Ecological Risk – Benefit Analysis of a Wetland Development Based on Risk Assessment Using "Expected Loss of Biodiversity"

Ecological risk from the development of a wetland is assessed quantitatively by means of a new risk measure, expected loss of biodiversity (ELB). ELB is defined as the weighted sum of the increments in the probabilities of extinction of the species living in the wetland due to its loss. The weighting for a particular species is calculated according to the length of the branch on the phylogenetic tree that will be lost if the species becomes extinct. The length of the branch on the phylogenetic tree is regarded as reflecting the extent of contribution of the species to the taxonomic diversity of the world of living things. The increments in the probabilities of extinction are calculated by a simulation used for making the Red List for vascular plants in Japan. The resulting ELB for the loss of Nakaikemi wetland is 9,200 years. This result is combined with the economic costs for conservation of the wetland to produce a value for the indicator of the "cost per unit of biodiversity saved." Depending on the scenario, the value is 13,000 yen per year-ELB or 110,000 to 420,000 yen per year-ELB (1 US dollar = 110 yen in 1999).     

Evaluation of Two Approaches to Defining Extinction Risk under the U.S. Endangered Species Act

The predominant definition of extinction risk in conservation biology involves evaluating the cumulative distribution function (CDF) of extinction time at a particular point (the “time horizon”). Using the principles of decision theory, this article develops an alternative definition of extinction risk as the expected loss (EL) to society resulting from eventual extinction of a species. Distinct roles are identified for time preference and risk aversion. Ranges of tentative values for the parameters of the two approaches are proposed, and the performances of the two approaches are compared and contrasted for a small set of real‐world species with published extinction time distributions and a large set of hypothetical extinction time distributions. Potential issues with each approach are evaluated, and the EL approach is recommended as the better of the two. The CDF approach suffers from the fact that extinctions that occur at any time before the specified time horizon are weighted equally, while extinctions that occur beyond the specified time horizon receive no weight at all. It also suffers from the fact that the time horizon does not correspond to any natural phenomenon, and so is impossible to specify nonarbitrarily; yet the results can depend critically on the specified value. In contrast, the EL approach has the advantage of weighting extinction time continuously, with no artificial time horizon, and the parameters of the approach (the rates of time preference and risk aversion) do correspond to natural phenomena, and so can be specified nonarbitrarily.     

Allee Effects and the Risk of Biological Invasion

The Allee effect is a nonlinear phenomenon exhibited in the population dynamics of sparse populations in which the per capita population growth rate increases with increasing population density. In sufficiently sparse populations, the Allee effect may lead to extinction and is known to generate a threshold in the probability of establishment when presented as a function of introduced population size or density. As introduced populations are generally small, Allee effects are probably common in biological invasions and their consideration is necessary for accurately assessing the risk of invasion by many species, including all sexually reproducing species. Bythotrephes longimanus, an invasive, freshwater, cladoceran zooplankter from Europe, is one such species. Here, I review a previously published model of the Allee effect for continuously sexually reproducing species. Then, I develop a new model for seasonally parthenogenetic species such as Bythotrephes, and thereby demonstrate the potential consequences of Allee effects. This result underscores the importance of considering nonlinear phenomena, including thresholds, when conducting risk analysis for biological introductions.     

Assessing the Risk of Invasive Spread in Fragmented Landscapes

Little theoretical work has investigated how landscape structure affects invasive spread, even though broad-scale disturbances caused by habitat loss and fragmentation are believed to facilitate the spread of exotic species. Neutral landscape models (NLMs), derived from percolation theory in the field of landscape ecology, provide a tool for assessing the risk of invasive spread in fragmented landscapes. A percolation-based analysis of the potential for invasive spread in fragmented landscapes predicts that invasive spread may be enormously enhanced beyond some threshold level of habitat loss, which depends upon the species' dispersal abilities and the degree of habitat fragmentation. Assuming that invasive species spread primarily through disturbed areas of the landscape, poor dispersers may spread better in landscapes in which disturbances are concentrated in space, whereas good dispersers are predicted to spread better in landscapes where disturbances are small and dispersed (i.e., fragmented landscape). Assessing the risk of invasive spread in fragmented landscapes ultimately requires understanding the relative effects of landscape structure on processes that contribute to invasive spread--dispersal (successful colonization) and demography (successful establishment). Colonization success is predicted to be highest when >20% of the landscape has been disturbed, particularly if disturbances are large or aggregated in space, because propagules are more likely to encounter sites suitable for colonization and establishment. However, landscape pattern becomes less important for predicting colonization success if species are capable of occasional long-distance dispersal events. Invasive species are also more likely to persist and achieve positive population growth rates (successful establishment) in landscapes with clumped disturbance patterns, which can then function as population sources that produce immigrants that invade other landscapes. Finally, the invasibility of communities may be greatest in landscapes with a concentrated pattern of disturbance, especially below some critical threshold of biodiversity. Below the critical biodiversity threshold, the introduction of a single species can trigger a cascade of extinctions among indigenous species. The application of NLMs may thus offer new insights and opportunities for the management and restoration of landscapes so as to slow the spread of invasive species.     

