warmer world, given that two effects are competing: warmer oceans provide conditions for stronger cyclones to develop while a more stable tropical atmosphere is associated with a decrease in cyclones 25 . Furthermore reliable observations of tropical cyclones exist only for a short timespan outside of the North Atlantic, rendering the testing of theories as well as attribution studies difficult. There have thus not been attribution studies for Cyclone Yaas, or Amphan or the Bay of Bengal more broadly. However, while the role of climate change on tropical cyclones in this area clearly needs more investigation, the studies that do exist in other parts of the world still allow some conclusions that apply outside of the North Atlantic to be drawn.

Heavy precipitation associated with tropical cyclones is increasing as well as storm surge heights due to sea level rise 25 . Both of these factors mean that for any given storm damages associated with tropical cyclones like Yaas are worse due to human-induced climate change. This is relevant for Yaas, given the storm surge was particularly damaging and storm surges have been shown to have become worse due to climate change in the Bay of Bengal 26 . In addition, while globally the overall frequency of tropical cyclones is not changing, and might even be declining 27 we do observe an increase in the proportion of major tropical cyclones 1 globally which again points to an increase in the damages in the wake of tropical cyclones because of human induced climate change.

Therefore, even in the absence of concrete attribution studies we can conclude that anthropogenic climate change is an important driver of the damages resulting from Yaas, even if it is uncertain if the storm intensity itself is affected we cannot quantify the contribution in the hazard itself without a dedicated study. This is further supported when looking at some of the most impactful tropical cyclones occurring in 2022, also in the Indian Ocean, hitting Madagascar, Mozambique and Malawi for which an attribution study confirmed that climate change indeed increased the intensity of the associated rainfall (see Table  S2 ).

The role climate change is playing with respect to cyclone Yaas and other extremes of 2022 that have hit particularly South Asia 28 is in contrast to other devastating extreme events of 2021, notably the drought affecting Southern Madagascar. Over the 24 months from July 2019 to June 2021 rainfall was very low, estimated as approximately a 1-in-135 year dry event, and in the observed record only surpassed in severity by a severe drought in 1990–92. Based on a recent attribution study conducted by a large group of scientists 29 , the occurrence of poor rains as observed from July 2019 to June 2021 has not significantly increased due to anthropogenic climate change. Importantly, this result is consistent with previous research on droughts in the region 30 , 31 and in line with the IPCC’s Sixth Assessment Report 1 which does not expect changes in drought frequency and intensity at current warming levels. Only if global mean temperatures exceed 2 °C above pre-industrial levels an increase in drought is projected.

As described in Zachariah et al. 28 , temperatures during the pre-monsoon season 2022 across large parts of India and Pakistan were consistently 3–8 °C above average, breaking many decadal and some all-time records in several parts of India, including the western Himalayas, the plains of Punjab, Haryana, Delhi, Rajasthan and Uttar Pradesh. In Pakistan many individual weather stations recording monthly all-time highs in March. By April almost 70% of India was affected by the heatwave. In Pakistan, temperatures above 49 °C were recorded in Jacobabad in Sindh, and 30% of the country was affected by the heatwave. Towards the end of April and in May, the heatwave extended into the coastal areas and eastern parts of India. An attribution study 28 estimated that while still an extreme event today, this heatwave would have been extremely rare without climate change but is expected to very regularly in a 2C-world. This is remarkable as the Indian subcontinent has until as late as 2016 seen little increase in extreme heat in large areas 32 . The last 2 years have shown that even if maximum temperatures show small trends in some parts, this does not hold for average temperatures and trends in maximum temperatures are emerging 25 , 28 .

The disasters of 2021/22

The section above highlights that in regions, not new to disasters, the nature of these disasters has changed and will continue to do so with anthropogenic climate change.

While disasters are not new, it is important to stress that disasters occur when natural (and unnatural) hazards meet vulnerability. Countries such as India and Bangladesh have successfully implemented cyclone preparedness programmes as well as heat-action plans in many areas with significant reduction in loss to life. However, loss of livelihoods, property and other non-economic losses and damages (Boyd et al. 33 ) continue to exist as seen during Yaas and other disasters that affect this region every year. Vulnerabilities are constructed over a long period of time. For example, in South Asia, caste based discrimination continues to exist which deter certain groups of people in moving towards upward social and economic mobility. This has also been seen during disasters such as Cyclone Yaas where some upper caste families did not allow dalits to enter the evacuation shelters in Mayurbhanj district 34 . Many parts of Southern Bangladesh had faced some of the worst impacts during cyclones Aila in 2009 and Sidr in 2007 31 continue to struggle. During one of the author’s field visit to Sathkira in 2011, which was also one of the affected areas during Yaas, it was observed that disasters were considered part of an annual process and people living with risks continue to be caught between cyclones and tigers in Sundarbans 35 . This highlights, that reporting on longstanding vulnerabilities and understanding how they change with climate change is both crucial to understand today’s unnatural disasters.

In Madagascar, particularly the “le Grand Sud” region, although the meteorological drought has not been made more likely by climate change, it is a disaster with devastating consequences for the local populations. Madagascar ranks 164 on the Human Development Index, with signs of progress on the economy and political stability 36 . However, the drought potentially puts Madagascar’s slow progress in jeopardy as disasters tend to set back development processes. Unfortunately, this did not receive global attention for a long time. Like in many other places, the visible impacts of droughts such as food insecurity, malnutrition, hunger, agrarian distress are only occurring towards the end of a period of suffering, when preparedness that would have been possible earlier is hardly seen but immediate disaster response is required. Many updates from The Famine Early Warning Systems Network (FEWS NET) in 2020, highlight loss of wages, people on the move going back to the rural areas due to loss of work, and the drought situation being complicated with the pandemic restrictions 37 . The Southern region is poorly connected in terms of infrastructure 38 which makes it hard for humanitarian aid to reach, again highlighting a development problem. This drought spanning over a long period of time, complicated with the ongoing COVID-19 pandemic has thus further exacerbated people’s poverty (see Harrington et al. 29 ), including a lack of seeds to plant in the next season, potentially prolonging the cycle of poor harvests and extreme poverty well beyond the end of the physical hazard. Yet another case to highlight that disasters are rarely natural and that only taking the hazard as well as different aspects of vulnerability into account allows to identify the important drivers of disasters and consequently where to focus development and adaptation efforts. Below important dimensions of vulnerability, that ideally would be part of a systematic reporting, are highlighted.

Research on Bangladesh highlights that cyclone shelters also independent of a pandemic can be considered unsafe due to range of factors by different groups of people making evacuation difficult for particular demographics and in turn increasing the impacts on these populations 39 . Due to this security issue, women and girls may not consider going to the cyclone shelter as an option.

Taking gender as an example, a recent review highlighted rigid gender beliefs and gender roles of women, discriminatory policies and practices against women, and lack of women’s leadership in socio-economic and political environments influenced women’s capacities and vulnerabilities to disasters. A study from Ambovombe Androy in Madagascar 40 highlights social structures, existing norms, lack of importance to girl child education as some of the key factors contributing to vulnerability and these factors always have long-term repercussions, thereby increasing vulnerability to disasters. Another example, highlighted during the pandemic showed that men seem to migrate within the country for work and this could have made matters worse during the pandemic lockdowns and less availability of work.

In India, there has been huge impacts on household remittances and women headed households in the rural areas during the pandemic 41 . These impacts may have been seen in other places such as Madagascar too. It is very common during disasters to use existing savings to cope with immediate impacts. However, these savings may not last very long and affected populations may start borrowing from less formal sources such as local money lenders. Over a long period of time, this results in disaster debts which are a common phenomenon in India and Bangladesh. A recent study highlighted that micro-credit provides for immediate coping and may leave populations with “increased debt (microcredit and/or informal credit), and loan default, ‘trapping’ at-risk people in indebtedness” 42 . While gender dimensions and coping strategies that increase vulnerability are studied in disaster research, they are not categories commonly used in reporting on weather and climate-related hazards and disasters and are rarely considered sufficiently in adaptation strategies 42 .

Effective communication is key for successful disaster evacuation and disaster preparedness 43 , 44 . India and Bangladesh are hailed as disaster evacuation champions and have very successful examples of evacuating over a million people to safety. This has been a result of long-term investments in early warnings, community level communication and evacuation procedures. Early-warnings are also well established in the United States and Germany, both the heatwave and the floods in these countries in 2021 have been well forecast 45 . However, in Germany, these warnings did not reach the affected population, leading to a significant number of deaths in an economically prosperous region, highlighting, that the communication with the potentially affected population is at least as important having established early warning systems. While there is an increase in use of different social media during disasters, research shows that most of the focus remains on technology and less on the people impacted by disasters 46 .

In Madagascar, while there has been progress in making disaster risk management plans 29 , the response to the drought nationally and globally highlights that vulnerability reduction has not been a priority. Another example from South Asia, the Nepal floods of 2021 during the COVID-19 pandemic also sends the same message to address different forms of vulnerability 47 . Nepal was devastated during the 2015 earthquake, a textbook example of how disasters and development are inter-connected. Nepal is faced with landslides and floods every year and vulnerability remains a constant problem. Therefore, disaster risk reduction will not be effective with only disaster preparedness that does not address the root causes of vulnerability and lack of capacities 48 . This conclusion can also be drawn when looking at the heat wave in parts of India and Pakistan 28 which has shown that the same vulnerable populations and many others affected disproportionately during COVID-19 are also affected during the heatwave. Lack of access to basic health and other social protection infrastructure has shown to exacerbate disaster impacts.

The type of livelihood activity clearly determined people’s exposure to heat and the lack of choice to escape the heat is a sign of vulnerability contributing to risk. Communities dependent on agriculture were worst hit due to low crop yield. Further, the heatwave also had far reaching compounding risks such as fires and energy crisis (Zachariah et al. 28 ). We need better disaster reporting and documentation on heatwaves as most heatwave deaths go under reported 49 . Much more work needs to be done for heat action plans to be effective across the region and in many other parts of the world. This does not only hold for heatwaves in the global South but also the global North. Highlighted by Human Rights Watch 50 , Canada was not prepared to protect the most vulnerable part of the population from the extreme heatwave 2021, similarly during the 2022 heatwave in the UK 51 , economically poor people suffered the most severe impacts as London is a city where the urban heat island effect is particularly unequal affecting lower-income neighbourhoods far worse than the rest of the city 52 .

A discussion on disaster governance and vulnerability to disasters is not only about the impacts seen but also about the factors that lead to these impacts 4 , 53 . Lack of disaster-related insurances, insufficient compensation to rebuild livelihoods makes disaster recovery a never ending process of disaster risk (re)creation; and further marginalisation. For example, all disasters in 2021 occurred while countries were also going through the COVID-19 second or third wave which made disaster evacuation and relief challenging. All disasters of 2022 occurred in countries where health-services and other social infrastructure was severely weakened by the pandemic.

The example of Germany shows economic prosperity alone is no guarantee for low impacts. Similarly not for low vulnerability as in the UK or US where inequity within country is high. The disaster-development nexus continues to be a huge challenge as most of the discussions within disaster risk management continues to be around disaster response and/or on the natural hazard component. Discussions around the Sustainable Development Goals continue to remain a rhetoric and isolated from reporting on climate change and extreme weather. Research shows that adaptation projects overlook important factors of vulnerability and also have create new forms of vulnerability 54 . All examples show that without reducing structural vulnerabilities, adaptation will not be efficient and not address what matters to people 55 . In all countries, including the champions, there is a long way to go in reducing structural vulnerabilities which make disaster impacts worse and thus needs to be central to any adaptation planning. For the latter, changes in the hazard vis a vis existing and changing risks and vulnerabilities are equally important.

Towards better extreme reporting

Better reporting can be done, even without dedicated studies needing to be developed for individual hazard events. The examples, e.g., the drought in Madagascar and the heat wave show that some comparably easy to access scientific knowledge 21 on the expected role of climate change in these very different events is available. While this does not replace attribution studies, the knowledge we have now goes a long way to avoid over and understating the role of climate change in disasters and can be used to inform messaging in the immediate context of the event, in particular to avoid focussing solely on the climate aspect of the disaster but similarly to avoid ignoring the human influence on the climate aspect 56 . This is crucially important as blaming disasters on climate or nature alone is not different to categorising them as “acts of god”, it ultimately takes agency and responsibility away from local contexts and hinders resilience building 4 . Similarly, ignoring climate change when it is in fact a major factor in the hazard has implications for loss and damage and climate justice in general 33 , 57 . This may lead to continued lack to attention to increase in losses and damages and lack of preparedness if events thought to be rare are not rare anymore.

2021 was a year that surprised many with high-impact disasters that led to a large death toll in countries like Canada and Germany. Repeated in 2022 by e.g., extreme heat in the UK, but also in India, Pakistan and Nigeria. Scientifically these extreme events were no surprises 58 but they hit unprepared populations, and many concluded these disasters to be new. However, while these examples are certainly partly caused by anthropogenic climate change, and thus having not entirely natural hazards as their driver, root causes of disasters are largely due to dimensions of socio-political inequities as shown in decades of disaster research. Depending on the region of the world, the type of hazard and the presence of other crises, e.g. the pandemic, the large inflation in 2022 the relative importance of individual drivers of disasters and their impacts can differ dramatically, and is often poorly understood as is exemplified through assessing the role of climate change above.

The 2022 extreme heatwave in the UK provides an example of how the provision of information on warnings for particularly vulnerable groups have led to a noticeably different reporting 59 , with governments and health agencies issuing warnings for specific groups that were widely reported in the media, including the right-wing press, even though some commentators were accusing the government of taking the heatwave too seriously. Figures  1 and 2 illustrate the result of the information from the em-dat expanded with information on climate change, demonstrating how relatively easily a global inventory on impacts of human-induced climate change could be achieved roughly following 7 , 60 . Other drivers of disasters could be systematically assessed in addition: was there early warning?; did the warning reach those most vulnerable?; who was affected the most and how often? What factors made a certain group of people more vulnerable and how? 61 Analysing and presenting this information, that often is available systematically, and including the dimensions of risk, preparedness, impact and response 1 , 60 , 62 will allow better reporting of disasters, a better understanding of the interplay between vulnerability and climate change and thus ultimately better adaptation.

Data availability

All data used are downloaded from em-dat. The SI details the criteria for including data in the tables and figures.

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Acknowledgements

We acknowledge funding from the H2020 project XAIDA with the Grant Agreement number 101003469.

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Friederike E. L. Otto

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EL Education Curriculum

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• ELA G5:M4:U1:L2

Launching Research of Natural Disasters

In this lesson, daily learning targets, ongoing assessment.

• Technology and Multimedia

Supporting English Language Learners

Universal design for learning, closing & assessments, you are here:.

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• ELA G5:M4:U1

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These are the CCS Standards addressed in this lesson:

• W.5.7: Conduct short research projects that use several sources to build knowledge through investigation of different aspects of a topic.
• W.5.8: Recall relevant information from experiences or gather relevant information from print and digital sources; summarize or paraphrase information in notes and finished work, and provide a list of sources.
• I can cite evidence from a source to support answers to my research questions. ( W.5.7, W.5.8 )
• Natural Disasters Research Note-catcher ( W.5.7, W.5.8 )

• Expert Group Natural Disaster signs by writing the name of each expert group natural disaster on a piece of paper: earthquakes, hurricanes, tornadoes, volcanoes, and tsunamis. Post in separate areas of the room.
• Group the Infer the Topic Resources as follows and post by the Expert Group Natural Disaster signs:
• Earthquakes: Resources 4, 5, 6, 17,
• Hurricanes: Resources 1, 2, 3, 18
• Tornadoes: Resources 7, 8, 15, 19
• Volcanoes: Resources 9, 10, 14, 21
• Tsunamis: Resources 11, 12, 13, 20
• Technology necessary for students to access the links provided on the Natural Disaster Video Links sheet (see Materials).
• Review the Independent Reading: Sample Plans in preparation for launching independent reading in the Closing (see the Tools page ).
• Post: Learning targets and applicable anchor charts (see Materials).

