2017 Vol. 8, No. 4

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Towards Quantitatively Understanding the Complexity of Social-Ecological Systems—From Connection to Consilience
Xiao-Bing Hu, Peijun Shi, Ming Wang, Tao Ye, Mark S. Leeson, Sander E. van der Leeuw, Jianguo Wu, Ortwin Renn, Carlo Jaeger
2017, 8(4): 343-356. doi: 10.1007/s13753-017-0146-5
The complexity of social-ecological systems (SES) is rooted in the outcomes of node activities connected by network topology. Thus far, in network dynamics research, the connectivity degree (CND), indicating how many nodes are connected to a given node, has been the dominant concept. However, connectivity focuses only on network topology, neglecting the crucial relation to node activities, and thereby leaving system outcomes largely unexplained. Inspired by the phenomenon of "consensus of wills and coordination of activities" often observed in disaster risk management, we propose a new concept of network characteristic, the consilience degree (CSD), aiming to measure the way in which network topology and node activities together contribute to system outcomes. The CSD captures the fact that nodes may assume different states that make their activities more or less compatible. Connecting two nodes with in/compatible states will lead to outcomes that are un/desirable from the perspective of the SES in question. We mathematically prove that the CSD is a generalized CND, and the CND is a special case of CSD. As a general, fundamental concept, the CSD can facilitate the development of a new framework of network properties, models, and theories that allows us to understand patterns of network behavior that cannot be explained in terms of connectivity alone. We further demonstrate that a co-evolutionary mechanism can naturally improve the CSD. Given the generality of co-evolution in SES, we argue that the CSD is an inherent attribute rather than an artificial concept, which underpins the fundamental importance of the CSD to the study of SES.
Correction to: Towards Quantitatively Understanding the Complexity of Social-Ecological Systems—From Connection to Consilience
Xiao-Bing Hu, Peijun Shi, Ming Wang, Tao Ye, Mark S. Leeson, Sander E. van der Leeuw, Jianguo Wu, Ortwin Renn, Carlo Jaeger
2017, 8(4): 357-357. doi: 10.1007/s13753-017-0147-4
A Framework for Disaster Vulnerability in a Small Island in the Southwest Pacific: A Case Study of Emae Island, Vanuatu
Guy Jackson, Karen McNamara, Bradd Witt
2017, 8(4): 358-373. doi: 10.1007/s13753-017-0145-6
The societal costs of disasters around the world are continuing to increase and Pacific Island countries are considered some of the most vulnerable. This is primarily due to a combination of high hazard exposure coupled with a range of social, economic, physical, and political vulnerabilities. This article contributes to the growing body of work that aims to understand the causal factors of disaster vulnerability, but with a specific focus on small island developing states. The article first develops a framework for understanding disaster vulnerability, drawing on extensive literature and the well-established Methods for the Improvement of Vulnerability in Europe (MOVE) framework, and second, applies this adapted framework using empirically-derived data from fieldwork on Emae Island, Vanuatu to provide a working understanding of the causal elements of disaster vulnerability. Drawn from a significant body of scholarship at the time, the MOVE framework was primarily developed as a heuristic tool in which disaster vulnerability is considered to be a function of exposure, susceptibility (socially, economically, physically, culturally, environmentally, institutionally), and a lack of resilience. We posit that this adapted framework for small islands should also include historical susceptibility, and we prefer livelihood resilience (as capabilities, social capital, knowledge, participation, and human rights) over lack of resilience. We maintain that understanding disaster vulnerability holistically, which is inclusive of both strengths and drawbacks, is crucial to ensure that limited resources can target the causal factors that produce vulnerability and help safeguard and improve livelihoods in both the short and long term.
Adaptation Decision Support: An Application of System Dynamics Modeling in Coastal Communities
Daniel Lane, Shima Beigzadeh, Richard Moll
2017, 8(4): 374-389. doi: 10.1007/s13753-017-0154-5
This research develops and applies a system dynamics (SD) model for the strategic evaluation of environmental adaptation options for coastal communities. The article defines and estimates asset-based measures for community vulnerability, resilience, and adaptive capacity with respect to the environmental, economic, social, and cultural pillars of the coastal community under threat. The SD model simulates the annual multidimensional dynamic impacts of severe coastal storms and storm surges on the community pillars under alternative adaptation strategies. The calculation of the quantitative measures provides valuable information for decision makers for evaluating the alternative strategies. The adaptation strategies are designed model results illustrated for the specific context of the coastal community of Charlottetown, Prince Edward Island, Canada. The dynamic trend of the measures and model sensitivity analyses for Charlottetown-facing increased frequency of severe storms, storm surges, and sea-level rise-provide impetus for enhanced community strategic planning for the changing coastal environment. This research is presented as part of the International Community-University Research Alliance C-Change project "Managing Adaptation to Environmental Change in Coastal Communities:Canada and the Caribbean" sponsored by the Social Science and Humanities Research Council of Canada and the International Development Resource Centre.
