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The biodiversity, ecosystem services and climate variability of the Antarctic continent and the Southern Ocean are major components of the whole Earth system. Antarctic ecosystems are driven more strongly by the physical environment than many other marine and terrestrial ecosystems. As a consequence, to understand ecological functioning, cross-disciplinary studies are especially important in Antarctic research. The conceptual study presented here is based on a workshop initiated by the Research Programme Antarctic Thresholds – Ecosystem Resilience and Adaptation of the Scientific Committee on Antarctic Research, which focussed on challenges in identifying and applying cross-disciplinary approaches in the Antarctic. Novel ideas and first steps in their implementation were clustered into eight themes. These ranged from scale problems, through risk maps, and organism/ecosystem responses to multiple environmental changes and evolutionary processes. Scaling models and data across different spatial and temporal scales were identified as an overarching challenge. Approaches to bridge gaps in Antarctic research programmes included multi-disciplinary monitoring, linking biomolecular findings and simulated physical environments, as well as integrative ecological modelling. The results of advanced cross-disciplinary approaches can contribute significantly to our knowledge of Antarctic and global ecosystem functioning, the consequences of climate change, and to global assessments that ultimately benefit humankind. [ABSTRACT FROM AUTHOR]

A probabilistic methodology to generate “risk maps” for determining the spatial extent and associated probability of groundwater leakage risk at Geologic Carbon Storage (GCS) sites was recently developed and is tested for well permeability distribution sensitivity here. Although the risk map methodology is general and may be used to assess leakage of either CO 2 or brine, the degree to which risk may occur via plugged and abandoned (P&A) brine leakage is arguably the most uncertain. This uncertainty stems from the possibility of a high number of undocumented wells at a given injection site which, even when properly plugged, may yield a number of different leakage pathways. Furthermore, determining the spatial extent and probability of brine leakage through P&A wells is not straightforward. The aforementioned risk maps are probabilistic and are based on the premise that two of the greatest sources of uncertainty in brine leakage through P&A wells are the location of the unknown well with respect to the injection well and the permeability of the leaky well (which can span over several orders of magnitude). The methodology utilizes either analytical solutions or numerical simulations in conjunction with probability theory to generate spatial distributions of risk. Risk is defined with either no-impact levels (i.e. zero brine concentration above background in the drinking water aquifer) or other user defined thresholds such as the secondary maximum contaminant level (SMCL) for total dissolved solids, a non-health related standard related to water hardness, color, and taste. These probabilistic maps can be used to provide risk-based descriptions of the injection area to inform site selection prior to injection and monitoring during or after injection has ceased, similar to the United States Environmental Protection Agency's definition of the area of review (AoR). However, unlike the AoR definition, we differentiate risks according to a tiered approach, where CO 2 leakage risk and brine leakage risk through P&A wells and open wellbores are assessed separately given that not only do the risks differ considerably, the spatial extents of each hazard do as well. A strength of this methodology is its demonstrated efficiency, which unlike computationally expensive Monte Carlo techniques that could require several thousands of simulations, requires only on the order of tens of simulations. Here, we assess the sensitivity of risk maps of a hypothetical, yet realistic GCS leakage scenario. In this sensitivity analysis, risk maps are generated with varying leaky well permeability distributions including differences in distribution modality and distribution variance. This work is motivated by the unknown quality to which many wells are sealed and/or the degree to which they degrade over time, in addition to the sheer unknown quantity of which P&A wells may be present at a single Geologic Carbon Storage site. Quantitative probabilities of exceeding contamination thresholds in the USDW are used for discussion, a practical metric for decision-makers and stakeholders. Results show that the modality of the leaky P&A distribution plays an important role in the risk profile and that larger variances in leaky P&A well permeability distribution may result in an overall lower profile of risk, depending on the upper-threshold of the distribution. [ABSTRACT FROM AUTHOR]

The risks to potable aquifers due to brine leakage through plugged and abandoned (P&A) wells is highly uncertain and a potentially significant contributor to the risk profile in Geologic Carbon Storage (GCS). This uncertainty stems from the unknown location of wells and the large variance of P&A wellbore permeability, making the spatial assessment of P&A brine leakage risk challenging. A new methodology is presented to generate “risk maps”, or spatial distributions of brine leakage risk to groundwater resources as defined with no-impact or Maximum Contaminant Level (MCL) thresholds. The methodology utilizes probability theory, thereby avoiding the use of computationally expensive Monte Carlo simulations while maintaining flexibility in modeling techniques. These maps provide quantitative probabilities of risk as a function of time to inform site selection and monitoring during and post-injection, conducive to the US EPA’s permitting of class-VI wells and the so-called “area of review”, AoR. As a demonstration of the methodology, a numerical model of a hypothetical fully-coupled system spanning from the injection reservoir to the USDW is used to assess the evolution of brine leakage through P&A wells. Risk maps of CO 2 leakage can also be generated with this methodology for a comprehensive assessment of GCS leakage risk. [ABSTRACT FROM AUTHOR]