Tech and Multimedia

• Continue to use the technology tools recommended throughout Modules 1-3 to create anchor charts to share with families, to record students as they participate in discussions and protocols to review with students later and to share with families, and for students to listen to and annotate text, record ideas on note-catchers, and word-process writing.
• Work Time C: Students use web research to answer research questions. There is a page of links (Natural Disaster Video Links) provided for them to quickly locate the videos.
• Consider that YouTube, social media video sites, and other website links may incorporate inappropriate content via comment banks and ads. Although some lessons include these links as the most efficient means to view content in preparation for the lesson, preview links and/or use a filter service, such as www.safeshare.tv , for viewing these links in the classroom.
• Supports guided in part by CA ELD Standards 5.I.C.10 Important points in the lesson itself
• The basic design of this lesson supports ELLs by allowing them to choose which natural disaster they will research, develop their own research questions, and work closely with an expert group to conduct their research. The offering of choice and supportive group work will increase students' motivation and level of engagement as they research their natural disaster during this unit and across the module.
• ELLs may find it challenging to generate research questions before they have chosen a natural disaster to research. Remind them of the research they conducted in Module 2, and guide the process for developing questions for this module as much as possible. Additionally, ELLs may find it challenging to identify relevant information in their expert group video to answer the research questions (see Levels of Support and the Meeting Students' Needs column)

Levels of support

For lighter support:

• After adding unfamiliar vocabulary words to the Academic Word Wall during Work Time A, invite students to use each word in a sentence with context. This will support their understanding of each word, as well as provide additional context for each word for students who need heavier support.

For heavier support:

• Consider introducing students to the natural disasters and allowing them to decide which one to research prior to the lesson. Allow students to view the videos and review their notes before deciding. Invite them to prioritize two natural disasters to allow for flexibility when strategically grouping students during Work Time B.
• Multiple Means of Representation (MMR): In order to facilitate effective learning during this lesson, ensure that all students have access to the directions in each activity, and feel comfortable with the expectations. Vary the ways in which you convey expectations for each activity or task. Consider engaging in a clarifying discussion about the directions, or creating an outline of the steps for each activity.
• Multiple Means of Action & Expression (MMAE): Continue to support a range of fine motor abilities and writing need by offering students options for writing utensils. Alternatively, consider supporting students' expressive skills by offering partial dictation of student responses. Recall that varying tools for construction and composition supports students' ability to express information gathered from the text.
• Multiple Means of Engagement (MME): Throughout this lesson, students have opportunities to share ideas and thinking with classmates. Some students may need support for engagement during these activities, so encourage self-regulatory skills by helping them anticipate and manage frustration by modeling what to do if they need help from their partners. Consider offering sentence frames to strategically selected peer models. Recall that offering these supports for engagement promotes a safe learning space for all students

Key: Lesson-Specific Vocabulary (L); Text-Specific Vocabulary (T); Vocabulary Used in Writing (W)

credible, affect, experience, relevant (L)

• Module Guiding Questions anchor chart (begun in Lesson 1)
• Working to Become Ethical People anchor chart (begin Module 1)
• Performance Task anchor chart (begun in Lesson 1)
• Natural Disasters Research note-catcher (one per student and one to display)
• Natural Disasters Research note-catcher (example, for teacher reference)
• Academic Word Wall (begun in Module 1)
• Domain-Specific Word Wall (begun in Lesson 1)
• Vocabulary log (from Module 1; one per student)
• Expert Group Natural Disaster signs (to display; see Teaching Notes)
• Infer the Topic resources (from Lesson 1; to display)
• Natural Disaster video links (one per student and one to display)
• Independent Reading: Sample Plans (for teacher reference; see the Tools page )

Materials from Previous Lessons

New materials.

Each unit in the 3-5 Language Arts Curriculum has two standards-based assessments built in, one mid-unit assessment and one end of unit assessment. The module concludes with a performance task at the end of Unit 3 to synthesize their understanding of what they accomplished through supported, standards-based writing.

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Global Research on Natural Disasters and Human Health: a Mapping Study Using Natural Language Processing Techniques

• Published: 14 November 2023
• Volume 11 , pages 61–70, ( 2024 )

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• Xin Ye 1 &
• Hugo Lin 2  

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Purpose of Review

This review aimed to systematically synthesize the global evidence base for natural disasters and human health using natural language processing (NLP) techniques.

Recent Findings

We searched Embase, PubMed, Scopus, PsycInfo, and Web of Science Core Collection, using titles, abstracts, and keywords, and included only literature indexed in English. NLP techniques, including text classification, topic modeling, and geoparsing methods, were used to systematically identify and map scientific literature on natural disasters and human health published between January 1, 2012, and April 3, 2022. We predicted 6105 studies in the area of natural disasters and human health. Earthquakes, hurricanes, and tsunamis were the most frequent nature disasters; posttraumatic stress disorder (PTSD) and depression were the most frequently studied health outcomes; mental health services were the most common way of coping. Geographically, the evidence base was dominated by studies from high-income countries. Co-occurrence of natural disasters and psychological distress was common. Psychological distress was one of the top three most frequent topics in all continents except Africa, where infectious diseases was the most prevalent topic.

Our findings demonstrated the importance and feasibility of using NLP to comprehensively map natural disasters and human health in the growing literature. The review identifies clear topics for future clinical and public health research and can provide an empirical basis for reducing the negative health effects of natural disasters.

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Global Research on Pandemics or Epidemics and Mental Health: A Natural Language Processing Study

Post-traumatic stress disorder and its associated factors among people who experienced traumatic events in east African countries, 2020: a protocol for systematic review and meta-analysis

Mental health and psychological impacts from the 2011 great east japan earthquake disaster: a systematic literature review, explore related subjects.

• Artificial Intelligence

Data Availability

The database used during the current study is available from the corresponding author upon reasonable requests.

Abbreviations

• Natural language processing

Posttraumatic stress disorder

Non-negative matrix factorization

Latent Dirichlet allocation

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Ye, X., Lin, H. Global Research on Natural Disasters and Human Health: a Mapping Study Using Natural Language Processing Techniques. Curr Envir Health Rpt 11 , 61–70 (2024). https://doi.org/10.1007/s40572-023-00418-3

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So, what's the difference between "weather" and "severe weather"? Is it just how hard the wind is blowing? Is it just thunder and lightning? Well, it can be some or all of those things. In this episode of Crash Course Kids, Sabrina talks to us about what makes severe weather and how it interacts with the geosphere and biosphere.

Weather-related disasters are exponentially increasing. In fact, two-thirds of Europe could be affected by an extreme weather event by 2100, according to a study published in the  Lancet Planetary Health journal on 4 August. In the 72 hours since, this year's world's strongest storm , Typhoon Noru pounded Central Japan, causing more than 400 flights to get cancelled.Landslides crippled Northern Italy and Southwest China following extended heatwaves Meanwhile, wildfires raged in  Western Greenland, an occurrence so rare that The European Union Earth Observation Programme has no data on  similar activity in this region. \"At this time, this appears to be unprecedented.\"

What's the difference between a hurricane, a typhoon, and a cyclone? Storm Shield Meteorologist Jason Meyers explains. They're all just different names for the same thing. In the Atlantic Ocean and the Northeast Pacific - basically the waters surrounding the United States - we call them hurricanes. In the Northwest Pacific near Asia - it's a typhoon.

In the South Pacific and the Indian Ocean, it's called a cyclone. The only difference between any of these storms is the direction they spin. Storms in the northern hemisphere spin counter-clockwise, and they spin clockwise in the southern hemisphere. All of these storms use the same ingredients to form - a weather disturbance, warm tropical oceans, moisture, and relatively light winds.

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Natural disasters: Conducting research, supporting affected labs December 6, 2017

Harvey … Irma … Maria … hurricanes that won’t be forgotten any time soon. And, although they don’t have names, let’s not forget the Mexico City earthquake in September and the northern California wildfires in October. We know that the human, environmental, and economic costs of natural disasters are high. Studies by the Environmental Protection Agency show that some extreme weather events such as heat waves and large storm systems are occurring more frequently now than in the past—and this trend is expected to continue.

As we watched these disasters unfold on the news, we saw that people with health problems face particular challenges. Individuals with chronic conditions such as kidney disease or COPD depend on electricity for dialysis machines or oxygen concentrators. People with mobility limitations may have trouble evacuating quickly. And, regardless of their physical health status, many, many people will suffer from psychological issues caused by the loss of property and possessions—and most importantly—of a loved one.

For older adults, such challenges during a natural disaster can be compounded by income and disability status. For example, the deaths of 14 individuals living in a Hollywood, Florida, nursing home from exposure to prolonged extreme heat in the aftermath of Hurricane Irma have focused particular attention on how to best help older people who live in nursing homes and similar settings before, during, and after natural disasters.

What can research tell us about natural disasters and aging?

The shock of these nursing home deaths tells us that formal care is at times significantly deficient in preparation for disasters, with terrible consequences. Yet, a much broader set of issues confronts us as we grapple with the difficulties that extreme weather presents to older adults. How can we better understand the social, psychological and biological pathways through which these extreme events affect health? What are the paths for resilience and recovery?

One recent study found that older adults exposed to Hurricane Sandy in 2012 experienced steeper increases in pain and functional limitations than those who were not exposed. Another study partially supported by the NIA, found that the severity of housing damage people experienced after the 2011 Great East Japan Earthquake and Tsunami was associated with elevated dementia risk. A third, which also received NIA support, examined the relationship between evacuation before 2008’s Hurricane Gustav and mortality among people with dementia and found that evacuation led to more deaths than staying put.

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Conducting Science in Disasters: Recommendations from the NIEHS Working Group for Special IRB Considerations in the Review of Disaster Related Research

Joan p. packenham.

1 Clinical Research Branch, National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, North Carolina, USA

Richard T. Rosselli

2 Social & Scientific Systems, Inc., Durham, North Carolina, USA

Steve K. Ramsey

Holly a. taylor.

3 Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA

4 Johns Hopkins Berman Institute of Bioethics, Baltimore, Maryland, USA

Alice Fothergill

5 Department of Sociology, University of Vermont, Burlington, Vermont, USA

Julia Slutsman

6 Office of Research Regulatory Affairs, Children’s National Medical Center, Silver Spring, Maryland, USA

7 Department of Pediatrics, George Washington University, School of Medicine and Health Sciences, Washington, DC, USA

Aubrey Miller

8 Office of the Director, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, USA

* J.S. was affiliated with the National Institutes of Health Clinical Center, Department of Bioethics, at the time the manuscript was initiated.

The authors declare they have no actual or potential competing financial interests.

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Research involving human subjects after public health emergencies and disasters may pose ethical challenges. These challenges may include concerns about the vulnerability of prospective disaster research participants, increased research burden among disaster survivors approached by multiple research teams, and potentially reduced standards in the ethical review of research by institutional review boards (IRBs) due to the rush to enter the disaster field. The NIEHS Best Practices Working Group for Special IRB Considerations in the Review of Disaster Related Research was formed to identify and address ethical and regulatory challenges associated with the review of disaster research. The working group consists of a diverse collection of disaster research stakeholders across a broad spectrum of disciplines. The working group convened in July 2016 to identify recommendations that are instrumental in preparing IRBs to review protocols related to public health emergencies and disasters. The meeting included formative didactic presentations and facilitated breakout discussions using disaster-related case studies. Major thematic elements from these discussions were collected and documented into 15 working group recommendations, summarized in this article, that address topics such as IRB disaster preparedness activities, informed consent, vulnerable populations, confidentiality, participant burden, disaster research response integration and training, IRB roles/responsibilities, community engagement, and dissemination of disaster research results. https://doi.org/10.1289/EHP2378

Introduction

Public health emergencies and disaster events have challenged the world’s preparedness and response capabilities for decades ( Figure 1 ). Since the attack on the World Trade Center in 2001, U.S. government agencies have redoubled their efforts to strengthen national preparedness, response, and recovery. With this national multiagency effort and continued exposure to new public health emergencies and disasters, the field of disaster research has evolved and has become commonplace in the post-disaster setting.

Timeline of major global public health emergencies and disasters, 2001–2016.

Figure 1 is adapted with permission from Lurie et al. ( 2013 ). We modified it significantly by extending the timeline, formatting color, and stratifying disasters by international and domestic.

From a government agency perspective, disaster research is the study of individual, community and organizational preparedness, response, and recovery from a broad range of disaster types. Disaster research is essential to understanding how to prepare for and respond to catastrophic events such as hurricanes, earthquakes, disease outbreaks and pandemics, hazardous material spills, and large-scale acts of terrorism, as well as understanding their impact on human health.

A unique feature of most disaster studies is the urgency of initiating data collection soon after the event to capture ephemeral baseline data that may be lost or subject to recall bias if collected later. Although the value of well-designed research studies in the immediate aftermath of disasters is recognized, there remain significant challenges that must be addressed to facilitate their administration. Some key challenges include time pressures related to the development of protocols and study materials, acquisition of rapid funding to support research work, concerns of the study team interfering with life-saving disaster response activities, and compromising a frail community ( Lurie et al. 2013 ; Miller et al. 2016 ).

Despite its recognized value, research involving human subjects after disasters may pose ethical concerns ( Ferreira et al. 2015 ; O’Mathúna 2009 ). For example, the lack of coordination across investigators conducting research after a disaster can result in survivors being approached to join research by multiple research teams asking similar questions and requesting duplicative sample collections. In addition to the burden this may place on survivors, it can lead to unnecessary confusion when representatives from aid organizations offering direct assistance are in the field at the same time ( Taylor 2016 ). Most importantly, concerns about the vulnerability of prospective disaster research participants have been raised and evaluated ( Macklin 2014 ; Levine 2004 ).

Although the Code of Federal Regulations (45 CFR Part 46—Protection of Human Subjects; DHHS 2009 ) does establish research protections for certain groups such as children, prisoners, women, and fetuses, there is no explicit protection for potentially vulnerable disaster survivor research participants. These human subject concerns led the National Institute of Environmental Health Sciences (NIEHS) to create an initiative to consider how institutional review boards (IRBs) can play a role in the preservation of ethical standards in the conduct of disaster research.

Objective and Approach

To address ethical and regulatory challenges in the oversight of post-disaster research, the Office of Human Research Compliance at NIEHS formed the new Best Practices Working Group for Special IRB Considerations in the Review of Disaster Related Research, as part of a larger effort at the National Institutes of Health (NIH) to enhance research oversight capacity after disasters. This effort, called the Disaster Research Response (DR2) program ( Lurie et al. 2013 ; Miller et al. 2016 ), began as a trans-NIH initiative in 2013 with the aim of developing a national framework to guide and facilitate research on the medical and public health aspects of disasters and public health emergencies. The working group was officially formed in September 2015 with the goals of exploring factors relevant to potential research participation in disasters and preparing IRBs for the review of disaster research protocols.

The multidisciplinary working group consisted of 60 members from 23 U.S. states who were recruited through a nomination process that sought to assemble a diverse group of stakeholders, including academic researchers; bioethicists; disaster responders; local, state, and federal officials; disaster survivors; community advocates; and IRB/regulatory experts, and officials. The diverse nature of the group reflects the fact that disaster research is often a collaborative venture and the recognition that complex disaster issues cannot be adequately addressed through the lens of a single discipline but requires multidisciplinary expertise ( NRC 2006 ). The multi-sector working group was formed with the objective of developing IRB disaster-related research recommendations for the human research protection, IRB/regulatory, and disaster research, and response communities.

At a meeting in July 2016, the working group was charged with addressing four overarching specific aims:

• 1. Preparing IRBs for the review of disaster research protocols
• 2. Exploring unique factors or heightened concerns as it relates to potential research participants and communities affected by disasters
• 3. Identifying participant burden for populations after disasters
• 4. Outlining duties and considerations of the IRB in the review of research involving disaster-affected communities.

Breakout groups of participants were given a different disaster scenario and disaster research case study, and all groups were asked to react to the same set of discussion questions. The disaster scenarios included earthquake, terrorist attack with detonation of a radiological dispersion device (i.e., a “dirty bomb”), hurricane, pandemic influenza outbreak, and a toxic industrial chemical spill. The disaster scenarios were based on the Planning Scenarios developed by the Homeland Security Council in partnership with the Department of Homeland Security ( Homeland Security Council 2006 ). The case studies that followed the scenarios were hypothetical, condensed disaster research protocols that were designed to be implemented during the immediate response stage of a particular disaster.

