Risk Hotspots Research Articles

Assessing, mapping and validating site-specific ecotoxicological risk for pesticide mixtures: A case study for small scale hot spots in aquatic and terrestrial environments

Mixture toxicity is a real world problem and as such requires risk assessment solutions that can be applied within different geographic regions, across different spatial scales and in situations where the quantity of data available for the assessment varies. Moreover, the need for site specific procedures for assessing ecotoxicological risk for non-target species in non-target ecosystems also has to be recognised. The work presented in the paper addresses the real world effects of pesticide mixtures on natural communities. Initially, the location of risk hotspots is theoretically estimated through exposure modelling and the use of available toxicity data to predict potential community effects. The concept of Concentration Addition (CA) is applied to describe responses resulting from exposure of multiple pesticides The developed and refined exposure models are georeferenced (GIS-based) and include environmental and physico-chemical parameters, and site specific information on pesticide usage and land use. As a test of the risk assessment framework, the procedures have been applied on a suitable study areas, notably the River Meolo basin (Northern Italy), a catchment characterised by intensive agriculture, as well as comparative area for some assessments. Within the studied areas, the risks for individual chemicals and complex mixtures have been assessed on aquatic and terrestrial aboveground and belowground communities. Results from ecological surveys have been used to validate these risk assessment model predictions. Value and limitation of the approaches are described and the possibilities for larger scale applications in risk assessment are also discussed.

How robustness and resilience support security business against antagonistic threats in transport network

Supply chain disruptions may derive from various sources but the antagonistic threats are centered in supply chain disruption. Antagonistic threats are dynamic due to the spiral input, processes and feedbacks which create a very complex situation to analyze, assess and making decision. Beside risks, vulnerability derived from supply chain characteristics is the other issue which should be measured. Antagonistic threats are magnified in such vulnerable supply chains. After 9/11, 2001, the Security and Efficiency of the global supply chain has become an important issue in global transportation. This leads firms to consider Supply chain security as part and parcel of a company’s comprehensive risk-management program. In a security business, it is essential to understand different type risks and evaluate transportation assets, do risk based prioritization, and protect customers through cost effective actions. This could be occurred corresponding to risk management methods. Providing security may occur internally by firms or they outsource it to security providers which could be performed in higher quality or more cost effectively. In this article, we focus on managing the risks and securing the supply chain business with the security theory and strategies in the supply chain and transportation network. In order to discover risks throughout the supply chain, security provider needs to find risk hot spots where the likelihood of risk is higher. We propose two approaches (geographical and elements/process) to seek probable risks. The next step is to take strategies for risk prevention and risk mitigation. Consequently, we connect the security strategies from the literature review and collected information from security business to suggest a suitable model of how to handle the risks and achieve security in a systemic and scientific way.

The influence of uncertainty on conservation assessments: Australian frogs as a case study

We evaluated the influence of uncertainty, based on variation in expert opinion, on assessment of conservation status of Australian amphibians. We examined relationships between different biological variables and inferred relative extinction risk, the influence of uncertainty on resulting ranks, and regional patterns of extinction risk and uncertainty. Our results were in general agreement with the International Union for the Conservation of Nature and Natural Resources but also reveal apparent high extinction risks among some taxa that the IUCN did not classify in any threatened category. These differences were exaggerated when the most conservative status assessments were taken from variation in expert opinion. Our assessments of relative extinction risk were strongly dependent on basic demographic variables, particularly population size, geographic distribution of populations and age at first reproduction. We identified regional hotspots of high relative extinction risk and poor knowledge of amphibians, leading to high uncertainty about the conservation status of species from those areas. Regional clustering of species with high relative extinction risk and high uncertainty may indicate higher levels of relative extinction risk than previously assessed. Our results highlight the influence of uncertainty on interpretation of conservation assessments of organism groups with large knowledge gaps. Uncertainty should be further incorporated into conservation planning as it not only highlights taxa with potentially underestimated extinction risk, but also facilitates identification of knowledge gaps informative of conservation status. Knowledge of regional patterns of extinction risk and uncertainty assists conservation planning through identification of regions of high extinction risk and/or large knowledge gaps.