Lyme disease (LD) risk is emerging rapidly in Canada due to range expansion of its tick vectors, accelerated by climate change. The risk of contracting LD varies geographically due to variability in ecological characteristics that determine the hazard (the densities of infected host-seeking ticks) and vulnerability of the human population determined by their knowledge and adoption of preventive behaviors. Risk maps are commonly used to support public health decision-making on Lyme disease, but the ability of the human public to adopt preventive behaviors is rarely taken into account in their development, which represents a critical gap. The objective of this work was to improve LD risk mapping using an integrated social-behavioral and ecological approach to: (i) compute enhanced integrated risk maps for prioritization of interventions and (ii) develop a spatially-explicit assessment tool to examine the relative contribution of different risk factors. The study was carried out in the Estrie region located in southern Québec. The blacklegged tick, Ixodes scapularis , infected with the agent of LD is widespread in Estrie and as a result, regional LD incidence is the highest in the province. LD knowledge and behaviors in the population were measured in a cross-sectional health survey conducted in 2018 reaching 10,790 respondents in Estrie. These data were used to create an index for the social-behavioral component of risk in 2018. Local Empirical Bayes estimator technique were used to better quantify the spatial variance in the levels of adoption of LD preventive activities. For the ecological risk analysis, a tick abundance model was developed by integrating data from ongoing long-term tick surveillance programs from 2007 up to 2018. Social-behavioral and ecological components of the risk measures were combined to create vulnerability index maps and, with the addition of human population densities, prioritization index maps. Map predictions were validated by testing the association of high-risk areas with the current spatial distribution of human cases of LD and reported tick exposure. Our results demonstrated that social-behavioral and ecological components of LD risk have markedly different distributions within Estrie. The occurrence of human LD cases or reported tick exposure in a municipality was positively associated with tick density and the prioritization risk index (p < 0.001). This research is a second step towards a more comprehensive integrated LD risk assessment approach, examining social-behavioral risk factors that interact with ecological risk factors to influence the management of emerging tick-borne diseases, an approach that could be applied more widely to vector-borne and zoonotic diseases. [ABSTRACT FROM AUTHOR]

A method to integrate the environmental risk of the multiple effects from uses and activities developed in harbor areas is presented. Consequences are considered as the effects derived from all identified hazards. Vulnerability is expressed in terms of functional relations between environmental susceptibility against a disturbance and the state of protection of the receptors at risk. Consequences and vulnerability are integrated obtaining a spatial variation of risk: prioritization maps. The maps are developed by 4 main stages: (1) environmental hazard identification; (2) estimation of the consequences; (3) estimation of vulnerability and, (4) integration of environmental risks. To adapt prioritization maps to the peculiarities of the study area, three different methods for the integration of the effects are proposed: average-value, worst-case and weighted methods. The implementation to a real case (Tarragona harbor, NE Spain) confirms its usefulness as a risk analysis tool to communicate and support water quality management in harbors. [ABSTRACT FROM AUTHOR]

Sophisticated geospatial modeling of environmental problems and hazards is far advanced in geography, decision science, and related fields. The political ecological application of these tools, especially in visualizing, debating, and contesting risk, is underdeveloped, however. By using visualizations of risk as an analytical tool to explore the views of citizens and county health officials, geospatial models can help to explore the schisms, connections, and associations among complex landscapes, diverse publics, and logics of governance. In this paper, we explore the case of West Nile virus in the Southwest United States, a site where county health departments, vector control districts, and urban residents practice varying methods of mosquito management. We created geospatial visualizations of mosquito microhabitat using a dynamic simulation model and remotely sensed imagery. These data, when differentially aggregated, produced divergent visualizations of mosquito risk spaces across the city of Tucson. Presenting maps to neighborhood residents and local health officials, we found they invited different understandings of spatialized areas of responsibility for mosquito management. Neighborhood focus groups expressed territorial notions of risk and responsibility that diverged widely from those of health officials. Visualizations were shown to both reflect and produce different mosquito narratives, showing how mapped models can help elicit political–ecological insight into the territorialization of mosquito control. [ABSTRACT FROM AUTHOR]