Major thematic elements from these discussions were collected and documented as 15 recommendations of the working group. Here we provide the recommendations as a framework and guidance for IRBs engaged in the review of disaster research protocols.

Working Group Recommendations

Recommendation 1: prior to consent, prospective participants should be asked, to the extent feasible, about unmet needs and provided assistance including referrals and resources to reduce risk and maximize benefit.

In the immediate aftermath of a disaster, survivors are often left behind with acute physical and mental health needs. Additionally, disasters can cause chronic impacts that impair social and economic stability including loss of employment and the dissolution of social networks. It is imperative that the life-sustaining and essential needs of potential research subjects are met for them to have adequate capacity to make a voluntary decision about enrollment in research.

Researchers may be the first outsiders to face a disaster survivor, and they therefore should be trained in this regard and should identify unmet needs created by the disaster—for example, asthmatics and diabetics who no longer have access to their medication, or renal patients who are cut off from their dialysis center. Researchers who encounter urgent concerns among survivors have a responsibility to immediately notify the appropriate response officials. Researchers also should be prepared to provide participants with information on official disaster relief resources that are available (e.g., location of Red Cross tent, FEMA assistance centers) as well as referrals to local medical and/or mental health providers.

Although referrals and resources could provide a benefit to potential participants, research should not interfere with potential research participants’ efforts to meet their survival-related needs. Critical unmet needs must be the priority over enrollment in research.

Recommendation 2: Close Monitoring of the Consent Process Is Key to Address Any Misconceptions about the Research

IRBs should ensure close monitoring of the consenting process during recruitment in disaster studies, especially in the immediate aftermath of a disaster. Research teams must establish a standard plan (e.g., which may include a capacity or competence assessment screening questionnaire) for determining the decision-making ability of disaster-affected research participants to provide informed consent. As a precaution to eliminate confusion concerning the exchange of disaster aid for participating in research ( Ahmad and Mahmud 2010 ), consent forms may include a section requiring the participants to initial for indication they understand that they are participating in research and that their participation in the study is independent of disaster aid administered by local, state, or federal agencies or other entities.

Additionally, research teams should distinguish themselves from responders by wearing vests, shirts, hats, and the like with clear labeling to establish their independence from the official responder community and clearly articulate to potential subjects that they are researchers asking them to engage in an optional research activity.

As with all clinical studies, participants should be reassured throughout the consent process that they may opt out of the research at any time, and the process of opting out should be discussed with them. Consistent with good clinical practice, researchers may consider re-consenting participants weeks to months after enrollment as an additional tool to ensure ongoing maintenance of a robust informed consent process and remind participants of the voluntary nature of study participation, especially for those who enrolled during the initial response phase to the disaster.

Recommendation 3: IRBs Should Guard against Any Reclassification of Minimal Risk Studies Due to the Establishment of New Post-Disaster Norms, and Should Ensure Transparency on Risks and Benefits of Research

When the probability and magnitude of harm anticipated in the research is not greater than those ordinarily encountered in daily life, the research is properly classified as minimal risk. Because disasters can establish new daily norms, one might assume that an IRB could adopt a relative standard for minimal risk studies established in their wake. However, it is inappropriate to tolerate increased research risks even in post-disaster settings where a “new normal” has been established.

There is a strong need for transparency in the research enterprise and clear identification and delineation of all potential risks and benefits of participating in a disaster-related study. Additionally, investigators should make it clear to potential participants, in the consent form and during the consent process, when the research offers no direct benefit. Researchers may want to consider a suitable level of remuneration commensurate with research participant time and effort and pay special attention to avoiding undue inducement under extreme post-disaster circumstances.

Recommendation 4: Research Teams Should Ensure Private Areas to Conduct Study Procedures to Minimize Risk of Confidentiality Breaches

Research procedures conducted in the disaster field may be out in the open because of damage to buildings and the set-up of temporary shelters. The loss of confidentiality may be particularly damaging in disaster studies when the release of personally identifiable information can create a long-lasting stigma of victimhood and potential discrimination experienced by survivors ( Harada et al. 2015 ). Research participants may also be concerned about the disclosure of sensitive medical information to their employers and/or insurance companies (e.g., disaster workers who participate in longitudinal research related to onsite exposures may potentially be banned from current or future work sites because their employer deems them unfit for deployment).

To address privacy and confidentiality issues, research teams should plan in advance how they would assemble private areas to conduct interviews, examinations, or other study procedures. Additionally, researchers may consider applying for a Certificate of Confidentiality issued by the National Institutes of Health, which may serve to protect identifiable research information from forced disclosure and provide additional reassurance to research participants that their research data will be kept confidential. Although there have been rare legal challenges to a Certificate of Confidentiality that have resulted in the loss of confidentiality ( Beskow et al. 2008 ), there is substantial evidence that these certificates fulfill their intended purpose ( Wolf et al. 2015 ).

Recommendation 5: Encourage Research on Groups (as Defined in 45 CFR 46 Such as Pregnant Women and Children) That Require Special Protections per Human Subjects Protection Regulations. Disaster Research Should Also Be Encouraged for Members of Vulnerable Groups That Are Underrepresented in the Disaster Research Literature Such as Women, Racial/Ethnic Minorities, and Elderly and Disabled Populations

Researchers should develop new strategies to overcome the perceived barriers to the conduct of disaster research with groups that require special protections or who may have unique vulnerabilities. Valuable, informative research data may be lost if studies do not include these populations in their disaster studies. This is especially true when conducting research to assess behavioral and mental health outcomes. Indeed, there is mounting evidence that members of vulnerable groups may experience significant long-term mental and physical consequences following disaster events ( Lai et al. 2014 ; King et al. 2012 ).

Justice demands that research be carried out for the benefit of the population as a whole; therefore, systematic exclusion of protected or vulnerable groups from disaster research studies should be avoided ( Mastroianni et al. 1994 ). Failure to include these groups leaves a knowledge gap in our understanding of the impact of disasters across the entire population.

If the inclusion of one or more protected groups introduces unacceptable risks, researchers must justify why they are appropriately excluded from the research. IRBs must be aware of this knowledge gap and question whether such groups are unfairly excluded (e.g., due to perceived regulatory burdens rather than actual increased risks of participation in research procedures) from disaster research proposals. In situations when there is no clear rationale to exclude, IRBs must require research teams to outline a plan for conducting outreach and recruitment of such underrepresented groups into the study.

Recommendation 6: Minimize Participant Burden Associated with Multiple Duplicative Studies in the Field through the Development of a Registry for Disaster Research Projects

Survivors of disasters are often approached by many investigators, all seeking the same or similar information ( IOM 2014 ). This can result in survey and specimen collection fatigue and an overall increase in participant burden ( IOM 2014 ). A coordinated effort among researchers and funders could reduce duplication. One potential solution is the creation of a registry of disaster research projects to centralize and make more transparent the overall disaster research enterprise. Although development of such a registry is not an IRB function, it is consistent with the mission of the IRB to identify potential risks that may act to increase participant burden.

Federal agencies and funders must play a leadership role in organizing such efforts by linking funding decisions to unique disaster research needs. An open and transparent database of disaster research studies, similar to ClinicalTrials.gov, would allow a central point for funders and government agencies to list disaster-related projects and requests for funding opportunities, reducing overall duplication.

Recommendation 7: IRBs That Are Likely to Receive Disaster Research Protocols for Review Should Engage the Disaster Researcher and Responder Community Prior to Disaster Events

Proactive engagement between IRBs, principal investigators (PIs), and the responder community may overcome some barriers to the timely review of disaster research protocols. Examples of engagement provided included inviting first responders and PIs to IRB trainings and meetings, securing responders with disaster expertise as ad hoc consultants to the IRB as a resource in the review of disaster research protocols, and setting up use agreements between IRBs and response agencies to ensure collaborative engagement during a disaster. Additionally, any perception of an antagonistic relationship between PIs and IRBs could be improved by proactive pre-disaster collaborative engagement.

Recommendation 8: Disaster Researchers Should Consider the Development of Pre-event Generic Protocols for Provisional Approval by Their Local IRB. IRBs May Consider the Use of “Contingent Approval” Status for Time-Sensitive Disaster Studies

Development of modular template protocols prior to disasters would facilitate protocol coordination and submission for approval after a disaster. A modular protocol would be one that is sufficiently flexible to fit a range of potential disaster scenarios. Activation of specific modular components that match the type and magnitude of the disaster and research interests could allow researchers to enter into the disaster field faster for time-sensitive disaster studies.

The NIH DR2 program has developed such a protocol (i.e., Rapid Acquisition of Pre- and Post-Incident Disaster Data—RAPIDD) for the study of disaster workers, and the NIEHS IRB provisionally approved it in May 2015 ( Miller et al. 2016 ). The IRB preapproval of RAPIDD as an advancement in disaster research can be emulated in other jurisdictions. Indeed, RAPIDD has already been used as a model to develop such protocols at the University of Iowa and the University of Texas Medical Branch.

Due to the variability that exists with different types and magnitudes of disasters, and depending on when the researcher wants to enter the disaster field, monitoring disaster research implementation in near real-time may help ensure the protection of research participants. IRBs are recommended to contingently approve disaster research protocols with the provision that the research team would report back to the IRB early in the implementation process and follow a fixed time schedule outlined by the IRB regarding any field related concerns or unanticipated issues. Additionally, an IRB may ask for the team to submit a continuing review report more frequently than the once a year required by federal regulations.

Recommendation 9: Outsource Disaster Research Protocols to Specialized IRBs or Designate a Specialized IRB for Review of Disaster-Related Research

IRBs should determine whether they have the appropriate expertise, review experience, training, and resources to properly review time-sensitive disaster-related research protocols. If an IRB determines that it lacks any of these elements, an alternate IRB with more disaster-related review experience should be made available when needed. An expansion of that idea could be the establishment of local or regional IRBs to act as specialized bodies for the review of disaster research protocols; inexperienced IRBs could then set up prepackaged reliance agreements with such entities. An example of such an entity is the Public Health Emergency Research Review Board (PHERRB), which has been put in place by the U.S. Department of Health and Human Services (DHHS) and NIH to serve as a single IRB exclusively for public health emergency research ( Lurie et al. 2013 ). Generally, the PHERRB may only be used for protocols that are conducted, supported, or regulated by HHS; that are subject to 45 CFR 46; and that require multiple IRB review.

Recommendation 10: IRBs Should Develop Disaster and Community Profile Templates to Be Used by Research Teams to Gather Contextual Information to Guide IRB Review and Decision Making

Disaster and community context is essential for IRBs to make informed decisions on disaster research protocols. IRBs should develop templates that would be populated by disaster researchers to provide the board with essential information about the disaster context. This template should include information on affected neighborhoods, morbidity and mortality associated with the event, post-disaster hazards and risks, and evacuation patterns among other variables. The template could also include detailed information on the community targeted for research (e.g., demographics, influential community groups, functional public health or medical infrastructure).

Recommendation 11: Researchers Must Be Aware of a Disaster’s Contextual Factors to Determine How They Impact Their Studies and to Optimize Timing of the Research Activities to Minimize Any Additional Stressors on Potential Research Participants while Maximizing Data Acquisition

Optimal timing of research in the post-disaster setting is of paramount importance. IRBs need to have access to near real-time data on the nature and impact of the disaster, as it unfolds, on the affected community targeted for research. Depending upon the type, timing, and magnitude of a disaster, there may be certain time periods after a disaster when prospective research participants may have multiple unmet needs and lack specific survival-related resources. During this time, research would be inappropriate, especially when it does not offer goods or services needed to meet survivors’ needs.

Disaster events that result in mass casualties and/or cause long-term disruptions in critical infrastructure (e.g., utilities, health care systems) are more likely to lead to periods of acute stress and uncertainty among survivors. When post-disaster settings become normalized, a window of opportunity for research may present itself. Conversely, periods of stress and uncertainty may increase over time, especially when social and economic systems continue to erode after a disaster or when the disaster evolves slowly (e.g., the Flint water crisis).

Recommendation 12: Encourage Mechanisms to Provide Pre-Disaster Local Community Knowledge to IRBs to Provide Context Specific to a Local Community

IRBs based in localities at risk for disaster should, in the pre-disaster phase, identify community advisory groups and stakeholders that represent the broader community and who can serve as ad hoc consultants. The engagement of existing community advisory groups is an effective avenue to understanding community concerns and pre-disaster context so that post-disaster context can be accurately assessed. IRBs should be sure to give adequate attention to disadvantaged socioeconomic populations that may be at risk for undue inducement or exploitation. Although it is recognized that community knowledge on IRBs has value for the review of all types of research, it is especially true in disaster studies when affected communities may be particularly challenged.

Because disasters are unpredictable in the communities they impact, preparedness efforts may only go so far. In the post-disaster setting, IRBs should make a concerted effort to contact community advisory groups in close proximity to the disaster to provide assistance in the review of a disaster research protocol. National organizations such as the Community-Campus Partnerships for Health provide access to community groups and academic institutions that can assist IRBs in their efforts. Disaster researchers can provide additional context by ensuring that their protocols include current information on the community to be studied and define strategies for gathering input from and ensuring participation by members of the community.

Recommendation 13: IRBs That Wish to Establish Competency in the Review of Disaster Research Protocols Should Create and Adopt a Disaster Research Training Program and Resource Guide; Disaster Research Teams Would Also Benefit from Emergency Response Training

Few IRBs have significant experience reviewing disaster protocols. IRB members should receive training on the basics of disaster management and specific human subject protection issues that can arise during the phases of disaster response and recovery as well as critical elements of IRB review for disaster-related research. PIs and their research teams could, in turn, be targeted for training on the regulatory aspects of the IRB review of disaster-related research.

IRBs also should strongly encourage PIs and research teams to receive emergency response training (e.g., Incident Command System, National Incident Management System) before entering the disaster field, particularly during the immediate aftermath and especially when the research requires formal integration with the emergency response structure, in part to avoid impeding disaster response operations. In the pre-disaster phase, collaboratively training PIs, IRBs, and disaster responders together would be beneficial for the entire disaster research enterprise. An excellent example of such preparedness training could be the development of tabletop and field exercises that simulate the planning and implementation of disaster studies in the midst of a disaster response.

Recommendation 14: IRBs Can Play an Important Role in Assessing the Feasibility of Disaster Research and Identifying Research That Might Not Lead to Generalizable Knowledge Due to the Disaster Context

The IRB review process includes an assessment of the feasibility of the research. If the research is unlikely to be successful in testing its hypotheses due to logistical constraints in the disaster field (e.g., lack of stable utilities, difficulty of ingress and egress to disaster sites), IRBs should require research teams to establish contingency plans and modify their research protocols. IRBs can also play a role in identifying and rejecting disaster research that may pose unacceptable risks to the study participants or the research team itself, or that clearly interfere with the life and property-saving work of disaster responders.

Recommendation 15: IRBs Should Assure That All Approved Disaster Research Specify and Confirm a Plan for the Timely Dissemination of Actionable Research Results Back to Key Stakeholders

One of the principles of ethical research is to provide results and feedback to stakeholders, and disaster research is no different in that regard ( Emanuel et al. 2008 ). IRBs should require researchers to develop a dissemination plan for the results that clearly describes how the data will be reported back to participants and the community throughout the life cycle of the study. The plan must ensure a timely report back and should consider specific entities such as community groups and health educators that can help translate scientific findings into lay language. Methods of dissemination should be carefully considered to optimize information exchange with the community and may include town hall forums, newsletters, and use of social media.

The burgeoning field of disaster research has placed greater demands on IRBs to ensure that the welfare and rights of human research subjects are protected during disaster studies. The review of disaster research protocols requires new tools and training for IRBs to assure the protection of disaster survivors from research-related harms. These recommendations are currently being evaluated and prioritized by NIH officials to determine the process for moving forward with implementation. Although disaster research conducted during response may be challenging, IRBs can play useful roles in achieving careful, balanced, thoughtful procedures that both consider the value of the research to advance science and reduce suffering—and that also consider the potential for harm based on the unique vulnerabilities of disaster survivors in a disaster aftermath.

