International Frameworks for Disaster Risk Reduction: Useful Guidance for Sustainable Mountain Development?

In recent decades, a number of global frameworks have been developed for disaster risk reduction (DRR). The Hyogo Framework for Action 2005–2015 and its successor document, the Sendai Framework for Disaster Risk Reduction, adopted in Japan in March 2015, provide general guidance for reducing risks from natural hazards. This is particularly important for mountainous areas, but DRR for mountain areas and sustainable mountain development received little attention in the recent policy debate. The question remains whether the Hyogo and Sendai frameworks can provide guidance for sustainable mountain development. This article evaluates the 2 frameworks in light of the special challenges of DRR in mountain areas and argues that, while the frameworks offer valuable guidance, they need to be further adapted for local contexts—particularly for mountain areas, which require special attention because of changing risk patterns like the effects of climate change and high land-use pressure.

Molecular Consequences of the SERPINH1/HSP47 Mutation in the Dachshund Natural Model of Osteogenesis Imperfecta.

Osteogenesis imperfecta (OI) is a heritable connective tissue disease characterized by bone fragility and increased risk of fractures. Up to now, mutations in at least 18 genes have been associated with dominant and recessive forms of OI that affect the production or post-translational processing of procollagen or alter bone homeostasis. Among those, SERPINH1 encoding heat shock protein 47 (HSP47), a chaperone exclusive for collagen folding in the ER, was identified to cause a severe form of OI in dachshunds (L326P) as well as in humans (one single case with a L78P mutation). To elucidate the disease mechanism underlying OI in the dog model, we applied a range of biochemical assays to mutant and control skin fibroblasts as well as on bone samples. These experiments revealed that type I collagen synthesized by mutant cells had decreased electrophoretic mobility. Procollagen was retained intracellularly with concomitant dilation of ER cisternae and activation of the ER stress response markers GRP78 and phospho-eIF2α, thus suggesting a defect in procollagen processing. In line with the migration shift detected on SDS-PAGE of cell culture collagen, extracts of bone collagen from the OI dog showed a similar mobility shift, and on tandem mass spectrometry, the chains were post-translationally overmodified. The bone collagen had a higher content of pyridinoline than control dog bone. We conclude that the SERPINH1 mutation in this naturally occurring model of OI impairs how HSP47 acts as a chaperone in the ER. This results in abnormal post-translational modification and cross-linking of the bone collagen.

Monitoring the temporal development of natural hazard risks as a basis indicator for climate change adaptation.

The potential effects of climatic changes on natural risks are widely discussed. But the formulation of strategies for adapting risk management practice to climate changes requires knowledge of the related risks for people and economic values. The main goals of this work were (1) the development of a method for analysing and comparing risks induced by different natural hazard types, (2) highlighting the most relevant natural hazard processes and related damages, (3) the development of an information system for the monitoring of the temporal development of natural hazard risk and (4) the visualisation of the resulting information for the wider public. A comparative exposure analysis provides the basis for pointing out the hot spots of natural hazard risks in the province of Carinthia, Austria. An analysis of flood risks in all municipalities provides the basis for setting the priorities in the planning of flood protection measures. The methods form the basis for a monitoring system that periodically observes the temporal development of natural hazard risks. This makes it possible firstly to identify situations in which natural hazard risks are rising and secondly to differentiate between the most relevant factors responsible for the increasing risks. The factors that most influence the natural risks could be made evident.

Spatial variability and potential impacts of climate change on flood and debris flow hazard zone mapping and implications for risk management