Evaluating Post-Fire Forest Resilience Using GIS and Multi-Criteria Analysis: An Example from Cape Sounion National Park, Greece

Forest fires are one of the major causes of ecological disturbance in the mediterranean climate ecosystems of the world. Despite the fact that a lot of resources have been invested in fire prevention and suppression, the number of fires occurring in the Mediterranean Basin in the recent decades has continued to markedly increase. The understanding of the relationship between landscape and fire lies, among others, in the identification of the system's post-fire resilience. In our study, ecological and landscape data are integrated with decision-support techniques in a Geographic Information Systems (GIS) framework to evaluate the risk of losing post-fire resilience in Pinus halepensis forests, using Cape Sounion National Park, Central Greece, as a pilot case. The multi-criteria decision support approach has been used to synthesize both bio-indicators (woody cover, pine density, legume cover and relative species richness and annual colonizers) and geo-indicators (fire history, parent material, and slope inclination) in order to rank the landscape components. Judgments related to the significance of each factor were incorporated within the weights coefficients and then integrated into the multicriteria rule to map the risk index. Sensitivity analysis was very critical for assessing the contribution of each factor and the sensitivity to subjective weight judgments to the final output. The results of this study include a final ranking map of the risk of losing resilience, which is very useful in identifying the "risk hotspots", where post-fire management measures should be applied in priority.

Risk Clusters, Hotspots, and Spatial Intelligence: Risk Terrain Modeling as an Algorithm for Police Resource Allocation Strategies

The study reported here follows the suggestion by Caplan et al. (Justice Q, 2010) that risk terrain modeling (RTM) be developed by doing more work to elaborate, operationalize, and test variables that would provide added value to its application in police operations. Building on the ideas presented by Caplan et al., we address three important issues related to RTM that sets it apart from current approaches to spatial crime analysis. First, we address the selection criteria used in determining which risk layers to include in risk terrain models. Second, we compare the “best model” risk terrain derived from our analysis to the traditional hotspot density mapping technique by considering both the statistical power and overall usefulness of each approach. Third, we test for “risk clusters” in risk terrain maps to determine how they can be used to target police resources in a way that improves upon the current practice of using density maps of past crime in determining future locations of crime occurrence. This paper concludes with an in depth exploration of how one might develop strategies for incorporating risk terrains into police decision-making. RTM can be developed to the point where it may be more readily adopted by police crime analysts and enable police to be more effectively proactive and identify areas with the greatest probability of becoming locations for crime in the future. The targeting of police interventions that emerges would be based on a sound understanding of geographic attributes and qualities of space that connect to crime outcomes and would not be the result of identifying individuals from specific groups or characteristics of people as likely candidates for crime, a tactic that has led police agencies to be accused of profiling. In addition, place-based interventions may offer a more efficient method of impacting crime than efforts focused on individuals.

Fish allergy risk derived from ambiguous vernacular fish names: Forensic DNA-based detection in Greek markets

Some fish species, like hakes, are amongst the most allergenic seafood species and represent a high proportion of food allergies, particularly in children. Seafood mislabelling or incomplete labelling may enhance inadvertent consumption of allergenic species. The problem can be accentuated in countries where vernacular names do not distinguish fish species, like in Greece, where hake, cod and other Gadoids are generically named with the same Greek word Bakaliaros. The purpose of the study was to detect and quantify allergenic fish species contained in commercial seafood labelled with generic and unspecific names. Commercial samples were obtained at random from Greek fish markets and fish species were identified based on PCR fragments of the 5S rDNA. Almost 85% of the analysed products contained highly allergenic hake or grenadier species and only 15% contained less allergenic species like cod and haddock. We conclude that commercial fish markets are potential hotspots of allergy risk, and suggest labelling containing species names and consumer education for reading labels as preventive measures.

An inventory-based approach for modeling single-tree storm damage — experiences with the winter storm of 1999 in southwestern Germany

Based on individual tree damage data dating back to the gale “Lothar” (winter 1999) in Baden-Württemberg, Germany, a statistical model was developed to estimate the risk of storm damage for individual trees. The data were compiled from the National German Forest Inventory. The model attempts to separate the effects of tree-specific variables, topography, site conditions and flow field related effects on damage probability. The crucial problem of missing information on the actual flow field parameters was solved by applying a generalized additive model that enables the simultaneous fit of a spatial trend function. The geographical location of risk hotspots as predicted by the model correspond well to the actual distribution pattern of storm damage as assessed by the forest service. Tree height proved to be one of the most important factors affecting the level of damage, while height to diameter at breast height ratio influences damage probability to a much lesser extent. The Norway spruce ( Picea abies (L.) Karst.) group has the highest potential to be damaged followed by the silver fir ( Abies alba Miller) – Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) group and the Scots pine ( Pinus sylvestris L.) – larches ( Larix spp.) group. Predicted probabilities for deciduous trees are generally lower than those of conifers. West- to south-exposed locations bear a considerably higher damage risk and waterlogged soils show an increased predicted probability compared with slightly or not waterlogged soils.