Acknowledgments

The authors would like to acknowledge their fellow members of the NIEHS Best Practices Working Group Steering Committee: B. Clark, J. “Chip” Hughes, S. Phillips, C. Philput, D. Resnik, and D. Wendler. They also acknowledge the contributions of the following individuals who provided assistance to the project: D. Abramson, L. Baker, C. Bebelle, P. Cacioppo, M. Chien-Hale, L. Close, F. Daniels, C. Edwards, B. Elmore, C. Garrard, M. Hanna-Attisha, B. Hoffman, K. James, M. Justice, M. Kudumu, J. Lambert, E. Lee, E. O’Connell, R. Stephens, M. Stewart, V. Timmons, E. Walter, P. Windsor, C. Wladyka, and F. Yucel.

This research was supported by the Intramural Research Program and the Office of the Director of the National Institute of Environmental Health Sciences, National Institutes of Health.

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Facing Hazards and Disasters: Understanding Human Dimensions (2006)

Chapter: 5 interdisciplinary hazards and disaster research, 5 interdisciplinary hazards and disaster research.

T his chapter addresses the committee’s charge to examine challenges posed for the social science hazards and disaster research community due to the expectation that, like other relevant research community disciplines, it become a major partner in integrated research. Interdisciplinary research has been gaining prominence across all domains of science, engineering, and social sciences. The first section of this chapter draws from the literature on interdisciplinary research to discuss definitions, challenges, and factors in the success of interdisciplinary studies generally. The second section focuses on interdisciplinarity in hazards and disaster research, with particular reference to the social sciences. It emphasizes trends in research funding structures, the role of multidisciplinary research centers, and the importance of interdisciplinary research for addressing gaps in knowledge about hazards and disasters. The third section presents several exemplars of interdisciplinary research in this field and draws insights and lessons from them. The final section summarizes key findings and offers recommendations for supporting interdisciplinary research in the field.

DEFINITIONS

Various terms have been used to describe research that crosses traditional disciplinary boundaries. These include “interdisciplinary,” “multidisciplinary,” “trans-disciplinary,” and “cross-disciplinary.” The terms have

been used in multiple, confusing, and often conflicting ways. For example (Klein, 1990:55),

The popular term cross-disciplinary … has been used for several different purposes: to view one discipline from the perspective of another, rigid axiomatic control by one discipline, the solution of a problem with no intention of generating a new science or paradigm, new fields that develop between two or more disciplines, a generic adjective for six different categories of discipline-crossing activities, and a generic adjective for all activities involving interaction across disciplines.

Emerging consensus suggests that research can generally be characterized by the degree of interaction among disciplines. In order of increasing interaction, the spectrum ranges from “multidisciplinary” to “interdisciplinary” to “trans-disciplinary” research.

In “multidisciplinary” research, investigators representing different disciplines often work in parallel, rather than collaboratively (Klein, 1990:56):

“Multidisciplinarity” signifies the juxtaposition of disciplines. It is essentially additive , not integrative . Even in a common environment, educators, researchers, and practitioners still behave as disciplinarians with different perspectives their relationship may be mutual and cumulative but not interactive, for there is “no apparent connection,” no real cooperation or “explicit” relationships, and even, perhaps, a “questionable eclecticism.” The participating disciplines are neither changed nor enriched, and the lack of “a well-defined matrix” of interactions means disciplinary relationships are likely to be limited and “transitory.”

Indeed, Klein (1990) finds that most activities purported to be “interdisciplinary” are in actuality “multidisciplinary,” particularly research arising from problem-focused projects that intrinsically involve multiple disciplines. Multidisciplinary research in essence involves two or more disciplines, each making a separate contribution to the overall study (NRC, 2005).

“Interdisciplinary” research, in contrast, is often defined along the lines of referring to “integration of different methods and concepts through a cooperative effort by a team of investigators … [not referring simply to] the representation of different disciplines on a team nor to individuals who may ‘themselves’ incorporate different disciplines on a project themselves” (Rhoten, 2004:10). For example, a National Research Council (NRC) committee provided the following definition (Pellmar and Eisenberg, 2000:3):

Interdisciplinary research is a cooperative effort by a team of investigators, each expert in the use of different methods and concepts, who have joined in an organized program to attack a challenging problem. Ongoing communication and reexamination of postulates among team members promote broadening of concepts and enrichment of understanding.

Although each member is primarily responsible for the efforts in his or her own discipline, all share responsibility for the final product.

Most recently, the NRC’s Committee on Facilitating Interdisciplinary Research (NRC, 2005b:26) has conceptualized the term to refer not necessarily to the composition of a research team, but rather to the mode of investigation:

Interdisciplinary research (IDR) is a mode of research by teams or individuals that integrates information, data, techniques, tools, perspectives, concepts, and/or theories from two or more disciplines or bodies of specialized knowledge to advance fundamental understanding or to solve problems whose solutions are beyond the scope of a single discipline or field of research practice.

This view emphasizes that true interdisciplinarity goes beyond involving two disciplines to create one product and is characterized by the synthesis of research ideas and methods. In some cases, particularly fruitful interdisciplinary efforts actually lead to the evolution of new disciplines, for example, neuroscience (Pellmar and Eisenberg, 2000:3).

The term “transdisciplinary” is distinct in referring to approaches that are “far more comprehensive in scope and vision [than interdisciplinary approaches]” (Klein, 1990:65). Examples of trans-disciplinary approaches include structuralism, Marxism, and policy sciences. Klein (1990) contrasts nondisciplinary versus disciplinary positions in the discourse:

The nondisciplinary position is more scornful of the disciplines. Visible in the call to overturn disciplinary hegemony, it has figured in propositions of “transdisciplinarity,” revisionist theories of “critical interdisciplinarity,” and the “integrative”/“interdisciplinary” distinction that emerged in education and the social sciences. The disciplinary position holds that disciplinary work is essential to good interdisciplinary work (Klein, 1990:106).

For hazards and disaster studies, it is useful to make several other distinctions. First, collaborative research within the social sciences differs from collaborative efforts by social scientists with natural scientists and engineers. Both are important for addressing knowledge gaps. However, the challenges of the latter are particularly great, as discussed in the next section. Basic research can also be distinguished from more applied types of studies (e.g., problem-focused, evaluation, impact assessment) in which interdisciplinary research tends to be more prominent.

For purposes of this report, the committee adopts the following positions with regard to defining interdisciplinary research within the social science hazards and disaster research community:

The term interdisciplinary is used as an umbrella term to represent efforts usually conducted by research teams that involve ideas and methods from more than one discipline.

There exists a spectrum of degrees of interdisciplinarity. These range from parallel efforts with a research team comprising different disciplines, to sequentially linked efforts where outputs of one disciplinary research effort provide inputs to another, to fundamentally integrated research where multiple disciplines interact in mutually transforming ways from problem definition through to research design and execution.

Research efforts across this spectrum are needed and appropriate to different types of problems.

Interdisciplinary research is particularly challenging when it crosses boundaries between the social sciences and the natural sciences and engineering.

Interdisciplinary research is challenging, and the potential of interdisciplinary research is often unrealized. “Across the spectrum of higher education, many initiatives deemed interdisciplinary are, in fact, merely reconfigurations of old studies—traditional modes of work patched together under a new label—rather than actual reconceptualizations and reorganizations or new research” (Rhoten, 2004:6). In the area of global environmental change, for example, there have been frequent calls for alliances between natural and social sciences but few successes (Stern et al., 1992).

The literature has identified numerous barriers to interdisciplinary research. These range from intellectual issues such as attitude and communication to organizational issues such as academic structure and funding mechanisms, for example (Pellmar and Eisenberg, 2000:4-5):

Disciplinary jargon and cultural differences among disciplines are serious problems. Surveys show concerns among researchers about perceptions of interdisciplinary science as second-rate…. There are concerns that training in interdisciplinary fields will not prepare graduates for a career. The explosion of information within each scientific discipline raises concerns about how long it would take to attain expertise in one, let alone two or more, fields…. Because publications and successful grants are essential for promotion and tenure, the concern that interdisciplinary research will reduce the likelihood of first-authorship and of funding presents an additional obstacle.

Some of the most commonly cited barriers to interdisciplinary research include lack of funding, indifference or hostility on the part of researchers, and incompatibility with academic incentive and reward structures. In a

recent study of interdisciplinary research centers and programs, Rhoten (2004:6) found that the latter may be most significant and perhaps even underestimated: “The transition to interdisciplinarity and consilience does not suffer from a lack of extrinsic attention at the ‘top’ or intrinsic motivation at the ‘bottom,’ but, rather, from a lack of systemic implementation in the ‘middle’” as universities have implemented piecemeal and incoherent policies rather than systematic reforms.

While systemic barriers may be most significant for research centers and programs, in individual studies, difficulties typically relate to the failure of a research team to function collaboratively. This failure may derive from causes ranging from individual researchers devaluing the contributions of other team members to inability of the group to bridge culture gaps. As an example of the latter, the NRC (2005b:54) Committee on Facilitating Interdisciplinary Research points to the culture gap between mechanical engineers and software engineers in some early robotics research: “To the first group, a robot with adequate sensors had little need for software; to the second group, an abundance of mechanical sensors was a sign of inadequate software.”

For hazards and disaster studies, the challenges of interdisciplinarity are compounded by additional hurdles. These relate to the marginal position of the social sciences relative to the natural science and engineering fields, perceptions of applied research, and attitudes toward mission-oriented research. Traditionally, hazard and disaster studies have been dominated by natural science and engineering fields. Public policy in the United States has emphasized scientific and technological “solutions” (e.g., earthquake prediction, earthquake engineering, flood control dams) to the hazards problem. Social science accounts for a small share of research funding, activity, and personnel in the hazards and disasters field generally; as noted in Chapter 9 , there are approximately as many social scientists in the hazards and disasters field as there are volcanologists. This marginality means that when social scientists are involved in interdisciplinary research with scientists or engineers, their involvement typically resembles an after-thought or “add-on” to a primarily “scientific” or “technical” inquiry. This situation is changing, but it is still rare in collaborations with science or engineering for social science concerns and concepts to substantially shape the overarching research questions and approach (for an exception, see Box 5.1 ).

Additionally, hazards and disaster studies are commonly viewed as applied research aimed at “fixing problems” rather than basic science intended to advance knowledge. It is not uncommon for consultants to participate in these studies. The perception of applied research often marginalizes hazards and disaster research within the social sciences in relation to established academic disciplines, so that research is difficult to

publish in mainstream disciplinary journals. The severity of this problem does vary across the social science disciplines. In geography, and to a lesser extent sociology and urban and regional planning, there are well-established traditions of hazards and disaster studies, and researchers in these areas have gained disciplinary prominence and intellectual influence. In other disciplines such as economics, psychology, anthropology, and political science, it is virtually impossible to publish hazards and disaster studies in mainstream journals. This constraint creates a substantial disincentive for researchers, particularly young scholars seeking tenure, to conduct research in this field. Consequently, the number of researchers in the field remains small (see Chapter 9 ).

Similarly, interdisciplinary journals, while widely read and influential within the hazards and disaster research community, are not well recognized by reviewers in mainstream disciplines. Consequently, they are given less weight than disciplinary journals by reviewers who make recommendations regarding tenure and promotion. Interdisciplinary journals include both traditional outlets such as the International Journal of Mass Emergencies and Disasters and Risk Analysis , as well as new interdisciplinary journals such as Environmental Hazards and the Natural Hazards Review .

Moreover, many hazards and disaster studies involve funding or collaboration with agencies and organizations other than the National Science Foundation (NSF). Historically, organizations such as the Federal Emergency Management Agency (FEMA), state emergency management agencies, the U.S. Army Corps of Engineers, the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), and the insurance industry have supported social scientists conducting hazards and disaster research. As noted in Chapters 1 and 2 of this report, the Department of Homeland Security (DHS) has recently emerged as a major funding source for some types of disaster research. Studies not primarily supported by NSF are often viewed as “mission-oriented,” responding to the interests of mission agencies (e.g., terrorism) rather than to intellectual curiosity or other motivations of basic science. This circumstance further impedes publication and acceptance by mainstream academic disciplines.

FACTORS IN SUCCESS

These impediments can be overcome, and the accumulation of experience points to a number of factors that seem to be important in the success of interdisciplinary studies. These factors generally pertain to three dimensions of the research process: the research problem, the participants, and management. External support plays a role in each of these dimensions.

As noted by the NRC Committee on Facilitating Interdisciplinary Research, trends toward more interdisciplinary research are driven, in part, by the complexity of natural and social phenomena and the need to address societal problems. Accordingly, that committee found that interdisciplinary research “works best when it responds to a problem or process that exceeds the reach of any single discipline or investigator” (NRC, 2005:53). Problem-oriented research thus appears to be favorable for interdisciplinary collaboration in that the value of different disciplines’ contributions and the need for integrative conceptualizations can be focused and driven by the complexity and demands of the societal problem itself.

Characteristics of the participants and research group also appear to be important. Experience from the National Laboratories, which routinely engage in interdisciplinary research, suggests that the first key to success is to “involve only people who find unraveling a complex transdisciplinary issue at least as important as their own discipline” (Wilbanks, in NRC, 2005:55-56). Interdisciplinary research and collaboration requires interpersonal skills beyond subject matter expertise in disciplinary methods (Pellmar and Eisenberg, 2000:43).

The size of the research team is also influential to some degree; studies have found that small groups (e.g., centers with less than 20 affiliates) that

have stable membership tend to be most successful at interdisciplinary integration (Klein, 1990; Rhoten, 2004). As far as research centers are concerned (Rhoten, 2004:9):

[I]nterdisciplinary centers need not only to be well-funded but to have an independent physical location and intellectual direction apart from traditional university departments. They should have clear and well-articulated organizing principles—be they problems, products, or projects—around which researchers can be chosen on the basis of their specific technical, methodological, or topical contributions, and to which the researchers are deeply committed. While a center should be established as a long-standing organizational body with continuity in management and leadership, its researchers should be appointed for flexible, intermittent but intensive short-term stays that are dictated by the scientific needs of projects rather than administrative mandates.

Much of the literature has focused on issues such as communication, leadership, rewards, and teamwork strategies that relate to project planning and management. For example, the NRC (2005b:18-19) found that “key conditions for effective [interdisciplinary research] … include sustained and intense communication, talented leadership, appropriate reward and incentive mechanisms (including career and financial rewards), adequate time, seed funding for initial exploration, and willingness to support risky research.”

Communication appears to be critical for overcoming disciplinary preconceptions where they may hinder interdisciplinary collaboration. It has been noted that effective teamwork requires that team members have trust in one another’s skills and expertise, which is difficult to evaluate when working with researchers from other disciplines. Good communication is thus essential for the process to succeed (Pellmar and Eisenberg, 2000:43). The experience of the National Laboratories suggests the importance of discouraging “disciplinary entitlements” wherein “something is accepted as truth because one discipline says so.” It also stresses the need to overcome disciplinary stereotypes, replacing them with personal relationships that require substantial time to cultivate (Wilbanks, in NRC, 2005:55-56).

The literature on organizational psychology suggests that one of the inherent dilemmas in multidisciplinary groups concerns the contradictory consequences of member diversity. Diversity can exist in underlying attributes such as (task-related) knowledge, skills, and abilities, as well as (relations-oriented) values, needs, attitudes, and personality characteristics. Diversity can also exist in readily detectable attributes such as (task-related) educational level, disciplinary degree, and team tenure, as well as (relations-oriented) gender, age, and ethnicity (Jackson et al., 1995). Team members are selected to staff a project on the basis of readily detectable task-related attributes (e.g., educational level, disciplinary degree) because these are

assumed to provide a valid indication of a person’s underlying task-related attributes (e.g., knowledge, skills, abilities). However, some readily detectable task-related attributes are associated with underlying relations-oriented attributes (i.e., disciplines vary in the prevalence of people with certain values, needs, attitudes, and personality characteristics), and some readily detectable relations-oriented attributes are stereotypically associated with underlying task-related attributes (e.g., ethnicity and gender, are thought to be correlated with certain skills and abilities such as mathematics).