The main goals of this study were to identifythe alpine torrent catchments that are sensitive to climatic changes and to assess the robustness of the methods for the elaboration of flood and debris flow hazard zone maps to specific effects of climate changes. In this study, a procedure for the identification and localization of torrent catchments in which the climate scenarios will modify the hazard situation was developed. In two case studies, the impacts of a potential increase of precipitation intensities to the delimited hazard zones were studied. The identification and localization of the torrent and river catchments, where unfavourable changes in the hazard situation occur, could eliminate speculative and unnecessary measures against the impacts of climate changes like a general enlargement of hazard zones or a general over dimensioning of protection structures for the whole territory. The results showed a high spatial variability of the sensitivity of catchments to climate changes. In sensitive catchments, the sediment management in alpine torrents will meet future challenges due to a higher rate for sediment removal from retention basins. The case studies showed a remarkable increase of the areas affected by floods and debris flow when considering possible future precipitation intensities in hazard mapping. But, the calculated increase in extent of future hazard zones lay within the uncertainty of the methods used today for the delimitation of the hazard zones. Thus, the consideration of the uncertainties laying in the methods for the elaboration of hazard zone maps in the torrent and river catchments sensitive to climate changes would provide a useful instrument for the consideration of potential future climate conditions. The study demonstrated that weak points in protection structures in future will become more important in risk management activities.

Avalanche risk assessment - a multi-temporal approach, results from Galtür, Austria

Snow avalanches pose a threat to settlements and infrastructure in alpine environments. Due to the catastrophic events in recent years, the public is more aware of this phenomenon. Alpine settlements have always been confronted with natural hazards, but changes in land use and in dealing with avalanche hazards lead to an altering perception of this threat. In this study, a multi-temporal risk assessment is presented for three avalanche tracks in the municipality of Galtür, Austria. Changes in avalanche risk as well as changes in the risk-influencing factors (process behaviour, values at risk (buildings) and vulnerability) between 1950 and 2000 are quantified. An additional focus is put on the interconnection between these factors and their influence on the resulting risk. The avalanche processes were calculated using different simulation models (SAMOS as well as ELBA+). For each avalanche track, different scenarios were calculated according to the development of mitigation measures. The focus of the study was on a multi-temporal risk assessment; consequently the used models could be replaced with other snow avalanche models providing the same functionalities. The monetary values of buildings were estimated using the volume of the buildings and average prices per cubic meter. The changing size of the buildings over time was inferred from construction plans. The vulnerability of the buildings is understood as a degree of loss to a given element within the area affected by natural hazards. A vulnerability function for different construction types of buildings that depends on avalanche pressure was used to assess the degree of loss. No general risk trend could be determined for the studied avalanche tracks. Due to the high complexity of the variations in risk, small changes of one of several influencing factors can cause considerable differences in the resulting risk. This multi-temporal approach leads to better understanding of the today's risk by identifying the main changes and the underlying processes. Furthermore, this knowledge can be implemented in strategies for sustainable development in Alpine settlements.

Modelling the system behaviour of wet snow avalanches using an expert system approach for risk management on high alpine traffic roads

The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.

Temporal variability of damage potential on roads as a conceptual contribution towards a short-term avalanche risk simulation

The fatality risk caused by avalanches on road networks can be analysed using a long-term approach, resulting in a mean value of risk, and with emphasis on short-term fluctuations due to the temporal variability of both, the hazard potential and the damage potential. In this study, the approach for analysing the long-term fatality risk has been adapted by modelling the highly variable short-term risk. The emphasis was on the temporal variability of the damage potential and the related risk peaks. For defined hazard scenarios resulting from classified amounts of snow accumulation, the fatality risk was calculated by modelling the hazard potential and observing the traffic volume. The avalanche occurrence probability was calculated using a statistical relationship between new snow height and observed avalanche releases. The number of persons at risk was determined from the recorded traffic density. The method resulted in a value for the fatality risk within the observed time frame for the studied road segment. The long-term fatality risk due to snow avalanches as well as the short-term fatality risk was compared to the average fatality risk due to traffic accidents. The application of the method had shown that the long-term avalanche risk is lower than the fatality risk due to traffic accidents. The analyses of short-term avalanche-induced fatality risk provided risk peaks that were 50 times higher than the statistical accident risk. Apart from situations with high hazard level and high traffic density, risk peaks result from both, a high hazard level combined with a low traffic density and a high traffic density combined with a low hazard level. This provided evidence for the importance of the temporal variability of the damage potential for risk simulations on road networks. The assumed dependence of the risk calculation on the sum of precipitation within three days is a simplified model. Thus, further research is needed for an improved determination of the diurnal avalanche probability. Nevertheless, the presented approach may contribute as a conceptual step towards a risk-based decision-making in risk management.

