Suchergebnisse

Detecting Extinction in Sighting Data -- Inferring Threat from Scientific Collections: Power Tests and an Application to Western Australian Acacia Species -- Identifying the Ecological Correlates of Extinction-Prone Species: A Case Study of New Zealand Birds -- Quantitative Methods for Modeling Species Habitat: Comparative Performance and an Application to Australian Plants -- Risk Assessment of a Proposed Introduction of Pacific Salmon in the Delaware River Basin -- Likelihood of Introducing Nonindigenous Organisms with Agricultural Commodities: Probabilistic Estimation -- "Best" Abundance Estimates and Best Management: Why They Are Not the Same -- Whaling Models for Cetacean Conservation -- Assessing Land-Use Impacts on Bull Trout Using Bayesian Belief Networks -- Using Matrix Models to Focus Research and Management Efforts in Conservation -- Variability and Measurement Error in Extinction Risk Analysis: The Northern Spotted Owl on the Olympic Peninsula -- Can Individual-Based Models Yield a Better Assessment of Population Variability? -- Potential of Branching Processes as a Modeling Tool for Conservation Biology -- Role of Genetics in Conservation Biology -- Modeling Problems in Conservation Genetics Using Laboratory Animals Richard Frankham -- Theoretical Properties of Extinction by Inbreeding Depression Under Stochastic Environments -- Mathematical Methods for Identifying Representative Reserve Networks.

An examination of the findings of the Second Circuit Court case of Shonubi IV challenges the claim that it represents a general rejection of statistical evidence in law. The 1991 case involved a Nigerian resident of the US accused of importing heroin by swallowing it in a sealed balloon. There was overwhelming evidence of Shonubi's guilt & a finding that he had made a total of eight such trips. The appeal did not contest his conviction but focused on the judge's interpretation of federal guidelines that indicated the sentence should depend on the quantity of heroin involved. Shonubi's sentence was based on the total amount of heroin smuggled in all eight episodes. The amount was determined by statistical estimates since physical evidence from the first seven incidents was unavailable. The case's progress through three successive appeals shows that the final decision to vacate the sentence was fair because of the dubious nature of the statistical evidence based on quantities other balloon smugglers had carried, rather than on what Shonubi himself smuggled. 24 References. J. Lindroth

Uncertainty analyses typically recognize separate stochastic and subjective sources of uncertainty, but do not systematically combine the two, although a large amount of data used in analyses is partly stochastic and partly subjective. We have developed methodology for mathematically combining stochastic and subjective sources of data uncertainty, based on new "hybrid number" approaches. The methodology can be utilized in conjunction with various traditional techniques, such as PRA (probabilistic risk assessment) and risk analysis decision support. Hybrid numbers have been previously examined as a potential method to represent combinations of stochastic and subjective information, but mathematical processing has been impeded by the requirements inherent in the structure of the numbers, e.g., there was no known way to multiply hybrids. In this paper, we will demonstrate methods for calculating with hybrid numbers that avoid the difficulties. By formulating a hybrid number as a probability distribution that is only fuzzily known, or alternatively as a random distribution of fuzzy numbers, methods are demonstrated for the full suite of arithmetic operations, permitting complex mathematical calculations. It will be shown how information about relative subjectivity (the ratio of subjective to stochastic knowledge about a particular datum) can be incorporated. Techniques are also developed for conveying uncertainty information visually, so that the stochastic and subjective components of the uncertainty, as well as the ratio of knowledge about the two, are readily apparent. The techniques demonstrated have the capability to process uncertainty information for independent, uncorrelated data, and for some types of dependent and correlated data. Example applications are suggested, illustrative problems are shown, and graphical results are given.