These incidental differences and stereotypic beliefs can have a significant effect on the performance of interdisciplinary projects where members of different disciplinary subgroups must work together. An obvious problem is that people’s confidence in some stereotypes exceeds those stereotypes’ predictive validity. A more fundamental dilemma is that diversity in underlying task-related attributes is an essential ingredient in innovation, adaptation, and performance (Jackson et al., 1995). However, diversity in underlying relations-oriented attributes can create friction, reduce normative consensus and cohesiveness, and cause members to leave the group. The positive effects of diversity can be attained and its negative effects minimized by promoting communication of information, cooperation in task performance, a positive work climate, and team cohesiveness.

Leadership is a second aspect of project management that is important in facilitating interdisciplinary research (Pellmar and Eisenberg, 2000:43):

Interdisciplinary research teams need leaders who understand the challenges of group dynamics and who can establish and maintain an integrated program. Leaders need to have vision, creativity, and perseverance…. To coordinate the efforts of a diverse team requires credibility as a research scientist, skill in modulating strong personalities, the ability to draw out individual strengths, and skill in the use of group dynamics to blend individual strengths into a team.

Effective leaders should foster an organizational climate that is conducive to interdisciplinary research. Organizational climate affects organizational effectiveness by influencing the degree to which team members are motivated to contribute toward group goals. It includes dimensions of leadership climate (leader initiating structure, leader consideration, and leader communication), team climate (team coordination, team cohesion, team task orientation, and team pride), and role climate (role clarity, but not role conflict or role overload) (Lindell and Whitney, 1995; Lindell and Brandt, 2000).

Reward structures are also important in facilitating interdisciplinary research. In particular, research team members should “know that their reputations will be affected by the success or failure of the enterprise—that everybody’s name will be on the product” (Wilbanks, in NRC, 2005:55-56). Rewarding performance at the group level, rather than at the individual

level, is an effective means of promoting cooperative goals (Ellis and Fisher, 1994).

Finally, a number of teamwork strategies have been found to be effective in the context of interdisciplinary research. Clarity is important with respect to roles, expectations, and authority, especially in terms of sharing of data and resources (Pellmar and Eisenberg, 2000). Role clarification and role negotiation enable team members to assess their mutual needs and expectations while also clarifying differences in their methodologies and ideologies (Klein, 1990).

Iteration is another strategy that has proven especially useful. “Iteration allows authors to become readers and critics by going over each other’s work in order to achieve a coherent, common assessment” (Klein, 1990:190). The team leader can facilitate the interaction by acting as a synthesizer.

More generally, cooperation can be enhanced by interdependence among subgroups’ tasks. Task interdependence within a project can be characterized in one of three ways (Thompson, 1967). First, subgroups have sequential interdependence when the initiation of one subgroup’s task is dependent on the completion of another subgroup’s task. Second, subgroups have reciprocal interdependence when their outputs cycle iteratively until the team product reaches an acceptable state. Third, subgroups have pooled interdependence when both depend on the same resources. This last type of interdependence is important because organizational subgroups operating in parallel are usually assumed to be independent, but they actually have pooled interdependence because all depend indirectly on the success of the others for the continued survival of the project as a whole. Thus, the interdependence of organizational subgroups will be extremely obvious when it is reciprocal and also quite obvious when it is sequential. However, project managers may need to emphasize the existence of pooled interdependence when project members mistakenly assume that they are completely independent of others. One of the most important consequences of cooperation on the reciprocally and sequentially interdependent tasks characteristic of many interdisciplinary research projects is that sharing of information and ideas, especially constructive discussion of alternative views, leads to greater productivity (Tjosvold, 1995).

Another strategy is to collaboratively involve subject matter experts (SMEs) in project management. In multidisciplinary research projects, no single person or even small group of persons has all of the knowledge needed to plan and implement the project. Thus, setting project objectives, identifying and scheduling tasks, and estimating resource needs requires collaboration among SMEs who are knowledgeable about all of the distinct areas to be addressed by the project. Similarly, SMEs from all areas must collaborate in organizing project staff, monitoring task performance, and adjusting resources or objectives in response to deviations from plans.

Successful collaboration among SMEs from the different functional areas is sometimes accomplished by augmenting the project manager with a project management team that actively contributes to project decisions. On small projects, the project management team comprises all project members, whereas on very large projects the project management team might consist of representatives from each functional area. If the members of the project management team have not worked together previously, they must accomplish a number of social tasks at the same time they are attempting to plan and implement the project. That is, according to McIntyre and Salas (1995), members must perform teamwork in order to accomplish task work . Task work requires project staff to learn enough about each other’s subject matter to develop a shared mental model of the project (Morgan and Bowers, 1995). This shared mental model must contain all of the elements needed for the project plan—project objectives, task schedules, and resource requirements. In a large project, it probably will not be possible for anyone other than the most interdisciplinary project personnel to develop a fully comprehensive mental model of the project; in an extremely large, complex project it probably will not be possible for anyone to develop a fully comprehensive mental model. Instead, project staff with the broadest scientific knowledge will have a detailed understanding of their own subject matter areas and the ways in which their areas interconnect with closely related areas. In addition, they would have a general understanding of other disciplines that do not link directly to their own. For example, a multidisciplinary earthquake center would be expected to have close linkages of earth scientists with structural engineers, structural engineers with planners, and planners with social scientists.

Finally, the literature on organizations suggests that group cohesiveness can be achieved in a number of ways (Ellis and Fisher, 1994). The first is through formulation of cooperative goals. The goals of individual team members are cooperative when they are positively linked, competitive when they are negatively linked and independent when they are unrelated. One of the easiest ways to establish cooperative goals is to reward performance at the group level, not at the individual level. A second method of achieving cohesiveness is to emphasize external threats. In the case of multidisciplinary projects, the threat of project failure raises the potential for mutual negative career consequences. A third way to achieve cohesiveness is for the group to rapidly achieve some visible goals. This can be accomplished if the team sets some easily attainable short-term goals that will provide early success experiences. Finally, cohesiveness can be enhanced by shared experiences, especially collaborative responses to difficult challenges such as preparing for external reviews.

INTERDISCIPLINARY TRENDS IN SOCIAL SCIENCE HAZARDS AND DISASTER RESEARCH

The NRC Committee on Facilitating Interdisciplinary Research (2005b:2) identified four fundamental forces that are driving the growth of interdisciplinary research:

the inherent complexity of nature and society,

the desire to explore problems and questions that are not confined to a single discipline,

the need to solve societal problems, and

the power of new technologies.

While these forces have long been influential for social science hazards and disaster research, recent trends toward interdisciplinarity can be ascribed to more proximate drivers. It is especially important to recognize the influence of the National Science Foundation in terms of research funding criteria as well as the earthquake engineering research centers.

Research Funding Structure

Interdisciplinary research has been gaining increasing emphasis from funding organizations, including NSF. Perceptions that there is little research funding for interdisciplinary studies appear to be unfounded, at least in recent years. One study (Rhoten, 2004:7) reported that

[W]e have found substantial evidence of extrinsic attention to interdisciplinary research in the discourses and resources of government agencies, policymakers, scholarly associations, and university administrators…. Of the $4.11 billion that the NSF requested from Congress for research and related activities in 2004, $765 million—a 16.5percent increase over 2003—has been earmarked for four priority areas all designated as interdisciplinary [including] Human and Social Dynamics…. In addition, private dollars are also being poured into interdisciplinary endeavors at unprecedented levels.

Many observers believe that research funding for interdisciplinary studies is not only well established but also likely to continue growing. This trend derives from the juxtaposition of stable or declining national budgets for research with a political climate that demands research expenditures be justified on practical, tangible grounds (Hackett, 2000). Even observers who are ambivalent about the merits of interdisciplinary research advocate acknowledging and taking advantage of its growing prominence (Hackett, 2000:259):

Very little is known about such initiatives…. In light of all this ignorance and uncertainty, it is difficult to embrace interdisciplinary initiatives. Yet they may be a lasting instrument of science policy, and the one area of real growth and opportunity. Our best option, then, is to proceed boldly but reflectively, giving such investments our whole-hearted support while thinking critically and systematically about their performance and consequences.

Human-environment interactions broadly defined, including hazards and disasters, have been a focus of numerous interdisciplinary initiatives at NSF in recent years. Some examples include initiatives for studies on Long-Term Ecological Research (LTER), including urban LTER, several centers for climate study, biocomplexity, human dimensions of global change, and Human and Social Dynamics (HSD). The latter in particular identifies “Decision making and Risk” as one focal area, and requires that research teams include at least one social scientist. Some “centers of excellence” being established by DHS have been directed to conduct interdisciplinary research, sometimes requiring a fairly prominent role for the social sciences.

Earthquake Engineering Research Centers

For social science hazards and disaster research, another important driver in interdisciplinary studies, particular with science and engineering, has been the NSF-supported earthquake engineering research centers, a major NSF contribution under the National Earthquake Hazards Reduction Program (NEHRP).

When the National Center for Earthquake Engineering Research (NCEER) was funded through NSF’s Directorate for Engineering in 1986, the aim was to promote multidisciplinary team research that would provide a more comprehensive understanding of earthquake hazards and how to cope with them. This was quite a novel idea at the time because what NSF sought was nothing less than the creation of a program of integrated research that included the most talented investigators from the earth sciences, engineering, and the social sciences. The notion was that researchers from these different disciplines would not merely work in parallel, as NSF grantees sometimes did in research carried out in individual and small group projects, but collaboratively. It turned out that it was particularly difficult to get the social scientists integrated into the NCEER program in this fashion, at least until some of the researchers that made up the engineering leadership began accepting the NSF vision and actually became champions of it. It helped, too, that some outstanding social scientists became members of the NCEER team, demonstrating the importance of the social sciences in developing a truly comprehensive understanding of earthquake hazards—that it wasn’t just about building design and performance.

NSF funding for NCEER lasted 10 years. With broad backing from the

earthquake research community, NSF funded three new centers in 1997: the Pacific Earthquake Engineering Research Center (PEER), the Mid-America Earthquake Center (MAE), and the Multidisciplinary Center for Earthquake Engineering Research (MCEER), which replaced and built on NCEER. As before, NSF charged the three centers with the task of conducting interdisciplinary research that included the social sciences, something that the larger earthquake research community had come to accept at least in principle since it encouraged NSF to continue supporting center-based research. Implementing this charge has remained a challenge in many ways, however, even with a multidisciplinary NSF staff providing oversight for the centers program and with multidisciplinary review panels participating in the periodic assessments of progress. Based on presentations to the committee by center leaders, as well as social scientists knowledgeable about the centers (including funded participants and external reviewers), MCEER has come closest to meeting NSF’s expectations for collaborative research. Perhaps a greater commitment on the part of its leadership is one factor, while another might be that as the successor to NCEER, it simply has had more time to make progress in that area.

It is evident that although the NSF mandate has been influential, it has not been sufficient to catalyze effective interdisciplinary research. Other factors, such as leadership and the duration of contact among researchers, have also been necessary for the development of trust and respect across the disciplines.

Table 5.1 provides some indication of the growth in interdisciplinary research involving the social sciences in the centers context. The table compares evidence of social science involvement in research activity at NCEER (1986–1994) and MCEER (2001–2004). Data pertain to the disciplinary

TABLE 5.1 Percentage of Publications by Disciplines of Authors, NCEER and MCEER

affiliations of authors and coauthors on papers in the centers’ Research Accomplishments publications covering the years indicated. The increase in social science research at the centers, particularly in interdisciplinary research, is evident. For example, social scientists were (co-)authors on only 8 percent of the NCEER papers, but 52 percent of the MCEER papers.

Funding for social science research has been similar at each of the three current centers (MCEER, MAE, and PEER). On average, the social sciences account for approximately 15 percent of research funding, varying from year to year in the range of 13 to 19 percent. At least one of the centers has indicated to the committee that it will continue to increase the social science share due to pressures from NSF site reviews (Bruneau, 2004; Dobson, 2005; May, 2005). The centers are supported with $2 million annual funding from NSF as well as substantial funds from industry and other sources. The centers thus represent a major source of interdisciplinary research funding and a locus of interdisciplinary research activity in recent years.

Importance of Interdisciplinary Research

The increase in interdisciplinary studies in social science hazards and disaster research reflects a growing consensus within the field about the importance of research problems that cannot be addressed through disciplinary studies alone. There have been numerous calls for interdisciplinary research. For example, at a recent NSF workshop on Integrated Research in Risk Analysis and Decision Making in a Democratic Society, one of the major conclusions reached by participants was: “To advance the basic science and increase the utility of risk analysis and decision science, it is necessary to foster interdisciplinary and multidisciplinary research that includes engineering, information sciences, natural sciences, and social sciences” (NSF, 2002:7).

This importance has also been cited with reference to the George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES). At a cost of more than $80 million, NEES is a major new initiative in NSF’s support for research on earthquake hazards. The focus of NEES is on laboratory experimentation and computer-based simulation. However, an NRC (2003b:125) committee charged with developing a research agenda for NEES cited the importance of collaboration between “scientists and engineers who will develop and test new theories on earthquakes, earthquake damage, and its mitigation” and “social and political scientists who will use the science and technology from NEES to develop better risk assessment tools, loss estimation models, and communication and teaching strategies to help enact and implement more enlightened policies on earthquake loss mitigation.”

The need for interdisciplinary studies was also emphasized in the Earth-

quake Engineering Research Institute’s (EERI) Research and Outreach Plan in earthquake engineering, a consensus document from the profession, which notes (EERI, 2003:29):

Many of the engineering and earth science research programs will benefit directly from [breakthrough technologies and opportunities identified in the Plan], but these efforts, by themselves, will not assure protection from loss. Translating knowledge to action continues to frustrate loss reduction efforts in this and other hazard mitigation efforts. A significant ground-breaking effort is also required to understand the underlying societal factors that contribute to vulnerability and inhibit efforts intended to reduce this vulnerability.

Recent advances in social science research hold particular promise in this regard. These include the challenging areas of risk perception and communication, societal inertia to change, decision making, effective fiscal instruments, and quantification of economic impacts. Consequently, a major component of this Plan is the complementary role of the social sciences, working in partnership with engineering and earth sciences, to achieve the goal of community resilience and protection from loss.

These calls for interdisciplinary research involving the natural sciences, engineering, and social sciences are not unique to the hazards and disaster field. Similar calls have been made in NRC and NSF reports on research agendas in environmental science. In environmental science, it is recognized that fundamental, disciplinary research in the natural sciences, social sciences, mathematics, and engineering is important and requires strengthening. At the same time, “present and future challenges include connecting across disciplines and scales, supporting synthesis studies and activities, more tightly linking science, technology, and decision making, and achieving predictive capability where possible” (Pfirman and AC-ERE, 2003:5). It has been noted that social science or human dimensions research, which supports as well as cuts across other scientific inquiry on global change, must involve both disciplinary and interdisciplinary approaches (NRC, 1999a). Environmental synthesis is needed “to frame integrated interdisciplinary research questions and activities and to merge data, approaches, and ideas across spatial, temporal, and societal scales” (Pfirman and AC-ERE, 2003:1).

Interdisciplinary research, moreover, requires new types of research groups, capabilities, educational frameworks, and forms of support. The NRC (2001) committee on Grand Challenges in Environmental Sciences found that no single discipline in environmental science could entirely capture how multiple driving variables affect environmental as well as human outcomes. It recommended new types of research teams and communities that can communicate and collaborate across the “gulf” that divides natural and social sciences. “These groups will require a large number of scientists

with broad, interdisciplinary perspectives, as well as an increased capability for cross-disciplinary collaboration among environmental scientists, who may develop more interdisciplinary orientations as a result” (NRC, 2001:71).

To this end, one NSF report has stressed the importance of adaptability (Pfirman and AC-ERE, 2003:6):

In this new era, imagination, diversity, and the capacity to adapt quickly are essential qualities for both institutions and individuals. This places a premium on the quality and evolutionary capacity of environmental research and education. In turn, the richness and complexity of interdisciplinary environmental research is creating the opportunity for more immediate and broad-based application of the results to human systems and problems.

These issues and recommendations resonate with the research needs in hazards and disaster research.

Interdisciplinary Research Needs

In discussing needs for interdisciplinary research, it is useful to consider specific examples and how they transcend traditional disciplinary boundaries. To do this, the committee begins with priorities outlined in the EERI (2003) Research and Outreach Plan prepared with support from NSF. As a further illustration, a type of research that is important, but often overlooked—evaluation research—is considered. Finally, and most importantly, the committee discusses the role of interdisciplinarity in the research priorities identified from the overview of research progress, gaps, and opportunities in the field that are identified in Chapters 3 and 4 .

