A Bayesian assessment of the effect of highway bypasses in Iowa on crashes and crash rate

Introduction

A common contention is that the construction of highway bypasses negatively impacts the economy of local communities by reducing pass-by traffic for businesses. However, as access to specific business' account records is limited, this impact is difficult to quantify. Another common contention is that bypasses contribute to a reduction in overall crashes in the community and in the surrounding areas. Even though a large number of bypasses have been constructed in the State of Iowa over the past several years, their actual impact in terms of traffic safety has not been quantified.

Objectives

This study seeks answers to the following questions: (a) Are bypasses in Iowa associated with a reduction in crash frequencies and crash rates on the bypassed highway? (b) Do bypasses in Iowa introduce a reduction of overall crash frequencies and rates or do they merely shift crashes from the highways through the communities to the bypasses with no significant overall reduction?

Method

We obtained crash information from the Iowa DOT at 19 sites on which a bypass was constructed sometime during the past 23 years. We also obtained the same information at six sites used as comparison sites on which no bypasses were constructed at least until 2005. We them employed a Bayesian approach to estimating the association between the construction of the bypass and crash rates, while also accounting for other factors.

Results

The construction of bypasses in Iowa is associated with a significant increase in traffic safety both on the main road through town and on the combined main road and bypass roadway.     

A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife.     

Estimating species occurrence, abundance, and detection probability using zero-inflated distributions

Researchers have developed methods to account for imperfect detection of species with either occupancy (presence absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.     

Conservation planning for successional landscapes

The systematic conservation planning literature invariably assumes that the biodiversity features being preserved in sites do not change through time. We develop a conservation planning framework for ecosystems where disturbance events and succession drive vegetation dynamics. The framework incorporates three key attributes of disturbance theory: heterogeneity in disturbance rates, spatial correlation between disturbance events and different impacts of disturbance. In our conservation problem we wish to maximise the chance that we represent a certain number of successional types given a cap on the number of sites we can conserve. Correlation between disturbance events dramatically complicates the problem of choosing the optimal suite of sites. However, in our problem we discover that spatial correlation in disturbances affects the optimal reserve network very little. The reason is twofold: (i) through our probabilistic framework we focus on the long-term effectiveness of reserve networks and (ii) in the dynamics considered in our model the state of a site is not only affected by the most recent (correlated) disturbance event but also by the site's long-term stochastic history which blurs the impact of spatial correlation. If successional states are the conservation target rather than individual species then, conserving a site can only contribute to meeting one target. However, given that correlation of disturbance events may be ignored, we show that if the number of candidate reserves is sufficiently large the statistical dependence of different conservation targets may be ignored, too. We conclude that the computational complexity of reserve selection methods for dynamic ecosystems can be much simpler than they first appear.     

Assessment of GM Crops in Commercial Agriculture

The caliber of recent discourse regarding geneticallymodified organisms (GMOs) has suffered from a lack of consensuson terminology, from the scarcity of evidence upon which toassess risk to health and to the environment, and from valuedifferences between proponents and opponents of GMOs. Towardsaddressing these issues, we present the thesis that GM should bedefined as the forcible insertion of DNA into a host genome,irrespective of the source of the DNA, and exclusive ofconventional or mutation breeding.Some defenders of the commercial use of GMOs have referred to thescientific work of GMO critics as ``junk science.' Such a claim isfalse and misleading, given that many papers critical of both theutility and safety of GMOs have been published in peer reviewedjournals by respected scientists. In contrast, there is a dearthof peer reviewed work to substantiate the frequently heardassertions of either safety or utility in GMOs. The polarity,which now characterizes much of the public discourse on GMOs,reflects not simply scientific disagreement, but alsodisagreement in underlying value assumptions. Value differencesstrongly affect the assessment of both benefit and harm fromGMOs.The concept of substantial equivalence occupies a pivotalposition in the GMO risk assessment process that is used in bothCanada and the US. A GMO judged to be substantially equivalent toa conventional product – as have all submissions to date – ispresumed to be safe enough for commercialization. The conclusionof safety – from both human health and environmental perspectives– should be based on scientific evidence, corroborated by actualexperimentation. However, regulators infer safety largely fromassumptions-based reasoning, with little or no experimentalvalidation. The judgement of safety because of substantialequivalence is a dubious argument by analogy.     

Improving the risk–risk trade-off method for use in safety project appraisal responses

Environmental Economics and Policy Studies - The risk–risk trade-off method is a technique used to elicit the relative trade-off between changes in morbidity and mortality risks in stated...     

Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness

Estimating the effectiveness of protected areas (PAs) in reducing deforestation is useful to support decisions on whether to invest in better management of areas already protected or to create new ones. Statistical matching is commonly used to assess this effectiveness, but spatial autocorrelation and regional differences in protection effectiveness are frequently overlooked. Using Colombia as a case study, we employed statistical matching to account for confounding factors in park location and accounted for for spatial autocorrelation to determine statistical significance. We compared the performance of different matching procedures—ways of generating matching pairs at different scales—in estimating PA effectiveness. Differences in matching procedures affected covariate similarity between matched pairs (balance) and estimates of PA effectiveness in reducing deforestation. Independent matching yielded the greatest balance. On average 95% of variables in each region were balanced with independent matching, whereas 33% of variables were balanced when using the method that performed worst. The best estimates suggested that average deforestation inside protected areas in Colombia was 40% lower than in matched sites. Protection significantly reduced deforestation, but PA effectiveness differed among regions. Protected areas in Caribe were the most effective, whereas those in Orinoco and Pacific were least effective. Our results demonstrate that accounting for spatial autocorrelation and using independent matching for each subset of data is needed to infer the effectiveness of protection in reducing deforestation. Not accounting for spatial autocorrelation can distort the assessment of protection effectiveness, increasing type I and II errors and inflating effect size. Our method allowed improved estimates of protection effectiveness across scales and under different conditions and can be applied to other regions to effectively assess PA performance.     

Genetics of growth in blue mussels: family and enzyme-heterozygosity effects

Shell length and electrophoretic heterozygosity at six enzyme loci were scored in juveniles of 30 hatchery-grown families and in adults of 10 field-grown families of the blue mussel Mytilus edulis. A total of 4 809 offspring were scored. We found no consistent pattern in the correlations between shell length and enzyme heterozygosity among sibs within families. However, a significant family effect on shell length was observed, suggesting an influence of background genotype on this character. A family effect on viability was also observed. When the environment and family effects were accounted for, a small positive correlation between heterozygosity and shell length at the juvenile stage remained. This correlation was significant in one of the three experiments. No such correlation was evident at the adult stage. Our interpretation of these results is that electrophoretic alleles appear to have no direct of independent effect of their own on growth. We suggest that the negative correlation of homozygosity with these characters, seen in natural populations, results from homozygosity for hidden recessive deleterious genes with which the electromorphs are in a steady state of quasilinkage disequilibrium.