Cancer Risk Estimation of Genotoxic Chemicals Based on Target Dose and a Multiplicative Model

A mechanistic model and associated procedures are proposed for cancer risk assessment of genotoxic chemicals. As previously shown for ionizing radiation, a linear multiplicative model was found to be compatible with published experimental data for ethylene oxide, acrylamide, and butadiene. The validity of this model was anticipated in view of the multiplicative interaction of mutation with inherited and acquired growth-promoting conditions. Concurrent analysis led to rejection of an additive model (i.e. the model commonly applied for cancer risk assessment). A reanalysis of data for radiogenic cancer in mouse, dog and man shows that the relative risk coefficient is approximately the same (0.4 to 0.5 percent per rad) for tumours induced in the three species.Doses in vivo, defined as the time-integrated concentrations of ultimate mutagens, expressed in millimol × kg^–1 × h (mMh) are, like radiation doses given in Gy or rad, proportional to frequencies of potentially mutagenic events. The radiation dose equivalents of chemical doses are, calculated by multiplying chemical doses (in mMh) with the relative genotoxic potencies (in rad × mMh^–1) determined in vitro. In this way the relative cancer incidence increments in rats and mice exposed to ethylene oxide were shown to be about 0.4 percent per rad-equivalent, in agreement with the data for radiogenic cancer.Our analyses suggest that values of the relative risk coefficients for genotoxic chemicals are independent of species and that relative cancer risks determined in animal tests apply also to humans. If reliable animal test data are not available, cancer risks may be estimated by the relative potency. In both cases exposure dose/target dose relationships, the latter via macromolecule adducts, should be determined.     

Failure Probability Under Parameter Uncertainty

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location‐scale families (including the log‐normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications.     

Probability and Possibility‐Based Representations of Uncertainty in Fault Tree Analysis

Expert knowledge is an important source of input to risk analysis. In practice, experts might be reluctant to characterize their knowledge and the related (epistemic) uncertainty using precise probabilities. The theory of possibility allows for imprecision in probability assignments. The associated possibilistic representation of epistemic uncertainty can be combined with, and transformed into, a probabilistic representation; in this article, we show this with reference to a simple fault tree analysis. We apply an integrated (hybrid) probabilistic‐possibilistic computational framework for the joint propagation of the epistemic uncertainty on the values of the (limiting relative frequency) probabilities of the basic events of the fault tree, and we use possibility‐probability (probability‐possibility) transformations for propagating the epistemic uncertainty within purely probabilistic and possibilistic settings. The results of the different approaches (hybrid, probabilistic, and possibilistic) are compared with respect to the representation of uncertainty about the top event (limiting relative frequency) probability. Both the rationale underpinning the approaches and the computational efforts they require are critically examined. We conclude that the approaches relevant in a given setting depend on the purpose of the risk analysis, and that further research is required to make the possibilistic approaches operational in a risk analysis context.     

Communicating Conservation Status: How Different Statistical Assessment Criteria Affect Perceptions of Extinction Risk

Although alternative forms of statistical and verbal information are routinely used to convey species’ extinction risk to policymakers and the public, little is known about their effects on audience information processing and risk perceptions. To address this gap in literature, we report on an experiment that was designed to explore how perceptions of extinction risk differ as a function of five different assessment benchmarks (Criteria A–E) used by scientists to classify species within IUCN Red List risk levels (e.g., Critically Endangered, Vulnerable), as well as the role of key individual differences in these effects (e.g., rational and experiential thinking styles, environmental concern). Despite their normative equivalence within the IUCN classification system, results revealed divergent effects of specific assessment criteria: on average, describing extinction risk in terms of proportional population decline over time (Criterion A) and number of remaining individuals (Criterion D) evoked the highest level of perceived risk, whereas the single‐event probability of a species becoming extinct (Criterion E) engendered the least perceived risk. Furthermore, participants scoring high in rationality (analytic thinking) were less prone to exhibit these biases compared to those low in rationality. Our findings suggest that despite their equivalence in the eyes of scientific experts, IUCN criteria are indeed capable of engendering different levels of risk perception among lay audiences, effects that carry direct and important implications for those tasked with communicating about conservation status to diverse publics.     