As noted earlier, the EERI Research and Outreach Plan is a consensus document from the profession. It “provides a vision for the future of earthquake engineering research and outreach focused on security of the nation from the catastrophic effects of earthquakes” (EERI, 2003:5). Interdisciplinary collaboration is clearly needed to address several of the priority research tasks identified in the plan, including the following (EERI, 2003:38):

System level simulation and loss assessment tools —e.g., validation studies to calibrate the accuracy of loss estimation models, incorporating the full range of physical and societal impacts and losses for earthquake and other hazards;

Assessment of cost effectiveness of loss mitigation —e.g., definition of performance measures for lifelines and communities, comprehensive direct and indirect loss models, more in-depth demonstration studies (involving an integration of disciplinary approaches),

and examination of nonlinear adaptive behavior in complex organizations;

Financial instruments to transfer risk —e.g., studies to assess the efficacy of alternative risk reduction or transfer methods, analysis of benefits and costs to various stakeholder groups, analysis of complementary roles of mitigation and insurance, and analysis of safeguards against insurance industry insolvency;

Advanced and emerging technologies for emergency response and effective recovery —e.g., real-time loss estimation tools, remote-sensing technologies for damage assessment, advanced decision-support systems for response and recovery, and advanced communication and networking systems for response and recovery

Methodologies and measurement of progress in reducing vulnerability and enhancing community resilience to earthquakes —e.g., risk management cost-effectiveness methodologies and analyses, investigation of societal impacts of catastrophic earthquakes, research on decision making and earthquake risk perceptions, and research on implementation of risk management and earthquake mitigation programs.

These research priorities call primarily for interdisciplinary collaboration between social scientists and researchers in the natural sciences and engineering, although a few (e.g., decision making, risk perception) would also involve interdisciplinary research within the social sciences.

Another example of needed research that is highly interdisciplinary is evaluation research. Evaluation is the systematic assessment of the value and worth of a program, policy, project, technology or some other object. The goal of evaluation research is to provide feedback on the appropriateness and effectiveness of the object of concern. Objects can be evaluated before they are implemented to aid in decision making about a range of alternatives or after they have been implemented to determine processes or impacts. Evaluation can help measure costs and benefits, implementation issues, outcomes, lessons learned, and effectiveness.

Most programs dealing with the reduction of losses from hazards are not evaluated on a systematic basis. For example, the nation’s oldest and largest mitigation program is the National Flood Insurance Program (NFIP). In its 30 years of existence, the NFIP’s effectiveness has never been evaluated (Mileti, 1999b). Most other major federal hazard reduction efforts have never been systematically evaluated, including the multiagency National Earthquake Hazards Reduction Program, FEMA’s National Dam Safety Program, or the Urban Search and Rescue Program. In the absence of program evaluation, it is difficult to understand if risk reduction efforts are effective (see Box 5.2 ).

Of particular relevance to this committee’s charge is the role of interdisciplinary research in addressing research gaps that the committee has identified in assessing knowledge in the field. The research recommendations presented in Chapters 3 and 4 of this report are repeated in Table 5.2 . The table also indicates the types of studies required to address each of these research needs—whether they be disciplinary (social science) studies, interdisciplinary studies involving collaborations within the social sciences, interdisciplinary studies involving social science collaborations with natural sciences and engineering, or some combination of these types. For each recommendation, the table also indicates which type is the primary research need.

Table 5.2 shows that for all of the priority research recommendations identified in Chapters 3 and 4 , some degree of interdisciplinary inquiry will be necessary. Disciplinary research needs remain in the vast majority of the recommendations. However, in only 4 of the 19 recommendations are the key research needs disciplinary. The primary research need in 11 of the cases is interdisciplinary within the social sciences. In the remaining four recommendations, it involves collaboration with the natural sciences and engineering. The committee therefore concludes that although important disciplinary research needs remain, the trend toward more interdisciplinary research appears to be consistent with major research needs in the field. Rather than leaving behind important unanswered disciplinary questions,

TABLE 5.2 Research Recommendations and Role of Interdisciplinary Studies 1 , 2

this trend is necessary and should be encouraged. Moreover, the greatest needs are for interdisciplinary research of a type that is often overlooked—studies that integrate knowledge across various disciplines within the social sciences.

EXEMPLARS AND LESSONS

This section presents four successful examples of interdisciplinary research in hazards and disaster social science. These studies were selected by the committee to demonstrate various forms, advantages, and contributions of interdisciplinarity. They also provide specific insights into both the challenges faced by researchers engaging in interdisciplinary research and the key ingredients for overcoming these challenges.

The four studies summarized below represent different types of successful interdisciplinary research in social science hazards and disaster research. Three of these studies were supported to a large degree by NSF, primarily through NEHRP. In the first, a study of the economic impact of infrastructure failures in earthquake disasters, social scientists collaborated with engineers under the auspices of an NSF-supported earthquake engineering research center. In the second, a study of human casualties in earthquakes, social scientists and engineers collaborated through their own initiative, outside the context of centers. The third study, focusing on decision making for risk protection, represents a case of successful interdisciplinarity between

different fields within the social sciences. In selecting the fourth example, sustainability science, the committee looked outside the traditional boundaries of hazards and disaster social science research to find an instructive example of successful interdisciplinary research.

What Is Successful Interdisciplinary Research?

In the growing literature on interdisciplinary research, surprisingly little has been written on assessment. By what criteria should interdisciplinary research be judged to be successful? According to one former NSF program officer (Hackett, 2000:258),

It is difficult to know whether interdisciplinary initiatives return fair value for the money invested, and it is difficult to measure their performance against that of traditional, disciplinary activities. Partly this is a problem of yardsticks and perspective, with metrics of any sort of science performance hard to come by and with sharp differences in perspectives on the fundamental merit of any sort of interdisciplinary effort.

According to the NRC Committee on Facilitating Interdisciplinary Research, a successful interdisciplinary research program will produce outcomes that influence multiple fields and feed back into disciplinary research. It would also enhance research personnel, creating “researchers and students with an expanded research vocabulary and abilities in more than one discipline and with an enhanced understanding of the interconnectedness inherent in complex problems” (NRC, 2005:150).

For purposes of this report, the committee has adopted the following general indicators of successful interdisciplinary research:

It seeks to advance knowledge in ways not possible through traditional, disciplinary research (e.g., through questions addressed or methods used).

It involves substantive collaboration among a team of researchers with diverse expertise and training (including at least one social scientist).

It produces outcomes that are significant and influential.

While recognizing that interdisciplinary research can, in rare cases, be conducted by a single individual, the committee chooses to focus on the more typical cases involving a team of at least two researchers from different disciplines.

Exemplar: Modeling How Infrastructure Failures Impact Urban Economies

Interdisciplinary research, particularly collaboration between social scientists and engineers, has been a continuing focus of the earthquake engineering research centers supported by NSF through NEHRP. As noted earlier, NCEER, particularly in the latter years of its 10-year existence, was a pioneer for involving social scientists as researchers and members of its leadership structure. The three earthquake engineering research centers (MCEER, MAE, and PEER) that succeeded it, which are approaching the end of their NSF-supported tenures, all engage social scientists in their research programs to varying degrees. Integrating research across the social sciences and engineering has proven challenging, however, even in the facilitating context of these centers. The learning curve has been steep, and success has been mixed.

One of the earliest cases of social scientists collaborating with engineers in the context of these centers has also been one of the most successful. Since the mid-1990s, researchers at NCEER and its direct successor MCEER have been developing increasingly sophisticated methods for assessing the social and economic losses caused by lifeline infrastructure failures in earthquakes. Lifelines such as electric power, water, and transportation systems provide critical services to every sector of society. Disasters have repeatedly shown that lifelines are highly vulnerable to damage and cause serious, wide-ranging impacts when they fail. Yet these broader impacts have not been considered in other loss estimation models, most notably FEMA’s HAZUS™ model.

Assessing the societal impacts of lifeline outages is an intrinsically interdisciplinary research problem. It requires addressing many, if not all, of the elements and interactions of the conceptual model of societal response to disasters presented in Chapters 1 , 3 , and 4 (see Figure 1.2 ), including linkages between pre-impact conditions of hazard exposure, physical vulnerability, and social vulnerability with conditions of the specific earthquake, pre-impact interventions, and post-impact responses. In the case of economic impacts of a water delivery system, for example, researchers must assess not only the extent of physical damage, but also the spatial pattern of water outage, restoration plans, and outage duration, the spatial and sectoral distribution of impacted businesses; and the sensitivity of business activity to water outage. To address this problem, the NCEER-MCEER research team brought together expertise in structural and systems engineering, urban planning, sociology, and economics.

Some of the advances made in this research can be regarded as contributions by individual researchers to their home disciplines. For example, engineers developed new methods for conducting network flow analysis

under conditions of earthquake damage (Hwang et al., 1998). Sociologists conducted business surveys that greatly advanced knowledge of how businesses prepare for, respond to, and are affected by disasters. Economists developed new models for capturing the way businesses and economic sectors respond resiliently to disasters (Rose et al., 1997; Rose and Liao, 2005).

Each of these individual advances contributed to the integrative core of the project, a model that estimates not just physical damage to lifelines in earthquakes but also the consequent outages and economic impacts (Shinozuka et al., 1997, 1998; Chang et al., 2002). Integration consisted largely of sequential linkages. For example, systems engineering models produced maps of initial outage patterns. These outage maps were used in a restoration model to assess utility restoration over time. Outage and restoration data were integrated in a geographic information system (GIS) with spatial data on business locations to estimate economic activity at risk. Survey-based information on the differential vulnerability of various types of businesses was used to translate these estimates into expected loss outcomes. This collaboration provides an example of a type of interdisciplinary research in which the contributions of different disciplines are effectively and productively linked, without fundamentally transforming the nature of the research in each area.

The integrated model was developed as a simulation tool. This allowed characterization of uncertainty in the outcomes. It also enabled policy analysis through “what-if” exploration and comparison of intervention options ranging from pre-disaster structural mitigations to strategies for post-disaster restoration. The NCEER-MCEER model has been applied to case studies of electric power and water systems in Memphis, Tennessee, and Los Angeles, California. The original loss estimation framework has been expanded and refined to address community resilience to disasters (Bruneau et al., 2003; Chang and Shinozuka, 2004).

The degree of interdisciplinarity in this effort is evident in the research outcomes. The integrated model has been documented in numerous publications coauthored by engineers and social scientists. These include journal articles, conference presentations, center research reports, and a center monograph.

The more intangible successes of this interdisciplinary research are also noteworthy. The NCEER-MCEER lifelines project produced research personnel experienced in and committed to interdisciplinary inquiry. Building on the experience of the centers, several of the key researchers—engineers as well as social scientists, established as well as young investigators—pursued further interdisciplinary research outside the context of the Centers. In some cases, the same investigators continued working together, and in others, they formed new collaborative teams. The project also paved the

way for the recent blossoming of a distinct literature on modeling the spatial economic impacts of disasters (e.g., Okuyama and Chang, 2004).

How, in this research example, were barriers to interdisciplinarity discussed earlier in this chapter overcome? Indeed, the research team did encounter barriers ranging from miscommunication to mistrust to perceived lack of academic rewards. It took several years, perhaps the better part of a decade, for productive collaborations to form.

Three factors proved essential to success: problem-focused collaboration, certain characteristics of the research team, and the center environment. The collaboration focused initially on a demonstration study for the Memphis electric power system, where NCEER engineering researchers had already made headway and were eager to extend their engineering loss results to measures of societal impact. Social scientists (primarily economists) were able to communicate and collaborate with the engineers by focusing on the specifics of the problem—for example, by understanding that for a given earthquake scenario, the engineering models simulated electric power outage by the utility’s service area and that these results could serve as linkages to economic impact models. The case study focus also provided a clear end goal for the collaboration: quantitative estimates of social and/or economic disruption resulting from power outage.

Characteristics of the research team, which evolved over time, were also crucial to success. The literature suggests that senior faculty may be best suited for interdisciplinary collaborations because they are able to “risk time out of the disciplinary mainstream” and, moreover, “often need new challenges” (Klein, 1990:182). This pattern applied in the NCEER-MCEER example, where a senior engineer (who served as Center director for a time) and a senior economist were mainstays of the effort. However, the project was only able to get off the ground through the efforts of other researchers who were able to serve as translators between engineering and economics. Key linkages were made by one junior researcher who had been formally trained in both areas.

Finally, the importance of the center environment in fostering this research cannot be underestimated. The literature on interdisciplinarity suggests the benefits of small groups with stable membership. In this case, the centers served as an incubator for an initially risky endeavor with little precedent in the field. It allowed the research team to evolve its membership and develop trust, interdisciplinary language, and collaborative practices over a period of several years.

The centers also provided important support for the endeavor. In addition to grant funding, this support included research infrastructure, such as the opportunity to publish in center technical reports, research accomplishment volumes, and monographs. Regular center meetings provided forums for researchers to meet and develop relationships with investigators from

other disciplines. Frequent peer reviews of the centers by NSF panels, which consistently sought evidence of collaboration between engineers and social scientists, also provided immediate and important impetus to the interdisciplinary research. For example, the lifeline project was showcased in several NSF site reviews of the centers.

It is fair to say that this research would not have occurred or succeeded—certainly not in its initial stages—without the supportive and facilitative center environment.

Exemplar: Analyzing Casualties Through a Standardized Framework

After the 1994 Northridge earthquake, a number of researchers in Southern California were funded to study injuries in that earthquake (Shoaf et al., 1998, 2001; Park et al., 2001; Seligson and Shoaf, 2002; Seligson et al., 2002; Peek-Asa et al., 2003). The group included researchers at University of California, Los Angeles, the Los Angeles County Department of Health Services (LAC-DHS), and the California Department of Health Services. Furthermore, the California Governor’s Office of Emergency Services (OES) had funded a major risk-consulting firm in Southern California to gather data on many aspects of the earthquake, including fatalities and injuries. The funding for these studies came from numerous sources, including NSF, and had different requirements. Since the senior researchers from the public health sector were all well acquainted, they made a conscious decision to meet to ensure the consistency of their methodologies and definitions of injury. One of the senior researchers at UCLA was also involved in the hazards and disasters community and invited researchers from the consulting firm to attend the meeting. The meeting included two sets of researchers from UCLA, researchers from LAC-DHS, and researchers from the consulting firm. Each of the research teams consisted of a senior researcher and at least one advanced doctoral student or junior researcher who served as project manager.

As the research on the Northridge earthquake evolved, the teams agreed on consistent terminology and methodology for the collection of data. As research continued, it was carried out primarily by junior researchers. This group of junior researchers included two injury epidemiologists, a public health educator, and an earthquake engineer. As the data collection came to an end and analysis began, this multidisciplinary team of researchers began to look at analysis and the usefulness of the complete data set collected for improving casualty estimation. The earthquake engineer had special expertise in loss estimation modeling. A proposal was submitted to NSF to utilize this unique data set to improve casualty estimation modeling. The public health educator and earthquake engineer served as coprincipal investigators on the project.

The research project, funded by NSF, culminated in a standardized data classification scheme for earthquake-related casualties (Shoaf et al., 2002). This classification scheme was unique in that it attempted to include standards for data that were in the domain of the engineers and geosciences (hazard characteristics and building characteristics) as well as those in the domain of public health and the medical sciences (sociodemographic characteristics and injury characteristics). This process led the earthquake engineer and the public health educator to see themselves as translators. The earthquake engineer would translate technical information from the engineering and geoscience communities into language that the public health educator could translate back to the epidemiology and medical communities, and vice versa. Ongoing collaboration between the public health educator and the engineer has resulted in a number of studies on earthquake casualties, as well as the development of casualty models for other hazards including flooding and a number of terrorism scenarios (Peek-Asa et al., 2001).

Factors influencing the success of this interdisciplinary association included characteristics of the team, mentorship of senior researchers, and the focused nature of the research. While the literature suggests that senior researchers are more likely to be successful in interdisciplinary projects, the success of this team was primarily the result of the junior researchers. Perhaps because public health is in itself an interdisciplinary field, the public health educator has been able to succeed in the field of public health while conducting research almost exclusively on disasters in an interdisciplinary fashion. Furthermore, the engineer engaged on this team had worked extensively in loss estimation and not exclusively in structural engineering. As young researchers, this team developed a new discipline in which, over the decade, they have become leaders in the field.

