Evaluating Critical Uncertainty Thresholds in a Spatial Model of Forest Pest Invasion Risk

Pest risk maps can provide useful decision support in invasive species management, but most do not adequately consider the uncertainty associated with predicted risk values. This study explores how increased uncertainty in a risk model's numeric assumptions might affect the resultant risk map. We used a spatial stochastic model, integrating components for entry, establishment, and spread, to estimate the risks of invasion and their variation across a two-dimensional landscape for Sirex noctilio , a nonnative woodwasp recently detected in the United States and Canada. Here, we present a sensitivity analysis of the mapped risk estimates to variation in key model parameters. The tested parameter values were sampled from symmetric uniform distributions defined by a series of nested bounds (±5%, … , ±40%) around the parameters' initial values. The results suggest that the maximum annual spread distance, which governs long-distance dispersal, was by far the most sensitive parameter. At ±15% or larger variability bound increments for this parameter, there were noteworthy shifts in map risk values, but no other parameter had a major effect, even at wider bounds of variation. The methodology presented here is generic and can be used to assess the impact of uncertainties on the stability of pest risk maps as well as to identify geographic areas for which management decisions can be made confidently, regardless of uncertainty.     

Probabilistic Analysis of the Inadvertent Reentry of the Cassini Spacecraft''s Radioisotope Thermoelectric Generators

As part of the launch approval process, the Interagency Nuclear Safety Review Panel provides an independent safety assessment of space missions--such as the Cassini mission--that carry a significant amount of nuclear materials. This survey article describes potential accident scenarios that might lead to release of fuel from an accidental reentry during an Earth swingby maneuver, the probabilities of such scenarios, and their consequences. To illustrate the nature of calculations used in this area, examples are presented of probabilistic models to obtain both the probability of scenario events and the resultant source terms of such scenarios. Because of large extrapolations from the current knowledge base, the analysis emphasizes treatment of uncertainties.     

Editorial

This issue begins with an article focused on Canada rural communities.Recent literature has placed considerable emphasis on the importanceof building and mobilizing neighbourhood or community socialcapital. There is less written about how social capital canbe concretized in situations of community conflict. The articleby Ann Dale and Jennie Sparkes reports on some qualitative researchconducted into a campaign led by a Canadian community rich inhuman and social capital against a multi-national corporation.They highlight the important role in the campaign played by'critical node individuals' operating within an open diversenetwork system and able to make and sustain connections strongenough to engage in a unified campaign. The authors suggestthat certain network structures are more likely to facilitate     

Delayed Parental Divorce: How Much Do Children Benefit?

This study compares children who experienced divorce in childhood with those who were young adults when their parents divorced to differentiate between long‐term effects of divorce resulting from preexisting factors, including the child's behavioral problems and psychological status as well as the family's economic circumstances, and those resulting from divorce itself. We used National Child Development Study data on 11,409 British children born in 1958 and followed up until age 33. Children's long‐term welfare appears to be linked both to conditions preceding and following the divorce event. The results point to some limitations of existing studies on divorce and suggest caution in drawing conclusions about average effects of divorce. The impact of divorce appears to be a complex blend of selection and socialization.     

The Discourse of Dress and Appearance: Identity Talk and a Rhetoric of Review

This article examines how identities are constructed and maintained via talk about personal dress and appearance. In this article, we introduce the concept of rhetoric of review, which is defined as the taken-for-granted rules that guide the evaluations of the appearances of self and others. Three basic components of a rhetoric of review are identified: moral precepts, program neutralizations, and review neutralizations. Data were derived from eight in-depth interviews with eighteen sorority members from a single university in the Southeastern United States. These data were used to expand Stone's (1962) conceptual framework of program and review by including Sykes and Matza's (1957) neutralization techniques. The purpose of this article is to bridge the interactionist perspectives on appearance and identity talk so as to augment our understanding of the discourse of appearance.     

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (i.e. directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error rule was more likely to choose the correct model than were the other tree-selection rules. The minimum-risk-complexity rule was more likely to choose the correct model than were the other tree-selection rules (1) with weaker relationships and equally important explanatory variables; and (2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.