One effect of passing through the world financial crisis is to pay closer attention to compliance with the regulations of business by banks and other financial institutions. In recent times there has also been an increase in the importance of compliance units involved in the management of compliance risk in the bank. The author in the paper highlights the need to risk monitoring of non-compliance with the regulations and presents some monitoring tools of this kind of risk in the bank. Examples of tools and techniques presented in the paper relate to banks operating in Poland. These are mainly methods based on using indicators, supported by information technology tools for business process management. The scope of compliance evolved last years to a much broader area. The author of the paper draws attention to the growing popularity of the approach integrating operational and compliance risk [ABSTRACT FROM AUTHOR]

Accelerating climate change and other cumulative stressors create an urgent need to understand the influence of environmental variation and landscape features on the connectivity and vulnerability of freshwater species. Here, we introduce a novel modeling framework for aquatic systems that integrates spatially explicit, individual-based, demographic and genetic (demogenetic) assessments with environmental variables. To show its potential utility, we simulated a hypothetical network of 19 migratory riverine populations (e.g., salmonids) using a riverscape connectivity and demogenetic model (CDFISH). We assessed how stream resistance to movement (a function of water temperature, fluvial distance, and physical barriers) might influence demogenetic connectivity, and hence, population vulnerability. We present demographic metrics (abundance, immigration, and change in abundance) and genetic metrics (diversity, differentiation, and change in differentiation), and combine them into a single vulnerability index for identifying populations at risk of extirpation. We considered four realistic scenarios that illustrate the relative sensitivity of these metrics for early detection of reduced connectivity: (1) maximum resistance due to high water temperatures throughout the network, (2) minimum resistance due to low water temperatures throughout the network, (3) increased resistance at a tributary junction caused by a partial barrier, and (4) complete isolation of a tributary, leaving resident individuals only. We then applied this demogenetic framework using empirical data for a bull trout (Salvelinus confluentus) metapopulation in the upper Flathead River system, Canada and USA, to assess how current and predicted future stream warming may influence population vulnerability. Results suggest that warmer water temperatures and associated barriers to movement (e.g., low flows, dewatering) are predicted to fragment suitable habitat for migratory salmonids, resulting in the loss of genetic diversity and reduced numbers in certain vulnerable populations. This demogenetic simulation framework, which is illustrated in a web-based interactive mapping prototype, should be useful for evaluating population vulnerability in a wide variety of dendritic and fragmented riverscapes, helping to guide conservation and management efforts for freshwater species. [ABSTRACT FROM AUTHOR]

Abstract: Geographical maps indicating the value of the basic reproduction number, R 0, can be used to identify areas of higher risk for an outbreak after an introduction. We develop a methodology to create R 0 maps for vector-borne diseases, using bluetongue virus as a case study. This method provides a tool for gauging the extent of environmental effects on disease emergence. The method involves integrating vector-abundance data with statistical approaches to predict abundance from satellite imagery and with the biologically mechanistic modelling that underlies R 0. We illustrate the method with three applications for bluetongue virus in the Netherlands: 1) a simple R 0 map for the situation in September 2006, 2) species-specific R 0 maps based on satellite-data derived predictions, and 3) monthly R 0 maps throughout the year. These applications ought to be considered as a proof-of-principle and illustrations of the methods described, rather than as ready-to-use risk maps. Altogether, this is a first step towards an integrative method to predict risk of establishment of diseases based on mathematical modelling combined with a geographic information system that may comprise climatic variables, landscape features, land use, and other relevant factors determining the risk of establishment for bluetongue as well as of other emerging vector-borne diseases. [Copyright &y& Elsevier]

Abstract: This brief review focuses on the value of predictive risk mapping and the question of how to test predictions of the spatial and temporal variation in risk of tick-borne diseases, specifically as caused by tick-borne encephalitis virus (TBEv). Predictions of the present distribution of TBEv, driven by satellite data, match the mapped records of TBE cases with 90% accuracy in the Baltic region and 81% accuracy in central Europe. Many of the apparently false predictions of TBE presence coincide with recent records of new or reactivated foci, and highlight regions for active surveillance. Predictions of the changes in TBEv distribution under the influence of climate change suggest that TBEv may be driven into increasingly high latitude and high altitude regions, until by the 2080s it is confined to parts of Scandinavia. This is consistent with the fact that enzootic TBEv cycles are inherently fragile and depend for their existence on specific seasonal temperature profiles and moisture conditions, which may be disrupted by climate change. Changes in the incidence of TBE in many countries since the 1990s are also consistent with these predictions, although there is evidence that local non-biological factors also play an important role in determining the incidence of disease. [Copyright &y& Elsevier]