The effect of the fact that researchers from a variety of fields had been calling for this type of research cannot be overlooked in the success of this team. Early in the research on the Northridge earthquake, members of this Northridge research team participated in a meeting of the U.S. Interdisciplinary Working Group on Earthquake Casualties. Participating in this working group, which had been meeting since the 1980s, lent credibility to the new research being done by this research team and encouraged it to continue the efforts begun by a number of other, more established researchers in the field.

Exemplar: Understanding Decision Making for Risk Protection

Knowledge of hazards and disasters has also been advanced by research that crosses disciplinary boundaries within the social sciences. One of the most successful examples concerns a long-standing collaboration between an economist, Howard Kunreuther, and a psychologist, Paul Slovic.

Through work spanning three decades, they have individually and jointly made major contributions to understanding how individuals perceive risk, manage risk, and make decisions regarding insurance and other forms of risk protection, and the implications for public policy (Slovic et al., 1974; Kunreuther and Slovic, 1978, 1996; Kunreuther et al., 1978, 1998; Slovic, 2000; Flynn et al., 2001). Their initial collaboration was supported by NSF through the Directorate of Research Applied to National Needs; much of their later collaborative research was also supported by NSF, some of it through NEHRP.

This collaboration was initially catalyzed by regular meetings of the Natural Hazards Research and Applications Information Center (established in 1976 at the University of Colorado at Boulder) and the encouragement of its founder, Gilbert White. As Slovic (2000:xxi) recalls,

In 1970, I was introduced to Gilbert White, who asked if the studies on decision making under risk that [another collaborator] and I had been doing could provide insights into some of the puzzling behaviors he had observed in the domain of human response to natural hazards. Much to our embarrassment, we realized that our laboratory studies had been too narrowly focused on choices among simple gambles to tell us much about risk taking behavior in the flood plain or on the earthquake fault.

Questions from White’s pioneering work on risk perception of flood hazard, such as why people who live in dangerous areas always return to live there after a disaster, or whether it was true that people react differently to risk if consequences are immediate as opposed to delayed, intrigued the psychologist and induced him to begin working on applied research problems. Discussions with the economist, Kunreuther, led initially to an influential overview paper (Slovic et al., 1974) that introduced recent research in psychology, including the work of A. Tversky and D. Kahneman (who won the Nobel Prize in Economics in 2002), and made linkages to the hazards and disasters field.

A few years later, Kunreuther began an NSF project on individual decision making for insurance and invited Slovic to participate on the team. The project, documented in Disaster Insurance Protection (Kunreuther and Slovic, 1978), involved an unusual blend of laboratory experimental work with field study. The field study included an extensive telephone survey of more than 3,000 insured and uninsured homeowners in floodplains and earthquake zones across the United States. Collaboration occurred throughout the project; for example, the economist and psychologist worked together to design the survey and jointly pilot-tested the questionnaire in person in neighborhoods of San Francisco. The laboratory experiments, led by the psychologist and closely advised by the economist, were designed to complement the survey. For instance, the survey found that homeowners

had poor knowledge of the hazard and generally took little action to mitigate their risk. Laboratory findings suggested an explanation: “that people refuse to attend to or worry about events whose probability is below some threshold,” where the threshold could vary between individuals and between situations (Kunreuther et al., 1978:236). Results further showed that people did not perceive insurance in the ways that economists had assumed. The study found, for instance, that people insured not against low-probability, high-consequence events, but against high-probability, low-consequence events—in effect viewing insurance as a form of investment (Slovic, 2005).

This early interdisciplinary collaboration appears to have played an important role in the careers of these influential researchers. Slovic, in particular, credits his early experiences in natural hazards research with expanding his horizons beyond the “usual narrow path” of the experimental psychologist, in particular, sensitizing him to “risks in the real world.” This led him to study technological risk, an issue of great currency in the 1970s, and to focus on issues of risk perception, whereas in his laboratory work, he had been more interested in issues of risk taking. This led to productive collaborations with a number of other researchers, work on risk and decision making in a societal context, and more than 50 papers on risk perception (Slovic, 2005).

A number of factors appear to have been significant in the success of this case. First, and arguably most important, is the involvement of researchers “who find unraveling a complex transdisciplinary issue at least as important as their own discipline” (Wilbanks in NRC, 2005). Curiosity and open-mindedness appear, along with a proclivity for intellectual collaboration, to have been important drivers. It may have helped that Slovic was working outside a university environment. A second factor was the problem-focused nature of the research. The complexity of the applied problem—that is, how people behave in the face of natural hazards and how they make decisions concerning insurance—demanded an interdisciplinary approach. It is also significant that the researchers placed high value on “integrating descriptive and prescriptive elements” in their research, insisting on both advancing knowledge and providing guidance for policy (Slovic, 2005). Third, the Natural Hazards Center at Boulder, the mentorship of Gilbert White, and grant support from NSF all appear to have provided crucial support in both tangible and intangible forms.

Exemplar: Sustainability Science

Instructive experiences can also be found in fields allied with hazards and disaster studies. The case of “sustainability science” demonstrates the possibility, processes, and challenges associated with developing fundamen-

tally interdisciplinary conceptual frameworks and research agendas that cross boundaries between the natural and social sciences. This example is especially apt because of the prominence of “sustainability” as a vision in the recent Second Assessment of research in the hazards and disaster field, wherein sustainability “means that a locality can tolerate—and overcome—damage, diminished productivity, and reduced quality of life from an extreme event without significant outside assistance” (Mileti, 1999b:4).

The idea of sustainable development emerged in the 1980s originating from multidisciplinary scientific perspectives on the interactions and interdependencies between society and the environment. The concept gained political traction and broader acceptance through two important and influential endeavors, both supported by the United Nations—the Brundtland Commission report (WCED, 1987), and the UN Conference on Environment and Development in Rio de Janeiro in 1992 and its Agenda 21 report (UNCED, 1992).

For the past two decades the international science plan for global environmental change was largely based on getting the correct scientific understanding of the interactions between the geosphere and biosphere as they influence climate change and other perturbations. The Intergovernmental Panel on Climate Change (IPCC) process initially focused on scientific questions, but within the past decade, the emphasis has shifted toward understanding the societal responses to climate change. One milestone in this transition from a purely natural science to an integrated natural science-social science perspective was the publication of the NRC report Our Common Journey (NRC, 1999b). Then-president of the National Academy of Sciences (NAS), Bruce Alberts, “saw in the idea of a sustainability transition the great challenge of the coming century and consistently urged the board to explore and articulate how the science and technology enterprise could provide the knowledge and know-how to help enable that transition” (NRC, 1999b:xiv). Funded with foundation support (rather than by federal agencies asking for advice), and a strong personal interest and leadership from the National Academies, this report lays out a research agenda for “sustainability science” (NRC 1999b:11):

Develop a research framework that integrates global and local perspectives to shape a “place-based” understanding of the interactions between environment and society.

Initiate focused research programs on a small set of understudied questions that are central to a deeper understanding of interactions between society and the environment.

Promote better utilization of existing tools and processes for linking knowledge to action in pursuit of a transition to sustainability.

Many of the members of the original Board on Sustainable Development (and others who participated in the workshops) had known one another for a long time and shared similar philosophical and intellectual predilections (Turner, 2005). Their work and interaction continued beyond the publication of the NRC report, especially in the promotion of scientific research in sustainability (Kates et al., 2001). When the U.S. Global Change Research Program wanted to explore some of the themes in more detail, they went to this group of scholars (William C. Clark, Robert Kates, Pamela Matson, Robert Corell, and Billie L. Turner, among others). With National Science Foundation support (with contributions from NOAA and NASA), an interdisciplinary group began meeting to discuss the conceptual and methodological development of sustainability science. The entire group met annually for a period of three years, with side conversations and work done at the participating institutions—Clark, Stanford, and Harvard universities and the Stockholm Environment Institute. The intensive summer annual workshops were a “must go.” From these workshops, the initial result was a series of published articles in the Proceedings of the National Academy of Sciences in 2003 that articulated both the conceptualization of the field and exemplars of how to implement them at various scales (Cash et al., 2003; Clark and Dickson, 2003; Kates and Parris, 2003; Parris and Kates, 2003; Turner et al., 2003a,b).

The success of the interdisciplinary research collaboration has been fostered by personal relationships among key participants, a common scholarly view of the need for better understanding of nature-society interactions, keen personal interest from leaders of the scientific establishment (NAS and the American Association for the Advancement of Science [AAAS]) and outside political forces (societal needs identified by the United Nations and others). The most significant outcomes to date have been in the conceptual development of the field, but the actual implementation of the science agenda has not happened in any meaningful way. The barrier has and continues to be funding. When sympathetic program managers left the primary mission agencies (NASA and NOAA) that were funding such work, funding languished. Despite this, sustainability science (as an integrated and interdisciplinary field of study) continues to enjoy strong intellectual support from the leadership of the scientific community (Raven, 2002).

Lessons for Successful Interdisciplinary Research

These four exemplars were selected to represent different types of interdisciplinary research. In reviewing factors leading to their success, however, a number of commonalities emerge:

Support from senior leaders. All four exemplars cite this factor, whether in the form of personal commitment to the interdisciplinary inquiry from senior researchers who were themselves involved in the research, mentoring and encouraging of junior researchers to collaborate, or personal interest from leaders of the scientific community.

Financial support from granting agencies. All four cases were supported by NSF, as well as other sources. In some cases, the grant funding catalyzed the collaboration, while, in others it enabled in-depth empirical studies to follow on conceptual discussions of interdisciplinary frameworks. Although difficult to verify, it appears that without this financial support, none of the collaborations would have flourished for long or, in some cases, materialized at all. In one case, as previously noted, research progress was impeded when funding was lost because sympathetic program officers left the supporting funding agencies.

Forum for continuous dialogue. In three of the cases, an institutional meeting ground (either a multidisciplinary center or a series of formal meetings) appears to have been important for fostering, if not also initiating, the intellectual dialogue across disciplines. This seems to have been particularly important when collaborators did not already have long-standing personal relationships, particularly where social scientists needed to establish new collaborations with natural scientists and engineers.

Focus on an applied problem. The three exemplars from the hazards and disaster field all noted that focus on an applied problem greatly facilitated interdisciplinary research. The complexity of the societal problem exceeded the bounds of any traditional discipline and required an interdisciplinary approach. Moreover, the problem focus provided clarity and specificity regarding the nature of the interdisciplinary knowledge needed.

A number of other common factors in success are also apparent, to a somewhat lesser degree, across the cases. Although each case cited “characteristics of the research team,” somewhat different characteristics were noted for each. They included junior researchers who could serve as interdisciplinary links or translators, long-standing personal relationships between the collaborators, and open rather than discipline-bound intellectual perspectives. Three of the cases involved at least one key participant from outside a university setting, which may have reduced the academic institutional barriers to collaboration that are often cited in the literature. Two of the cases noted the importance of external calls from the scientific community for interdisciplinary research on the specific problem. These

factors appear to be important in some circumstances, but they do not appear to be as robust explanations as the ones listed above. The cases profiled here corroborate many of the findings summarized earlier from the larger literature on interdisciplinary research.

RECOMMENDATIONS

Interdisciplinarity in hazards and disaster research is growing. Interdisciplinary research, both within and beyond the social sciences, has made major contributions to the field. Interdisciplinarity figures prominently in the research needs of the field. While unanswered disciplinary questions remain, all of the priority research needs identified by the committee (see Chapters 3 and 4 ) involve multiple disciplines and are in part, if not fundamentally, interdisciplinary.

Research centers have proven to be very important in facilitating interdisciplinary research, as demonstrated in the hazards field and reinforced by recommendations in related fields. A workshop on integrated research in risk analysis and decision making yielded a consensus recommendation that “the most effective way to achieve program goals is to fund multidisciplinary centers.” (NSF, 2002:7) In the area of human dimensions of global environmental change, centers have been advocated in order to strengthen key linkages between the natural and social sciences (Stern et al., 1992).

The committee makes three recommendations regarding interdisciplinary hazards and disaster research.

Recommendation 5.1: As NSF funding for the three earthquake engineering research centers (EERCs) draws to a close, NSF should institute mechanisms to sustain the momentum that has been achieved in interdisciplinary hazards and disaster research.

In 2007, the three EERCs will come to the end of their 10-year terms of NSF support. At the same time, the Network for Earthquake Engineering Simulation (NEES), at a cost of more than $80 million, will soon dominate the landscape of NSF-supported hazards research. Both of these changes threaten the momentum that has developed with regard to social science involvement in interdisciplinary hazards and disaster research. Within the EERCs, a necessary condition for the fostering of social science research and interdisciplinary collaborations was the sustained pressure from annual NSF site review teams. As the EERCs “graduate” to self-sustaining financing structures and seek support from the private sector, it is likely that the role of social science research will be diminished. At risk are the valuable lessons, experience, and momentum developed over the last two decades.

Within NEES, because of its emphasis on laboratory testing of physical structures, opportunities for social science involvement appear to be very

limited. While the NEES research agenda cites the importance of interdisciplinary collaboration with the social sciences, none of the specific recommendations within that research agenda reflect this importance (NRC, 2003b). Within NEES, the Grand Challenges program, which funds research on “compelling national research” problems that require a “comprehensive systems approach” and “in-depth, cross-disciplinary, and multi-organizational investigation” ( http://www.nsf.gov/pubs/2005/nsf05527/nsf05527.htm ), provides the most likely context for social science involvement. However, the NEES program has not funded any Grand Challenges research projects to date.

Recommendation 5.2: The hazards and disaster research commu nity should take advantage of current, unique opportunities to study the conditions, conduct, and contributions of interdiscipli nary research itself.

Social science expertise on subjects ranging from individual decision making to organizational effectiveness and evaluation research should be utilized to study interdisciplinary research in the hazards and disaster field. One opportunity consists of research on NEES; for example, to investigate how a spatially distributed network structure influences the research enterprise and to evaluate the effectiveness of such a structure. A second opportunity is the impending “graduation” of the earthquake engineering research centers from NSF funding to industry and other forms of financial support: for example, to study how this change affects the role of interdisciplinary research generally and interdisciplinary research involving the social sciences, in particular; to study centers and how they do or do not work effectively; and to systematically investigate team building in hazards research. A third opportunity would be to make similar comparisons between research supported by NEHRP and that supported by the Department of Homeland Security.

Recommendation 5.3: NSF should support the establishment of a National Center for Social Science Research on Hazards and Disasters.

In such a center, the committee envisions a distributed consortium of researchers and research units across the United States, with affiliated members located across the world. Similarly to NEES, it would take advantage of telecommunications technology to link spatially distributed data repositories, facilities, and researchers. It would provide an institutionalized, integrative forum for social science research on hazards and disasters, much as the Southern California Earthquake Center (SCEC) does for the earthquake earth sciences community. The key charges of the center would include

facilitating access to and use of disaster data;

coordinating post-disaster reconnaissance efforts of social scientists;

providing consensus statements from the research community to inform public policy;

providing educational materials (i.e., integrating existing materials, developing new ones, and disseminating both), such as Web-based short courses, that can help disseminate social science research findings to a broad range of audiences, including students, investigators new to the field, potential collaborators in other disciplines, and researchers in developing countries;

supporting researchers in developing the expertise they need to successfully engage in interdisciplinary research—for example, through doctoral and post-doctoral opportunities, sabbaticals, career development awards, or formal training (see Pellmar and Eisenberg, 2000:11; for an example, see www.nianet.org ); and

catalyzing interdisciplinary collaborations, both within the social sciences and between the social sciences and natural sciences and/or engineering; for example, through convening workshops and symposia.

Core nodes of the network would include existing university-based research centers that are focused on hazards and disaster research (see Chapter 8 ), those DHS centers of excellence that involve social science research (e.g., the National Center for the Study of Terrorism and Responses to Terrorism), and the new centers recommended by this committee—the Data Center for Social Science Research on Hazards and Disasters (see Chapter 4 ) and the Center for Modeling, Simulation, and Visualization of Hazards and Disasters (see Chapter 7 ). However, individual researchers not associated with these existing centers would also have access to this distributed network.