Participatory Early Warning Systems: Youth, Citizen Science, and Intergenerational Dialogues on Disaster Risk Reduction in Brazil
Victor Marchezini, Rachel Trajber, Débora Olivato, Viviana Aguilar Muñoz, Fernando de Oliveira Pereira, Andréa Eliza Oliveira Luz
2017, 8(4): 390-401. doi: 10.1007/s13753-017-0150-9
Building national people-centered early warning systems (EWS) is strongly recommended by the United Nations International Strategy for Disaster Reduction (UNISDR). Most of the scientific literature is critical of the conventional view of EWS as a linear model with a topdown approach, in which technological features are given more attention than human factors. It is argued that EWS should be people-centered, and used for risk prevention, with an emphasis on resilience, rather than only being triggered when a hazard occurs. However, both the UNISDR and the literature fail to say how a people-centered EWS should be built, and what steps are needed to put EWS into effect. This article examines the obstacles and measures required to promote people-centered EWS, with a focus on the situation in Brazil. After assessing the institutional vulnerability of EWS, we analyze some measures that can be taken to reduce institutional vulnerability, based on experiences with a participatory citizen science educational project that involved high school students. Some guidelines are developed for adopting a bottom-up approach towards achieving the four elements of EWS-risk knowledge, monitoring, communication of warnings, and response capability-with the help of school curricula.
Factors Influencing Post-disaster Reconstruction Project Management for Housing Provision in the Gaza Strip, Occupied Palestinian Territories
Adnan Enshassi, Tarik Chatat, Jason von Meding, Giuseppe Forino
2017, 8(4): 402-414. doi: 10.1007/s13753-017-0155-4
In the Occupied Palestinian Territories, the Gaza Strip has suffered regular cycles of reconstruction due to systematic destruction during Israeli military operations, as in 2006, 2008-2009, 2012, and 2014. In this context of ongoing conflict this article aims to identify, rank, and discuss the most important factors influencing post-disaster reconstruction project management (PDRPM) for housing in the Gaza Strip. A set of key factors that influence PDRPM were assembled as a result of a global literature review. A questionnaire survey was conducted, and the obtained data were analyzed using a relative importance index for each PDRPM factor. Findings are presented in six groups:housing approaches, organizational behavior, project funding, supply chain and logistics, communication and coordination, and PDRPM context. Findings indicate that the most significant factors that influence PDRPM for housing provision in the Gaza Strip are related to issues associated with financial resources. It is critical that sufficient funding should be available in order to allow organizations to undertake housing projects in an effective and efficient way. Joint efforts are required from international donors and local organizations in order to effectively manage financial resources with the ultimate goal of improving PDRPM for housing provision.
Economic and Human Loss Empirical Models for Earthquakes in the Mediterranean Region, with Particular Focus on Algeria
Abdelheq Guettiche, Philippe Guéguen, Mostefa Mimoune
2017, 8(4): 415-434. doi: 10.1007/s13753-017-0153-6
In this study, loss estimation models were developed for reasonably accurate assessment of economic and human losses from seismic events in the Mediterranean region, based on damage assessment at an urban scale. Data were compiled from existing worldwide databases, and completed with earthquake information from regional studies. Economic data were converted to a single common currency unit (2015 USD value) and the wealth of the areas affected by 65 earthquakes of the region from 1900 to 2015 was assessed. Reduced-form models were used to determine economic and human losses, with earthquake magnitude and intensity as hazard-related variables, and gross domestic product of the affected area and the affected population as exposure-related variables. Damage to buildings was also used as a hazard-related variable to predict economic and human losses. Finally, site-specific regression models were proposed for economic and human losses due to earthquakes in the Mediterranean region, and more specifically, in Algeria. We show that by introducing the damage variable into the models, prediction error can be reduced, and that accuracy of loss model estimation is site dependent and requires regional data on earthquake losses to improve. A case study for Constantine, Algeria shows the improvements needed for increased accuracy.