Outcomes of Active Surveillance for Ductal Carcinoma in Situ: A Computational Risk Analysis.

BACKGROUND Ductal carcinoma in situ (DCIS) is a noninvasive breast lesion with uncertain risk for invasive progression. Usual care (UC) for DCIS consists of treatment upon diagnosis, thus potentially overtreating patients with low propensity for progression. One strategy to reduce overtreatment is active surveillance (AS), whereby DCIS is treated only upon detection of invasive disease. Our goal was to perform a quantitative evaluation of outcomes following an AS strategy for DCIS. METHODS Age-stratified, 10-year disease-specific cumulative mortality (DSCM) for AS was calculated using a computational risk projection model based upon published estimates for natural history parameters, and Surveillance, Epidemiology, and End Results data for outcomes. AS projections were compared with the DSCM for patients who received UC. To quantify the propagation of parameter uncertainty, a 95% projection range (PR) was computed, and sensitivity analyses were performed. RESULTS Under the assumption that AS cannot outperform UC, the projected median differences in 10-year DSCM between AS and UC when diagnosed at ages 40, 55, and 70 years were 2.6% (PR = 1.4%-5.1%), 1.5% (PR = 0.5%-3.5%), and 0.6% (PR = 0.0%-2.4), respectively. Corresponding median numbers of patients needed to treat to avert one breast cancer death were 38.3 (PR = 19.7-69.9), 67.3 (PR = 28.7-211.4), and 157.2 (PR = 41.1-3872.8), respectively. Sensitivity analyses showed that the parameter with greatest impact on DSCM was the probability of understaging invasive cancer at diagnosis. CONCLUSION AS could be a viable management strategy for carefully selected DCIS patients, particularly among older age groups and those with substantial competing mortality risks. The effectiveness of AS could be markedly improved by reducing the rate of understaging.

Network Dynamics in Natural Resource Governance: A Case Study of Swiss Landscape Management

Structural characteristics of social networks have been recognized as important factors of effective natural resource governance. However, network analyses of natural resource governance most often remain static, even though governance is an inherently dynamic process. In this article, we investigate the evolution of a social network of organizational actors involved in the governance of natural resources in a regional nature park project in Switzerland. We ask how the maturation of a governance network affects bonding social capital and centralization in the network. Applying separable temporal exponential random graph modeling (STERGM), we test two hypotheses based on the risk hypothesis by Berardo and Scholz (2010) in a longitudinal setting. Results show that network dynamics clearly follow the expected trend toward generating bonding social capital but do not imply a shift toward less hierarchical and more decentralized structures over time. We investigate how these structural processes may contribute to network effectiveness over time.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Firm-level impacts of natural disasters on production networks : evidence from a flood in Thailand

In this paper, we explore the firm-level impacts of flooding in Thailand in 2011, specifically those on the procurement patterns at Japanese affiliates in Thailand. Our findings are as follow. First, the damaged small firms are more likely to lower their local procurement share, particularly the share of procurement from other Japanese-owned firms in Thailand. Second, damaged young firms and damaged old firms are more likely to raise the shares of imports from Japan and China, respectively. Third, there are no impacts on imports from ASEAN and other countries. These findings are useful for uncovering how multinational firms adjust their production networks before and after natural disasters.

Survey and brain storming studies about machines, constructions, human and environmental risk consideration in the careers of the Universidad Politécnica of Madrid