Adaptive urban governance: new challenges for the second generation of urban adaptation strategies to climate change

The task of adapting cities to the impacts of climate change is of great importance—urban areas are hotspots of high risk given their concentrations of population and infrastructure; their key roles for larger economic, political and social processes; and their inherent instabilities and vulnerabilities. Yet, the discourse on urban climate change adaptation has only recently gained momentum in the political and scientific arena. This paper reviews the recent climate change adaptation strategies of nine selected cities and analyzes them in terms of overall vision and goals, baseline information used, direct and indirect impacts, proposed structural and non-structural measures, and involvement of formal and informal actors. Against this background, adaptation strategies and challenges in two Vietnamese cities are analyzed in detail, namely Ho Chi Minh City and Can Tho. The paper thereby combines a review of formalized city-scale adaptation strategies with an empirical analysis of actual adaptation measures and constraints at household level. By means of this interlinked and comparative analysis approach, the paper explores the achievements, as well as the shortcomings, in current adaptation approaches, and generates core issues and key questions for future initiatives in the four sub-categories of: (1) knowledge, perspectives, uncertainties and key threats; (2) characteristics of concrete adaptation measures and processes; (3) interactions and conflicts between different strategies and measures; (4) limits of adaptation and tipping points. In conclusion, the paper calls for new forms of adaptive urban governance that go beyond the conventional notions of urban (adaptation) planning. The proposed concept underlines the need for a paradigm shift to move from the dominant focus on the adjustment of physical structures towards the improvement of planning tools and governance processes and structures themselves. It addresses in particular the necessity to link different temporal and spatial scales in adaptation strategies, to acknowledge and to mediate between different types of knowledge (expert and local knowledge), and to achieve improved integration of different types of measures, tools and norm systems (in particular between formal and informal approaches).

Disaster Risk Reduction: Cases from urban Africa

Very little has been written on the growing number of urban disaster risk hotspots, or the integration of disaster risk reduction and human settlement planning in Africa aside from publications by the World Bank, United Nations and a few other international organisations. This book aspires to fill these gaps, and I recommend it as essential reading for any urban development or disaster management practitioner or academic concerned with risk reduction in African cities. I also recommended the book for courses on sustainable human settlements, development planning and disaster risk reduction.

Economic Sources and Spatial Distribution of Airborne Chromium Risks in the U.S.

We present a model that integrates the economic input-output approach of life cycle assessment with environmental fate, exposure, and risk assessment to estimate the spatial distribution of air toxic health risks due to sector-specific economic activity in the U.S. The model is used to relate the economic activity and exposure potential (population density and meteorology) associated with point source emissions of the heavy metal and carcinogen, hexavalent chromium, or Cr(VI), on a county basis. Total direct annual airborne emissions of Cr(VI) in the U.S. were 44 tonnes in 2002, with 97% from facilities in four major sectors: power generation, wood, plastics, and chemicals, metals, and scientific services. These include 6 tonnes of Cr(VI) emitted in the supply chains of these sectors. A highly variable national distribution of lifetime cancer risk is predicted, with a population-weighted mean of 2.7 x 10(-7), but with hot-spot counties with lifetime risks as high as 6 x 10(-6). Furthermore, high exposures and risks tend to occur in more highly populated counties. In particular, the population of Los Angeles County is exposed to the highest level of risk in the country and almost three-quarters of the total predicted cancer incidence due to inhalation of airborne Cr(VI) emissions. This finding can be attributed largely to the use of Cr(VI) as a corrosion inhibitor by the scientific services sector facilities in the county, the use of shorter facility stacks, and their sitting within a highly populated area. These results indicate that linking economic activity, emission estimates, and fate and transport models for air toxics can inform both life cycle impact and comparative health risk assessments, allowing us to better target emission reductions to minimize hot-spots of risk.