Toxic chemicals can exert effects on all levels of the biological hierarchy, from cells to organs to organisms to populations to entire ecosystems. However, most risk assessment models express their results in terms of effects on individual organisms, without corresponding information on how populations, groups of species, or whole ecosystems may respond to chemical stressors. Ecological Modeling in Risk Assessment: Chemical Effects on Populations, Ecosystems, and Landscapes takes a new approach by compiling and evaluating models that can be used in assessing risk at the population, ecosystem

Although the parameters for contaminant bioaccumulation models most likely vary over time, lack of data makes it impossible to quantify this variability. As a consequence, Monte Carlo models of contaminant bioaccumulation often treat all parameters as having fixed true values that are unknown. This can lead to biased distributions of predicted contaminant concentrations. This article demonstrates this phenomenon with a case study of selenium accumulation in the mussel Mytilus edulis in San Francisco Bay. "Ignorance‐only" simulations (in which phytoplankton and bioavailable selenium concentrations are constant over time, but sampled from distributions of field measurements taken at different times), which an analyst might be forced to use due to lack of data, were compared with "variability and ignorance" simulations (sampling phytoplankton and bioavailable selenium concentrations each month). It was found that ignorance‐only simulations may underestimate or overestimate the median predicted contaminant concentration at any time, relative to variability and ignorance simulations. However, over a long enough time period (such as the complete seasonal cycle in a seasonal model), treating temporal variability as if it were ignorance at least gave a range of predicted concentrations that enclosed the range predicted by explicit treatment of temporal variability. Comparing the temporal variability in field data with that predicted by simulations may indicate whether the right amount of temporal variability is being included in input variables. Sensitivity analysis combined with biological knowledge suggests which parameters might make important contributions to temporal variability. Temporal variability is potentially more complicated to deal with than other types of stochastic variability, because of the range of time scales over which parameters may vary.

Strategies for risk communication : evolution, evidence, experience / W. Troy Tucker and Scott Ferson -- Numeracy and the perception and communication of risk / Ellen Peters -- Evolution, risk, and neural representation / Karli K. Watson -- Linguistic uncertainty in qualitative risk analysis and how to minimize it / Janet M. Carey and Mark A. Burgman -- Transparency in risk communication : graphical and analog tools / Elke Kurz-Milcke, Gerd Gigerenzer, and Laura Martignon -- Visualizing seismic risk and uncertainty : a review of related research / Ann Bostrom, Luc Anselin, and Jeremy Farris -- The neuronal substrate of risky choice : an insight into the contributions of neuroimaging to the understanding of theories on decision making under risk / Verena Vorhold -- Multiple systems in decision making / Alan G. Sanfey and Luke J. Chang -- A frequency/consequence-based technique for visualizing and communicating uncertainty and perception of risk / David Slavin, W. Troy Tucker, and Scott Ferson -- Risk communication and risky choice in context : ambiguity and ambivalence hypothesis / Xiao-Tian Wang -- Models and methods in delay discounting / Aaron D. Tesch and Alan G. Sanfey -- Science, precaution, and the politics of technological risk : converging implications in evolutionary and social scientific perspectives / Andy Stirling -- Evolved altruism, strong reciprocity, and perception of risk / W. Troy Tucker and Scott Ferson -- Perceiving others' perceptions of risk : still a task for Sisyphus / Adam M. Finkel

Testing is viewed as a critical aspect of any strategy to tackle epidemics. Much of the dialogue around testing has concentrated on how countries can scale up capacity, but the uncertainty in testing has not received nearly as much attention beyond asking if a test is accurate enough to be used. Even for highly accurate tests, false positives and false negatives will accumulate as mass testing strategies are employed under pressure, and these misdiagnoses could have major implications on the ability of governments to suppress the virus. The present analysis uses a modified SIR model to understand the implication and magnitude of misdiagnosis in the context of ending lockdown measures. The results indicate that increased testing capacity alone will not provide a solution to lockdown measures. The progression of the epidemic and peak infections is shown to depend heavily on test characteristics, test targeting, and prevalence of the infection. Antibody based immunity passports are rejected as a solution to ending lockdown, as they can put the population at risk if poorly targeted. Similarly, mass screening for active viral infection may only be beneficial if it can be sufficiently well targeted, otherwise reliance on this approach for protection of the population can again put them at risk. A well targeted active viral test combined with a slow release rate is a viable strategy for continuous suppression of the virus.