The center would receive core funding from NSF and mission agencies such as DHS, NOAA, and NASA. It would leverage these funds to attract support from state and local governments, as well as international agencies and the private and not-for-profit sectors.

Such a center arrangement would provide several important benefits for social science research on hazards and disasters. First, it would provide a “critical mass” research network. The field is small, characterized by a modest number of core researchers, spread over many disciplines and many institutions, and bolstered by others who are only intermittently involved in hazards research (see Chapter 9 ). Achieving a critical mass is important for attracting and retaining researchers, as well as catalyzing interdisciplinary collaborations (see, for instance the first and third exemplars above).

Second, such a center would elevate the stature of the field. This would enable social scientists to negotiate interdisciplinary, collaborative research agendas with their natural science and engineering counterparts on coequal footing. This could lead, for example, to interdisciplinary collaborations on hazards and disasters that address fundamental dynamics of social change (see Chapter 2 ). Such research has not been possible in the context of the EERCs, where social scientists comprise a small minority and research agendas have been set predominantly by engineers. The envisioned center would allow social science insights and concerns to influence, rather than simply extend, priorities in natural science and engineering research for the ultimate goal of making society safer.

Third, such a center would provide needed international leadership. The benefits of critical mass and stature noted above could be especially important in other countries, where social science research on hazards and disasters is often poorly established. Moreover, the benefits of an international network also extend to U.S. researchers, particularly in promoting collaborative research on the linkages between disasters and development (see Chapter 6 ).

Social science research conducted since the late 1970's has contributed greatly to society's ability to mitigate and adapt to natural, technological, and willful disasters. However, as evidenced by Hurricane Katrina, the Indian Ocean tsunami, the September 11, 2001 terrorist attacks on the United States, and other recent events, hazards and disaster research and its application could be improved greatly. In particular, more studies should be pursued that compare how the characteristics of different types of events—including predictability, forewarning, magnitude, and duration of impact—affect societal vulnerability and response. This book includes more than thirty recommendations for the hazards and disaster community.

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Glogging About Natural Disasters

• Resources & Preparation
• Instructional Plan
• Related Resources

As background knowledge to Susan Pfeffer's novels The Dead and the Gone and Life as We Knew It , students research natural disasters.  In these two companion novels set in two different locations in the United States, the world's environment has been changed because the moon has been pushed closer to the earth.  This disturbance causes a series of natural disasters and epidemics.  To fully understand the effects natural disasters have had on the world's environment, each student researches a different natural disaster.  Then they use these facts as well as safety tips in unique glogs, online interactive multimedia posters, that will include student-recorded weather announcements.

Featured Resources

• Natural Disaster Notetaking Sheet : Students use this sheet to take notes while doing research for their glogs.

Glogster EDU : This website is used for the creation of glogs.

From Theory to Practice

Technology generates opportunities for students to practice their reading skills, analyze information, synthesize that information, and then communicate their findings to others. As Belinha DeAbrue points out in her article "Glogster: A Poster-Sized Look at Student Movie Stars," “attracting the teenagers in today’s very digital and multimedia society has become an issue amongst educators.”  She suggests that using Glogster to make glogs bridges the gap between the classroom and the students’ highly multimedia world outside of the classroom.

Additionally, this web 2.0 tool used in this lesson provides an educational side to its website which provides private access for teachers and students, therefore, creating a safe environment for students of all ages.

Further Reading

Common Core Standards

This resource has been aligned to the Common Core State Standards for states in which they have been adopted. If a state does not appear in the drop-down, CCSS alignments are forthcoming.

State Standards

This lesson has been aligned to standards in the following states. If a state does not appear in the drop-down, standard alignments are not currently available for that state.

NCTE/IRA National Standards for the English Language Arts

• 1. Students read a wide range of print and nonprint texts to build an understanding of texts, of themselves, and of the cultures of the United States and the world; to acquire new information; to respond to the needs and demands of society and the workplace; and for personal fulfillment. Among these texts are fiction and nonfiction, classic and contemporary works.
• 3. Students apply a wide range of strategies to comprehend, interpret, evaluate, and appreciate texts. They draw on their prior experience, their interactions with other readers and writers, their knowledge of word meaning and of other texts, their word identification strategies, and their understanding of textual features (e.g., sound-letter correspondence, sentence structure, context, graphics).
• 4. Students adjust their use of spoken, written, and visual language (e.g., conventions, style, vocabulary) to communicate effectively with a variety of audiences and for different purposes.
• 5. Students employ a wide range of strategies as they write and use different writing process elements appropriately to communicate with different audiences for a variety of purposes.
• 6. Students apply knowledge of language structure, language conventions (e.g., spelling and punctuation), media techniques, figurative language, and genre to create, critique, and discuss print and nonprint texts.
• 7. Students conduct research on issues and interests by generating ideas and questions, and by posing problems. They gather, evaluate, and synthesize data from a variety of sources (e.g., print and nonprint texts, artifacts, people) to communicate their discoveries in ways that suit their purpose and audience.
• 8. Students use a variety of technological and information resources (e.g., libraries, databases, computer networks, video) to gather and synthesize information and to create and communicate knowledge.
• 11. Students participate as knowledgeable, reflective, creative, and critical members of a variety of literacy communities.
• 12. Students use spoken, written, and visual language to accomplish their own purposes (e.g., for learning, enjoyment, persuasion, and the exchange of information).

Materials and Technology

• Computers with Internet capabilities, microphones, headphones, and the free software Audacity loaded onto the computers
• Classroom with LCD projector and whiteboard/interactive whiteboard
• Books about natural disasters
• Stopwatches for timing
• Creating a Glog
• Natural Disasters List
• Natural Disaster Notetaking Sheet
• Suggested Print Materials about Natural Disasters
• Natural Disaster Websites
• Sample Weather Warning
• Natural Disaster Checklist
• Natural Disaster Glog Rubric

For a minimal charge, this website provides fifty accounts per educator to create glogs.  Additionally, it offers schools a yearly subscription levels so that students can be linked to more than one teacher.

This free software will allow students to record and then upload their recordings to their glogs.

MSN has several videos that can serve as examples for the radio broadcasts.  Simply play the video without projection, so students hear the videos as if it were on radio.  Furthermore, you can search the website for just videos, making it very easy for the busy educator to find an example.

Students can use this website to cite their sources using MLA format.

Reports of past weather events all over the world in concise, easy to understand language.  This website also has the current weather warnings for the United States which can serve as a guide for the students’ recordings that they will create as part of their glogs.  The current weather warnings are listed at https://alerts.weather.gov/cap/us.php?x=1 .

This site fully covers all natural disasters that have happened in the world.

This website has several articles on the various disasters and safety tips.  Additionally, the kids’ section of the site has short videos of storms.

At this website, students can learn about tornadoes, earthquakes, hurricanes, and volcanoes as well as create simulations of these natural disasters.

Preparation

• Before these sessions, students have learned note taking skills.  They can be taught note taking skills through the minilesson Research Building Blocks:  Notes, Quotes, and Fact Fragments as well as know the importance of citing sources through the standard lesson Research Building Blocks:  “Cite Those Sources.” Furthermore, if this is the students’ first project citing sources, then using Exploring, Plagiarism, Copyright, and Paraphrasing prior to this project would be beneficial.
• Before this lesson, work with your school librarian so that various titles on individual natural disasters as well as books that cover these topics in general for safety and survival tips will be available.  The Suggested Print Materials about Natural Disasters has several titles for the latter type of books.  Additionally, the Natural Disaster Booklist gives more titles that will benefit the students’ research.  Reserve one period in your school library to check out these books and for students to begin their research (or check out these books for your classroom).
• Reserve time in your school’s computer lab for a total of five class periods, with at least one day out of the lab between sessions four and five.  Check that computers have Audacity or other software for the students to record as students will produce their own short weather-related recording.  Microphones and headphones must also be available for the students.
• If possible, have the research websites and Glogster EDU bookmarked on the computers.  If that is not feasible, you can sign up for a wiki at Wikispaces where you can create a class page for the links and later use this site to show your glogs to your community.  If that is not possible, make copies of  the Natural Disaster Websites , one per computer.
• Sign up for an account at Glogster EDU and request the number of student accounts you need (up to fifty are included in your subscription).   Glogster will generate user names and passwords for your student accounts.  Assign each student an account.
• Make copies of Creating a Glog , the Natural Disaster Glog Rubric , and the Natural Disaster Checklist (one for each student).
• Familiarize yourself with Glogster by using the ReadWriteThink Strategy Guides Teaching With Glogster: Using Virtual Posters in the Classroom and Using Glogster to Support Multimodal Literacy .   Practice the steps of making a glog using Creating a Glog .  Create a sample glog for a natural disaster or use a sample from the Glogster EDU website such as The 2011 Japan Tsunami .
• Also, become familiar with Audacity (or other recording software) so that you can save files as .mp3 or .wav.
• Find current weather warnings from the NOAA which students can use to write their scripts for their recordings.  See the Sample Weather Warning for an example.

Student Objectives

Students will:

• practice the necessary technology skills for assembling glogs.  These include recording, saving pictures, and uploading files.
• learn the importance of acknowledging sources for information as well as digital images.
• create a correctly formatted bibliography for information and images.
• learn about several past disasters that have affected the world.
• understand weather safety tips and survival tips.
• communicate their findings by sharing their glogs with their classmates.

Session One

• Ask the students what weather-related emergencies are typical for your area.  Ask how we prepare for these emergencies, what we do during these events, and what we do after a weather-related disaster.   Also, discuss how we know when a weather emergency is imminent.
• Explain that the students will be soon split into two literature circles to read Susan Pfeffer’s novels in which a single event happens in both novels changes the world’s environment.  This event causes many natural disasters throughout the world.  Ask students what natural disasters they have heard of before.  You can prompt them to think about what they have previously discussed in science classes before.
• Explain that to help them understand the tragedy about which they will read in the two companion novels, each student will research a natural disaster, assemble a glog, and share that glog with the class.
• Show the sample glog that you have created or use one from Glogster EDU .
• Go through the Natural Disaster Glog Rubric and grade the sample glog as a class.
• Project the Natural Disasters List and have each student select a different disaster.
• Give each student the printouts Natural Disaster Notetaking Sheet and the Natural Disaster Checklist .  Discuss what they will be looking for in the books and websites they will use in the next three sessions.
• Lead the students in a discussion on why they will need to cite their sources for this project.  Model for the students how to cite a book so that they are ready for Session Two.

Session Two

• Have students check out books about their individual disasters.   Have the general disaster books available to all students during the next three sessions.
• Before students begin taking notes, remind them to cite their books.
• Monitor the students as they research, noting time on task.  Check for any inaccuracies on their Natural Disaster Notetaking Sheets .

Sessions Three and Four

• Before students begin their research, remind them they will need at least five pictures for their glog.  Ask students why they will cite their pictures’ sources.  Prompt their answers by comparing citing a book or website to citing a picture.  Because Glogster uses URLs to bring in pictures, have students open a word processing file to save the URLs of pictures they want to use on their glogs.  Model for the students how to create this list.  Then model for the students how to correctly cite a web source.
• Have the students continue to research using the websites listed as well as their books they checked out in the last session.  Before students start taking notes, remind them to cite their websites.  Again, have available to them the general disaster books.
• Monitor the students as they research, noting time on task.  Check for any inaccuracies on their notetaking sheets.
• Check that students have sufficient information in sections so that they will have material for their scripts .

Session Five

• Ask students what type of weather-related drills we perform in school.  Discuss how they learned to prepare for these drills.  Then ask how the school would know if we were going to have a weather-related emergency.
• The student can choose to write a public announcement that prepares the area for a disaster that might sometime happen.  For this choice, explain the student will use the notes on preparing for the disaster.  For a sample, play a video from online, such as this Hurricane Survival Guide from MSN.com , without the projector on, so students just hear the script as if it were a radio broadcast.
• The student can choose to write a weather warning for the particular disaster he/she has researched.  For this choice, the student will use the notes on the particular disaster.  Project the Sample Weather Warning from NOAA that is included in the printouts.  Explain to the students that this is what radio and television stations receive when a warning has been issued.  Model for the students using the provided script how this warning is turned into a live radio warning.  Also, discuss with the students the sense of urgency that the announcer’s voice has when reading a weather warning and that they may include their notes on what to do during a weather disaster.
• The student can choose to write a newscast after the disaster has struck and explain what happened to the area.  For this choice the student will use the section on description and after the event survival tips.
• While students are working on their scripts, check the students have completed the Natural Disaster Notetaking Sheet .
• As students complete their rough drafts of their scripts, assign them to be partners.  Hand out stopwatches to each pair.  Instruct students to practice reading their scripts as they time each other, checking that each reaches the two minute minimum time length.  Recommend students make suggestions for improvement on each other’s scripts.  If time allows, switch partners for more practice.
• For homework, assign students who did not complete their scripts to finish and practice.

Session Six

• Collect students’ final copies of their scripts.  Read these and make any suggestions before the next session.
• Model steps 1-12 of creating a glog using the printout Glog It .   Save step 13 for tomorrow when they have recorded their broadcast.
• After modeling the steps, have the students open their word processing files with their images so they have their pictures for their glogs.  Give each student his/her username and password.  When the student signs in for the first time, the student will be asked to type in his/her name.  Instruct the students to do so because then you will be able to see on your teacher dashboard the students by name and username.
• Allow students time to work on their glogs.  While students work, check on their accuracy of information.  Question students about which pictures they have selected and why these pictures represent their disaster.  Offer feedback on their layout and choices for their glogs as they work.
• Encourage students to work on their glogs from any computer (home or public library, for example) since this is an Internet-based program.

Sessions Seven and Eight

• Demonstrate how to use Audacity (or other recording software) and where to save an audio file on your computer system.  Model for the students how to add this sound file to their glogs, which is step 13 on Creating a Glog .
• Divide the class into two groups.  Rather than having all students recording at once, give the microphones and headphones to every other student to minimize background noise on the recordings.  Those not recording can work on citing their sources using their file on images as well as their note taking sheet for books and websites.  Suggest to students that they can use Easybib.com for creating their Works Cited page.
• Allow students time to work on their glogs. Monitor their progress.  Check on the accuracy of their Works Cited pages.
• Remind students that during Session Nine all glogs will be shared, so encourage them to work outside of class.

Session Nine

• Have each student share his/her glog with the class, allowing students to ask questions at the end of each presentation.  From the teacher’s dashboard in Glogster , each student’s glog can be easily accessed so that each student does not have to log-in before each presentation.
• After all have presented, allow time for the student reflection questions that are included in the assessment section.
• Establish a class wiki and post links to the glogs to the wiki.  Publish your classroom wiki to the community, so the audience for your students is larger.
• Give students the option of adding a video recording in place of a sound recording.
• Read other books that feature natural disasters such as The Volcano Disaster by Peg Kehret, Earthquake Terror by Peg Kehret, Trapped by Michael Northrup,  Night of the Howling Dogs by Graham Salisbury, Ninth Ward by Jewell Parker Rhodes or The Killing Sea by Richard Lewis.
• If computer resources are not available, students could make posters with paper and present these to the class.  As part of their presentations, the students could read their scripts to the class.

Student Assessment / Reflections

• Review each student’s completed Natural Disaster Notetaking Sheet and recording script.
• During the class periods, observe and note the students’ time on task as this is one of the categories on the rubric .
• Using the Natural Disaster Glog Rubric , evaluate each student’s completed glog.
• Allow class time for students to present their glogs to the class.  Question students about their choices of graphics and pictures for their disaster.  Allow classmates to pose questions to each presenter.
• After all the glogs have been presented, ask students to reflect on the learning experience by having them complete one or more of the following prompts.  Explain that their answers can include information they learned from each other’s presentations.

o    Because of this project, I learned ____________ about natural disasters.

o    Because of this project, I learned ____________ about technology.

o    The most important ideas I learned from this project was____________.

o    I want to know more about _____________.

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Students explore the nature and structure of expository texts that focus on cause and effect and apply what they learned using graphic organizers and writing paragraphs to outline cause-and-effect relationships.

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