Modeling Impact of Natural Hazard-Induced Disasters on Income Distribution in the United States
Lin Fang, Jiayu Wu, Tatjana Miljkovic
2017, 8(4): 435-444. doi: 10.1007/s13753-017-0148-3
Economic damage due to hurricane activities has been shown to impact income inequality in the coastal states of the United States. We consider 17 other natural hazards, in addition to hurricanes, that affected the entire United States for the period 1970-2013. Two fixed effects models were developed to quantify the relationship between income inequality and economic and demographic variables, including crop and property losses from natural hazard-induced disasters. These models include state-byyear and region-by-year fixed effects models. Our findings show that the damages from all natural hazards impact income distribution across the United States, not only in hurricane-affected areas, but also in non-hurricane states. The results of our study have important implications for the insurance industry and government policymakers.
Different Mortality Effects of Extreme Temperature Stress in Three Large City Clusters of Northern and Southern China
Lingyan Zhang, Zhao Zhang, Chenzhi Wang, Maigeng Zhou, Peng Yin
2017, 8(4): 445-456. doi: 10.1007/s13753-017-0149-2
Extreme temperature events have affected Chinese city residents more frequently and intensively since the early 2000s, but few studies have identified the impacts of extreme temperature on mortality in different city clusters of China. This study first used a distributed lag, nonlinear model to estimate the county/district-specific effects of extreme temperature on nonaccidental and cardiovascular mortality. The authors then applied a multivariate meta-analysis to pool the estimated effects in order to derive regional temperature-mortality relationship in three large city clusters-the Beijing-Tianjin-Hebei (BTH) region, the Yangtze River Delta (YRD), and the Pearl River Delta (PRD), which represent northern and southern regions. With 0-3 days' lag, the strongest heat-related mortality effect was observed in the BTH region (with relative risk (RR) of 1.29; 95% confidence interval (CI):1.13-1.47), followed by the YRD (RR=1.25; 95% CI:1.13-1.35) and the PRD (RR=1.14; 95% CI:1.01-1.28) areas. With 0-21 days' lag, the cold effect was pronounced in all city clusters, with the highest extreme cold-related mortality risk found in the PRD area (RR=2.27; 95% CI:1.63-3.16), followed by the YRD area (RR=1.85; 95% CI:1.56-2.20) and BTH region (RR=1.33; 95% CI:0.96-1.83). People in the southern regions tended to be more vulnerable to cold stress, but the northern population was more sensitive to heat stress. By examining the effects of extreme temperature in city clusters of different regions, our findings underline the role of adaptation towards heat and cold, which has important implications for public health policy making and practice.
Relationships Between Evacuation Population Size, Earthquake Emergency Shelter Capacity, and Evacuation Time
Xiujuan Zhao, Wei Xu, Yunjia Ma, Lianije Qin, Junlin Zhang, Ying Wang
2017, 8(4): 457-470. doi: 10.1007/s13753-017-0157-2
Determining the location of earthquake emergency shelters and the allocation of affected population to them are key issues that face shelter planning and emergency management. To solve this emergency shelter location-allocation problem, evacuation time and the construction cost of shelters-both influenced by the evacuation population size and its spatial distribution-are two important considerations. In this article, a mathematical model with two objectives-to minimize total weighted evacuation time (TWET) and total shelter area (TSA)-is allied with a modified particle swarm optimization algorithm to address the problem. The relationships between evacuation population size, evacuation time, and total shelter area are examined using Jinzhan Town in Chaoyang District of Beijing, China, as a case study. The results show that TWET has a power function relationship with TSA under different population size scenarios, and a linear function applies between evacuation population and TWET under different TSAs. The joint relationships of TSA, TWET, and population size show that TWET increases with population increase and TSA decrease, and compared with TSA, population influences TWET more strongly. Given a reliable projection of population change and spatial planning of a study area, this method can be useful for government decision making on the location of earthquake emergency shelters and on the allocation of evacuees to those shelters.
Quantifying Disaster Physical Damage Using Remote Sensing Data—A Technical Work Flow and Case Study of the 2014 Ludian Earthquake in China
Yida Fan, Qi Wen, Wei Wang, Ping Wang, Lingling Li, Peng Zhang
2017, 8(4): 471-488. doi: 10.1007/s13753-017-0143-8
Disaster damage assessment is an important basis for the objective assessment of the social impacts of disasters and for the planning of recovery and reconstruction. It is also an important research field with regard to disaster mitigation and risk management. Quantitative assessment of physical damage refers to the determination of the physical damage state of the exposed elements in a disaster area, reflecting the aggregate quantities of damages. It plays a key role in the comprehensive damage assessment of major natural hazard-induced disasters. The National Disaster Reduction Center of China has established a technical work flow for the quantitative assessment of disaster physical damage using remote sensing data. This article presents a quantitative assessment index system and method that can be integrated with high-resolution remote sensing data, basic geographical data, and field survey data. Following the 2014 Ludian Earthquake in Yunnan Province, China, this work flow was used to assess the damage to buildings, roads, and agricultural and forest resources, and the assessment results were incorporated into the Disaster Damage Comprehensive Assessment Report of the 2014 Ludian Earthquake for the State Council of China. This article also outlines some possible improvements that can be addressed in future work.