INTEGRATED ASSESSMENT OF WASTEWATER TREATMENT PLANTS FOR SUSTAINABLE RIVER BASIN MANAGEMENT

Sustainable water management is based onto an integrated approach that considers, among the others aspects, strategic planning, operational practices and infrastructure development, the last one being the most important challenge in this field for Romania because of the severe problems related to the outdated treatment infrastructure. Wastewater treatment plants (WWTPs) represent a critical point in ensuring the sustainable use of water resources, as they directly affect the quality of aquatic environment and from this point of view, there is an urgent need to develop simple and reliable instruments for performance evaluation and prioritization of actions. This paper presents the assessment of seven WWTPs from Iasi County, Romania by applying an integrated methodology that considers the environmental risk as a function of the environmental impacts and their respective probabilities. This method allows the quantification of environmental impacts and associated risks based on multiple water quality indicators and it allows an in depth analysis of the impacts and risks components, proving thus, a valuable instrument for supporting the analysis and decision making processes within integrated river basin management. In this way, the identification and prioritization of the impact and risk hotspots of wastewater infrastructure in a river basin have been realized. The results have showed that the highest impacts and risks are caused by the rural WWTPs, while the lowest impacts and risks are induced by the urban centers, although they produce the highest outlet effluent flows. Furthermore, the assessment has revealed that the main risks induced by the WWTPs are given by the very high ammonia concentrations in the discharge flows. The study concludes that unless the efficiency of the WWTPs increases, the risks remain very high and the magnitude of the polluting events may also cause irreversible damages to the receiving water bodies.

A Culture of Neglect: Climate Discourse and Disabled People

A Culture of Neglect: Climate Discourse and Disabled People

Secondary invasion of the round goby into high diversity Great Lakes tributaries and species at risk hotspots: potential new concerns for endangered freshwater species

The round goby (Neogobius melanostomus) first invaded North America in 1990 when it was discovered in the St. Clair River. Despite more than 15 years of potential invasion, many Great Lakes’ lotic systems remained uninvaded. Recently, we captured the round goby from several Great Lakes tributaries known as species-at-risk hotspots. With a combination of field sampling of round gobies and literature review of the impact of round gobies on native taxa, we assess the potential impacts of the secondary invasion to native species using three mechanisms: competition; predation; and indirect impacts from the loss of obligate mussel hosts. We estimate that 89% (17/19) of benthic fishes and 17% (6/36) of mussels that occur in these systems are either known or suspected to be impacted by the secondary invasion of round goby. In particular, we note that the distribution of potential impacts of round goby invasion was largely associated with species with a conservation designation, including seven endangered species (1 fish, 6 mussels). As these recent captures of round goby represent novel occurrences in high diversity watersheds, understanding the potential impacts of secondary invasion to native biota is fundamental to prevent species declines and to allow early mitigation.

A comparison of selected global disaster risk assessment results

We compare country risk rankings derived from two recently published global disaster risk analyses. One set of country rankings is based on the Disaster Risk Index (DRI) developed by the United Nations Environment Program (UNEP) Division of Early Warning and Assessment Global Resource Information Database project under a contract to the United Nations Development Program (UNDP). The other is based on an index of disaster mortality risk developed by the Global Natural Disaster Risk Hotspots project implemented by Columbia University, the World Bank and associated partners. We convert data from these sources into two comparable indexes of disaster mortality risk and rank countries according to the resulting values for a set of natural hazards common to both studies. The country rankings are moderately correlated, ranging from .41 to .56 for individual hazards to .31 for multi-hazard mortality risks. We identify the top 25 countries according to the mortality risk values we recomputed from each study’s results to show the degree to which countries are highly ranked in common. The numbers of countries common to both lists for individual hazards range from 7 to 16 out of 25. The correspondence among the top 25 ranked countries is lowest for earthquakes and floods. Only 6 out of 25 countries are common to both lists in the multi-hazard case. We suggest that while the convergence in the results for some hazards is encouraging, more work is needed to improve data and methods, particularly with respect to assessing the role of vulnerability in the creation of risk and the calculation of multi-hazard risks.