U.S. Aviation Regulations Increase Probability of Midair Collisions

A purely stochastic Monte Carlo model is used to compare the relative midair collision course probabilities and mean closing velocities of four systems of rules for aircraft cruising altitudes as a function of altitude error: (1) current U.S. federal rules, (2) random altitudes, and (3) two proposed alternatives to the current rules. This model increments error while: (1) counting collisions among cruising pairs of aircraft following the four rules being tested on random headings between randomly placed airports, and (2) calculating mean closing velocities for each rule. The calculations verify that: (1) federal rules increase collision course probabilities by about four times more than for a chaotic system of aircraft cruising at randomly selected altitudes, (2) risk is directly proportional to the level of compliance, and (3) mean closing velocities resulting from the current rule are slightly less than for random altitudes, while being almost twice as high as for the proposed rules. High closing velocities are shown to increase the collision probability.     

Evaluating Methods for Estimating Existential Risks

Researchers and commissions contend that the risk of human extinction is high, but none of these estimates have been based upon a rigorous methodology suitable for estimating existential risks. This article evaluates several methods that could be used to estimate the probability of human extinction. Traditional methods evaluated include: simple elicitation; whole evidence Bayesian; evidential reasoning using imprecise probabilities; and Bayesian networks. Three innovative methods are also considered: influence modeling based on environmental scans; simple elicitation using extinction scenarios as anchors; and computationally intensive possible‐worlds modeling. Evaluation criteria include: level of effort required by the probability assessors; level of effort needed to implement the method; ability of each method to model the human extinction event; ability to incorporate scientific estimates of contributory events; transparency of the inputs and outputs; acceptability to the academic community (e.g., with respect to intellectual soundness, familiarity, verisimilitude); credibility and utility of the outputs of the method to the policy community; difficulty of communicating the method's processes and outputs to nonexperts; and accuracy in other contexts. The article concludes by recommending that researchers assess the risks of human extinction by combining these methods.     

A Comprehensive Model for Managing Credit Risk on Home Mortgage Portfolios*

Managing credit risk in financial institutions requires the ability to forecast aggregate losses on existing loans, predict the length of time that loans will be on the books before prepayment or default, analyze the expected performance of particular segments in the existing portfolio, and project payment patterns of new loans. Described in this paper are tools created for these functions in a large California financial institution. A forecasting model with Markovian structure and nonstationary transition probabilities is used to model the life of a mortgage. Logistic and regression models are used to estimate severity of losses. These models are integrated into a system that allows analysts and managers to depict the expected performance of individual loans and portfolio segments under different economic scenarios. With this information, analysts and managers can establish appropriate loss reserves, suggest pricing differentials to compensate for risk, and make strategic lending decisions.     

A Theory of Diversity

How can diversity be measured? What does it mean to value biodiversity? Can we assist Noah in constructing his preferences? To address these questions, we propose a multi‐attribute approach under which the diversity of a set of species is the sum of the values of all attributes possessed by some species in the set. We develop the basic intuitions and requirements for a theory of diversity and show that the multi‐attribute approach satisfies them in a flexible yet tractable manner. A natural starting point is to think of the diversity of a set as an aggregate of the pairwise dissimilarities between its elements. The multi‐attribute framework allows one to make this program formally precise. It is shown that the program can be realized if and only if the family of relevant attributes is well‐ordered (“acyclic”). Moreover, there is a unique functional form aggregating dissimilarity into diversity, the length of a minimum spanning tree. Examples are taxonomic hierarchies and lines representing uni‐dimensional qualities. In multi‐dimensional settings, pairwise dissimilarity information among elements is insufficient to determine their diversity. By consequence, the qualitative and quantitative behavior of diversity differs fundamentally.     

A Risk Assessment Method for Biological Introductions

This article describes an application of a method for assessing risks associated with the introduction of an organism into a new environment. The test organism was a binucleate Rhizoctonia fungal isolate that has potential for commercial development as a biological control agent for damping-off diseases in bedding plants. A test sample of host plant species was selected using the centrifugal phylogenetic host range principles, but with an emphasis on economic species. The effect of the fungus on the plant was measured for each species and expressed on a logarithmic scale. The effects on weights of shoots and roots per container were not normally distributed, nor were the effects on the number of plants standing (those which survived). Statements about the effect on the number standing and the shoot weight per container involved using the observed (empirical) distribution. This is illustrated with an example. Problems were encountered in defining the population of species at risk, and in deciding how this population should be formally sampled. The limitations of the method are discussed.     