The Universidad Politécnica of Madrid (UPM) includes schools and faculties that were for engineering degrees, architecture and computer science, that are now in a quick EEES Bolonia Plan metamorphosis getting into degrees, masters and doctorate structures. They are focused towards action in machines, constructions, enterprises, that are subjected to machines, human and environment created risks. These are present in actions such as use loads, wind, snow, waves, flows, earthquakes, forces and effects in machines, vehicles behavior, chemical effects, and other environmental factors including effects of crops, cattle and beasts, forests, and varied essential economic and social disturbances. Emphasis is for authors in this session more about risks of natural origin, such as for hail, winds, snow or waves that are not exactly known a priori, but that are often considered with statistical expected distributions giving extreme values for convenient return periods. These distributions are known from measures in time, statistic of extremes and models about hazard scenarios and about responses of man made constructions or devices. In each engineering field theories were built about hazards scenarios and how to cover for important risks. Engineers must get that the systems they handle, such as vehicles, machines, firms or agro lands or forests, obtain production with enough safety for persons and with decent economic results in spite of risks. For that risks must be considered in planning, in realization and in operation, and safety margins must be taken but at a reasonable cost. That is a small level of risks will often remain, due to limitations in costs or because of due to strange hazards, and maybe they will be covered by insurance in cases such as in transport with cars, ships or aircrafts, in agro for hail, or for fire in houses or in forests. These and other decisions about quality, security for men or about business financial risks are sometimes considered with Decision Theories models, using often tools from Statistics or operational Research. The authors have done and are following field surveys about risk consideration in the careers in UPM, making deep analysis of curricula taking into account the new structures of degrees in the EEES Bolonia Plan, and they have considered the risk structures offered by diverse schools of Decision theories. That gives an aspect of the needs and uses, and recommendations about improving in the teaching about risk, that may include special subjects especially oriented for each career, school or faculty, so as to be recommended to be included into the curricula, including an elaboration and presentation format using a multi-criteria decision model.

Geochemistry and risk assessment of street dust in Luanda, Angola, a tropical urban environment

A total of 92 samples of street dust were collected in Luanda, Angola, were sieved below 100 μm, and analysed by ICP-MS for 35 elements after an aqua-regia digestion. The concentration and spatial heterogeneity of trace elements in the street dust of Luanda are generally lower than in most industrialized cities in the Northern hemisphere. These observations reveal a predominantly “natural” origin for the street dust in Luanda, which is also manifested in that some geochemical processes that occur in natural soils are preserved in street dust: the separation of uranium from thorium, and the retention of the former by carbonate materials, or the high correlation between arsenic and vanadium due to their common mode of adsorption on solid particles in the form of oxyanions. The only distinct anthropogenic fingerprint in the composition of Luanda's street dust is the association Pb–Cd–Sb–Cu (and to a lesser extent, Ba–Cr–Zn). The use of risk assessment strategies has proved helpful in identifying the routes of exposure to street dust and the trace elements therein of most concern in terms of potential adverse health effects. In Luanda the highest levels of risk seem to be associated (a) with the presence of As and Pb in the street dust and (b) with the route of ingestion of dust particles, for all the elements included in the study except Hg, for which inhalation of vapours presents a slightly higher risk than ingestion. However, given the large uncertainties associated with the estimates of toxicity values and exposure factors, and the absence of site-specific biometric factors, these results should be regarded as preliminary and further research should be undertaken before any definite conclusions regarding potential health effects are drawn.

Impact attribution models to evaluate drought effects: economic impacts, risk analyses and management strategies in Spain and Chile