Effect of host populations on the intensity of ticks and the prevalence of tick-borne pathogens: how to interpret the results of deer exclosure experiments

Deer are important blood hosts for feeding Ixodes ricinus ticks but they do not support transmission of many tick-borne pathogens, so acting as dead-end transmission hosts. Mathematical models show their role as tick amplifiers, but also suggest that they dilute pathogen transmission, thus reducing infection prevalence. Empirical evidence for this is conflicting: experimental plots with deer removal (i.e. deer exclosures) show that the effect depends on the size of the exclosure. Here we present simulations of dynamic models that take into account different tick stages, and several host species (e.g. rodents) that may move to and from deer exclosures; models were calibrated with respect to Ixodes ricinus ticks and tick-borne encephalitis (TBE) in Trentino (northern Italy). Results show that in small exclosures, the density of rodent-feeding ticks may be higher inside than outside, whereas in large exclosures, a reduction of such tick density may be reached. Similarly, TBE prevalence in rodents decreases in large exclosures and may be slightly higher in small exclosures than outside them. The density of infected questing nymphs inside small exclosures can be much higher, in our numerical example almost twice as large as that outside, leading to potential TBE infection risk hotspots.

Indian Ocean Dipole Modulates the Number of Extreme Rainfall Events over India in a Warming Environment

This study shows that high resolution rainfall data indicate an increase in number of extreme rainfall events over India in the last few decades. Unravelling the mechanism behind this increasing number of extreme rainfall events in central India is important as these intense rainfall events cause floods and related damage to the life and property of more than 400 million people living in this region. The natural disaster risk hotspots analysis projected the central Indian region as the most vulnerable region for floods in the Indian subcontinent. Here, we present first evidence that the extreme rainfall events in central India in recent decades are strongly modulated by cool sea surface temperature anomalies in the south-eastern equatorial Indian Ocean. The ongoing warming trend of the Indian Ocean coupled with the increase in the number of Indian Ocean Dipole years in recent decades suggests more frequent extreme rainfall events and related hazards in central India in forthcoming years.

GIS, geostatistics, metadata banking, and tree-based models for data analysis and mapping in environmental monitoring and epidemiology

By the example of environmental monitoring, some applications of geographic information systems (GIS), geostatistics, metadata banking, and Classification and Regression Trees (CART) are presented. These tools are recommended for mapping statistically estimated hot spots of vectors and pathogens. GIS were introduced as tools for spatially modelling the real world. The modelling can be done by mapping objects according to the spatial information content of data. Additionally, this can be supported by geostatistical and multivariate statistical modelling. This is demonstrated by the example of modelling marine habitats of benthic communities and of terrestrial ecoregions. Such ecoregionalisations may be used to predict phenomena based on the statistical relation between measurements of an interesting phenomenon such as, e.g., the incidence of medically relevant species and correlated characteristics of the ecoregions. The combination of meteorological data and data on plant phenology can enhance the spatial resolution of the information on climate change. To this end, meteorological and phenological data have to be correlated. To enable this, both data sets which are from disparate monitoring networks have to be spatially connected by means of geostatistical estimation. This is demonstrated by the example of transformation of site-specific data on plant phenology into surface data. The analysis allows for spatial comparison of the phenology during the two periods 1961–1990 and 1991–2002 covering whole Germany. The changes in both plant phenology and air temperature were proved to be statistically significant. Thus, they can be combined by GIS overlay technique to enhance the spatial resolution of the information on the climate change and use them for the prediction of vector incidences at the regional scale. The localisation of such risk hot spots can be done by geometrically merging surface data on promoting factors. This is demonstrated by the example of the transfer of heavy metals through soils. The predicted hot spots of heavy metal transfer can be validated empirically by measurement data which can be enquired by a metadata base linked with a geographic information system. A corresponding strategy for the detection of vector hot spots in medical epidemiology is recommended. Data on incidences and habitats of the Anophelinae in the marsh regions of Lower Saxony (Germany) were used to calculate a habitat model by CART, which together with climate data and data on ecoregions can be further used for the prediction of habitats of medically relevant vector species. In the future, this approach should be supported by an internet-based information system consisting of three components: metadata questionnaire, metadata base, and GIS to link metadata, surface data, and measurement data on incidences and habitats of medically relevant species and related data on climate, phenology, and ecoregional characteristic conditions.