Spatial Risk Assessment Across Large Landscapes with Varied Land Use: Lessons from a Conservation Assessment of Military Lands

Spatial decision-support tools are necessary for assessment and management of threats to biodiversity, which in turn is necessary for biodiversity conservation. In conjunction with the U.S. Geological Survey-Biological Resources Division's Species at Risk program, we developed a GIS-based spatial decision-support tool for relative risk assessments of threats to biodiversity on the U.S. Army's White Sands Missile Range and Fort Bliss (New Mexico and Texas) due to land uses associated with military missions of the two bases. The project tested use of spatial habitat models, land-use scenarios, and species-specific impacts to produce an assessment of relative risks for use in conservation planning on the 1.2 million-hectare study region. Our procedure allows spatially explicit analyses of risks to multiple species from multiple sources by identifying a set of hazards faced by all species of interest, identifying a set of feasible management alternatives, assigning scores to each species for each hazard, and mapping the distribution of these hazard scores across the region of interest for each combination of species/management alternatives. We illustrate the procedure with examples. We demonstrate that our risk-based approach to conservation planning can provide resource managers with a useful tool for spatial assessment of threats to species of concern.     

Knight不确定条件下的模糊二叉树期权定价模型

在市场含有Knight不确定因素的环境下,影响期权价格的因素不仅仅具有随机性的特点,而且还存在着模糊的性质.因而我们假设股票价格服从模糊随机过程,使用基于抛物型模糊数的二叉树模型对欧式期权进行定价,得到的风险中性概率及期权价格为一个赋权区间.在使用中国权证数据进行的实证中,采用二次规划方法确定模型参数,并对模糊期权价格进行去模糊化,与传统的二叉树模型进行实证比较后发现,应用模糊二叉树模型能得出更准确的市场价格预测.投资者可以选择自己可接受的置信度,得到一个模糊价格区间,以此指导投资策略.此外,应用此模型能够得到期权价格的模糊程度的度量-模糊度,从而获知Knight不确定性的大小.     

A Distributional Approach to Characterizing Low-Dose Cancer Risk

Since cancer risk at very low doses cannot be directly measured in humans or animals, mathematical extrapolation models and scientific judgment are required. This article demonstrates a probabilistic approach to carcinogen risk assessment that employs probability trees, subjective probabilities, and standard bootstrapping procedures. The probabilistic approach is applied to the carcinogenic risk of formaldehyde in environmental and occupational settings. Sensitivity analyses illustrate conditional estimates of risk for each path in the probability tree. Fundamental mechanistic uncertainties are characterized. A strength of the analysis is the explicit treatment of alternative beliefs about pharmacokinetics and pharmacodynamics. The resulting probability distributions on cancer risk are compared with the point estimates reported by federal agencies. Limitations of the approach are discussed as well as future research directions.     

Influence of Routine Slaughtering on the Evolution of BSE: Example of British and French Slaughterings

The aim of this article is to build a methodology allowing the study and the comparison of the potential spread of BSE at the scale of countries under different routine slaughtering conditions in order to evaluate the risk of nonextinction due to this slaughtering. We first model the evolution in discrete time of the proportion of animals in the latent period and that of infectives, assuming a very large branching population not necessarily constant in size, two age classes, less than 1-year-old animals, and adult animals. We analytically derive a bifurcation parameter rho(0) allowing us to predict either endemicity or extinction of the disease, which has the meaning of an epidemiological reproductive rate. We show that the classical reproductive number R(0) cannot be used for prediction if the size of the population, when healthy, does not remain stable throughout time. We illustrate the qualitative results by means of simulations with either the British routine slaughtering probabilities or the French ones, the other conditions being assumed identical in both countries. We show that the French probabilities lead to a higher risk of spread of the disease than the British ones, this result being mainly due to a smaller value of the routine slaughtering probability of the adult animals in France than in Great Britain.     

Wildfire Exposure Analysis on the National Forests in the Pacific Northwest,USA

We analyzed wildfire exposure for key social and ecological features on the national forests in Oregon and Washington. The forests contain numerous urban interfaces, old growth forests, recreational sites, and habitat for rare and endangered species. Many of these resources are threatened by wildfire, especially in the east Cascade Mountains fire‐prone forests. The study illustrates the application of wildfire simulation for risk assessment where the major threat is from large and rare naturally ignited fires, versus many previous studies that have focused on risk driven by frequent and small fires from anthropogenic ignitions. Wildfire simulation modeling was used to characterize potential wildfire behavior in terms of annual burn probability and flame length. Spatial data on selected social and ecological features were obtained from Forest Service GIS databases and elsewhere. The potential wildfire behavior was then summarized for each spatial location of each resource. The analysis suggested strong spatial variation in both burn probability and conditional flame length for many of the features examined, including biodiversity, urban interfaces, and infrastructure. We propose that the spatial patterns in modeled wildfire behavior could be used to improve existing prioritization of fuel management and wildfire preparedness activities within the Pacific Northwest region.     

基于Copula的外汇投资组合风险分析

本文简要介绍了Archimedean Copula,并运用Archimedean Copula给出了确定两种外汇最小风险(VaR)投资组合的方法。并用这个方法,对欧元和日元的投资组合做了相应的风险分析,得到了二者的最小风险投资组合,并对不同置信水平下VaR和组合系数做了敏感性分析。