La sequía es un fenómeno natural que se origina por el descenso de las precipitaciones con respecto a una media, y que resulta en la disponibilidad insuficiente de agua para alguna actividad. La creciente presión que se ha venido ejerciendo sobre los recursos hídricos ha hecho que los impactos de la sequía se hayan visto agravados a la vez que ha desencadenado situaciones de escasez de agua en muchas partes del planeta. Los países con clima mediterráneo son especialmente vulnerables a las sequías, y, su crecimiento económico dependiente del agua da lugar a impactos importantes. Para reducir los impactos de la sequía es necesaria una reducción de la vulnerabilidad a las sequías que viene dada por una gestión más eficiente y por una mejor preparación. Para ello es muy importante disponer de información acerca de los impactos y el alcance de este fenómeno natural. Esta investigación trata de abarcar el tema de los impactos de las sequías, de manera que plantea todos los tipos de impactos que pueden darse y además compara sus efectos en dos países (España y Chile). Para ello se proponen modelos de atribución de impactos que sean capaces de medir las pérdidas económicas causadas por la falta de agua. Los modelos propuestos tienen una base econométrica en la que se incluyen variables clave a la hora de evaluar los impactos como es una variable relacionada con la disponibilidad de agua, y otras de otra naturaleza para distinguir los efectos causados por otras fuentes de variación. Estos modelos se adaptan según la fase del estudio en la que nos encontremos. En primer lugar se miden los impactos directos sobre el regadío y se introduce en el modelo un factor de aleatoriedad para evaluar el riesgo económico de sequía. Esto se hace a dos niveles geográficos (provincial y de Unidad de Demanda Agraria) y además en el último se introduce no solo el riesgo de oferta sino también el riesgo de demanda de agua. La introducción de la perspectiva de riesgo en el modelo da lugar a una herramienta de gestión del riesgo económico que puede ser utilizada para estrategias de planificación. Más adelante una extensión del modelo econométrico se desarrolla para medir los impactos en el sector agrario (impactos directos sobre el regadío y el secano e impactos indirectos sobre la Agro Industria) para ello se adapta el modelo y se calculan elasticidades concatenadas entre la falta de agua y los impactos secundarios. Por último se plantea un modelo econométrico para el caso de estudio en Chile y se evalúa el impacto de las sequías debidas al fenómeno de La Niña. iv Los resultados en general muestran el valor que brinda el conocimiento más preciso acerca de los impactos, ya que en muchas ocasiones se tiende a sobreestimar los daños realmente producidos por la falta de agua. Los impactos indirectos de la sequía confirman su alcance a la vez que son amortiguados a medida que nos acercamos al ámbito macroeconómico. En el caso de Chile, su diferente gestión muestra el papel que juegan el fenómeno de El Niño y La Niña sobre los precios de los principales cultivos del país y sobre el crecimiento del sector. Para reducir las pérdidas y su alcance se deben plantear más medidas de mitigación que centren su esfuerzo en una gestión eficiente del recurso. Además la prevención debe jugar un papel muy importante para reducir los riesgos que pueden sufrirse ante situaciones de escasez. ABSTRACT Drought is a natural phenomenon that originates by the decrease in rainfall in comparison to the average, and that results in water shortages for some activities. The increasing pressure on water resources has augmented the impact of droughts just as water scarcity has become an additional problem in many parts of the planet. Countries with Mediterranean climate are especially vulnerable to drought, and its waterdependent economic growth leads to significant impacts. To reduce the negative impacts it is necessary to deal with drought vulnerability, and to achieve this objective a more efficient management is needed. The availability of information about the impacts and the scope of droughts become highly important. This research attempts to encompass the issue of drought impacts, and therefore it characterizes all impact types that may occur and also compares its effects in two different countries (Spain and Chile). Impact attribution models are proposed in order to measure the economic losses caused by the lack of water. The proposed models are based on econometric approaches and they include key variables for measuring the impacts. Variables related to water availability, crop prices or time trends are included to be able to distinguish the effects caused by any of the possible sources. These models are adapted for each of the parts of the study. First, the direct impacts on irrigation are measured and a source of variability is introduced into the model to assess the economic risk of drought. This is performed at two geographic levels provincial and Agricultural Demand Unit. In the latter, not only the supply risk is considered but also the water demand risk side. The introduction of the risk perspective into the model results in a risk management tool that can be used for planning strategies. Then an extension of the econometric model is developed to measure the impacts on the agricultural sector (direct impacts on irrigated and rainfed productions and indirect impacts on the Agri-food Industry). For this aim the model is adapted and concatenated elasticities between the lack of water and the impacts are estimated. Finally an econometric model is proposed for the Chilean case study to evaluate the impact of droughts, especially caused by El Niño Southern Oscillation. The overall results show the value of knowing better about the precise impacts that often tend to be overestimated. The models allow for measuring accurate impacts due to the lack of water. Indirect impacts of drought confirm their scope while they confirm also its dilution as we approach the macroeconomic variables. In the case of Chile, different management strategies of the country show the role of ENSO phenomena on main crop prices and on economic trends. More mitigation measures focused on efficient resource management are necessary to reduce drought losses. Besides prevention must play an important role to reduce the risks that may be suffered due to shortages.