Understanding the El Niño Costero of 2017: The Definition Problem and Challenges of Climate Forecasting and Disaster Responses
Ivan J. Ramírez, Fernando Briones
2017, 8(4): 489-492. doi: 10.1007/s13753-017-0151-8
This preliminary study examines the definition problem and challenges of climate forecasting and disaster responses associated with the El Niño costero (coastal) of 2017, which developed rapidly with no warning and had catastrophic effects in Peru. Such a localized El Niño was not documented since 1925. An initial review suggests that in addition to the characteristics of the event (surprise), government responses may have been inadequate (as media reported) because of conflicting forecast reports (U.S. and Peru), which provoked a hydrometeorological debate and stifled decision making. Partly to blame was the El Niño definition problem, which can cause uncertainty and affect perception of risk, depending on which region of the equatorial Pacific one uses to identify an event. Responses were further complicated by the fact that some regions within Peru were experiencing drought prior to the El Niño costero's onset and impacts from the El Niño 2015-2016 were less than expected. Furthermore, a new government was in place, which may have hindered action. Thus, El Niño costero provides lessons to heed, not only with respect to the forecast information, but also with reference to the context of the forecast and disaster setting, which can influence disaster responses to hydrometeorological threats.
Glacial Lake Outburst Flood Disasters and Integrated Risk Management in China
Shijin Wang, Lanyue Zhou
2017, 8(4): 493-497. doi: 10.1007/s13753-017-0152-7
High-risk areas for glacial lake outburst flood (GLOF) disasters in China are mainly concentrated in the middle-eastern Himalayas and Nyainqêntanglha (Nyenchen Tanglha Mountains), Tibetan Plateau. In the past 20 years, glaciers in these regions have retreated and thinned rapidly as a response to regional climate warming, leading to the formation of new glacial lakes and the expansion of existing glacial lakes. These areas are located in the border belt between the Indian and the Eurasian plates, where tectonic seismic activity is also frequent and intense. Earthquakes have often compromised the stability of mountain slopes, glaciers, and moraine dams, resulting in an imbalance in the state of glacial lakes and an increase of loose materials in valleys. It is foreseeable that the possibility of GLOFs and disaster occurrence will be great in the context of frequent earthquakes and continued climate warming. This article presents the temporal and spatial characteristics of GLOF disasters, as well as the conditions and mechanisms of GLOF disaster formation, and proposes an integrated risk management strategy to cope with GLOF disasters. It aims to facilitate the mitigation of the impacts of GLOF disasters on mountain economic and social systems, and improve disaster risk analysis, as well as the capability of risk management and disaster prevention and reduction.
The 4th World Landslide Forum: Landslide Research and Risk Reduction for Advancing the Culture of Living with Natural Hazards
Irasema Alcántara-Ayala, Kyoji Sassa, Matjaž Mikoš, Quinli Han, Jakob Rhyner, Kaoru Takara, Satoru Nishikawa, Badaoui Rouhban, Sálvano Briceño
2017, 8(4): 498-502. doi: 10.1007/s13753-017-0139-4
The World Landslide Forum is a triennial mainstream conference that gathers together the scientific and technological community, policymakers, industry actors, public officials, and other stakeholders, who deal with the understanding and management of landslide disaster risk. The establishment of the ISDR-ICL Sendai Partnerships 2015-2025 for Global Promotion of Understanding and Reducing Landslide Disaster Risk in Sendai during the 2015 World Conference on Disaster Risk Reduction (WCDRR) enabled the landslide science and technology community support the implementation of the Sendai Framework for Disaster Risk Reduction 2015-2030 in order to prevent new and reduce existing disaster risk. The 4th World Landslide Forum (WLF4) was held in Ljubljana, Slovenia, from 29 May to 2 June 2017 and discussed the progress of landslide research and risk reduction for advancing the culture of living with natural hazards. A high-level panel composed of United Nations officials, international stakeholders, and national organizations sought to identify the best mechanisms to be developed by the community of the International Consortium on Landslides (ICL). The objective was to advance the implementation of the ISDR-ICL Sendai Partnerships, to achieve a better commitment among partners, and to provide substantive services to developing countries. During the WLF4, the 2017 Ljubljana Declaration on Landslide Risk Reduction was adopted and the concept framework of the Kyoto 2020 Commitment was endorsed.