Mold spore penetration through wall service outlets: a pilot study

A pilot study was conducted to estimate fungal spore penetration for wall service outlets subjected to a constant air pressure. During the laboratory experiment, a wall chamber was fabricated, and telephone, electrical, and cable service outlets were installed. Penicillium chrysogenum spores were aerosolized into the chamber that was held under pressure. Spores that penetrated the outlets were funneled into an impinger for microscopic enumeration. Thirty trials were conducted for each of the five outlets (N?= 150), and the wall chamber was decontaminated between trials. Results of an analysis of variance suggest wall service outlets allow spore penetration. The penetration factor for the telephone outlet was significantly greater than all other outlets (p?< 0.05), and there was no difference in penetration between electrical outlets with and without plugs. Penetration factor differences were attributed to air leakage rates across the outlets. Due to the experimental design and equipment limitations, further research is needed to support these findings.     

Emergency room evidence on the role of alcohol intoxication in injury at work in the U.S.

Alcohol is a known risk factor for many kinds of injuries, but past research has failed to implicate alcohol intoxication as a major cause of work injuries in the U.S. Local and regional studies have indicated that alcohol-related injuries are relatively less common in work settings than non-work settings. In a six-month study, the National Electronic Injury Surveillance System collected the first national sample data on alcohol and injuries presenting to hospital emergency rooms. The study included both work injuries and product-related non-work injuries. Alcohol intoxication was ascertained by emergency room chart review. Alcohol involvement was much lower than in other studies, probably because of poor sensitivity in ascertainment, and it was 10 times lower among work injuries than non-work injuries. “Non-work activities at the time of injury” were a significant risk factor for alcohol-related injuries (odds ratio = 7). Thus, results of this national study are consistent with previous research in finding that alcohol poses a greater risk for nonwork injury than for work injury.     

Obtaining species: sample size considerations

Suppose fish are to be sampled from a stream. A fisheries biologist might ask one of the following three questions: ‘How many fish do I need to catch in order to see all of the species?’, ‘How many fish do I need to catch in order to see all species whose relative frequency is more than 5%?’, or ‘How many fish do I need to catch in order to see a member from each of the species A, B, and C?’. This paper offers a practical solution to such questions by setting a target sample size designed to achieve desired results with known probability. We present three sample size methods, one we call ‘exact’ and the others approximate. Each method is derived under assumed multinomial sampling, and requires (at least approximate) independence of draws and (usually) a large population. The minimum information needed to compute one of the approximate methods is the estimated relative frequency of the rarest species of interest. Total number of species is not needed. Choice of a sample size method depends largely on available computer resources. One approximation (called the ‘Monte Carlo approximation’) gets within ±6 units of exact sample size, but usually requires 20–30 minutes of computer time to compute. The second approximation (called the ‘ratio approximation’) can be computed manually and has relative error under 5% when all species are desired, but can be as much as 50% or more too high when exact sample size is small. Statistically, this problem is an application of the ‘sequential occupancy problem’. Three examples are given which illustrate the calculations so that a reader not interested in technical details can apply our results.     

Halton iterative partitioning: spatially balanced sampling via partitioning

A new spatially balanced sampling design for environmental surveys is introduced, called Halton iterative partitioning (HIP). The design draws sample locations that are well spread over the study area. Spatially balanced designs are known to be efficient when surveying natural resources because nearby locations tend to be similar. The HIP design uses structural properties of the Halton sequence to partition a resource into nested boxes. Sample locations are then drawn from specific boxes in the partition to ensure spatial diversity. The method is conceptually simple and computationally efficient, draws spatially balanced samples in two or more dimensions and uses standard design-based estimators. Furthermore, HIP samples have an implicit ordering that can be used to define spatially balanced over-samples. This feature is particularly useful when sampling natural resources because we can dynamically add spatially balanced units from the over-sample to the sample as non-target or inaccessible units are discovered. We use several populations to show that HIP sampling draws spatially balanced samples and gives precise estimates of population totals.     

Bridging information domains to improve ecological understanding of biological invasions in a marine ecosystem

We devised a practical method for integrating information on 2 marine invasive species using 3 different approaches: standardized ecological monitoring, online-reporting databases, and surveys of anglers and crabbers. Focusing on 2 recently introduced species with different characteristics, the Asian shore crab (Hemigrapsus sanguineus) and Chinese mitten crab (Eriocheir sinensis), in the Hudson-Raritan watershed of New York and New Jersey, we used sensitivity analyses to explore the relative contribution of each information source to knowledge of species abundance and distribution. All 3 information sources contributed something unique to understanding abundance and distribution of the introduced crabs. Online and survey data on Asian shore crabs significantly affected predictions of abundance, whereas monitoring data did not. When survey data were omitted, abundance estimates were unchanged over time, but when they were included, the model predicted an increased abundance in 2012. All 3 data sets for the Asian shore crab significantly affected estimates of species coverage; surveys had the biggest influence, increasing range size by 4097.25 km². For the catadromous Chinese mitten crab, ecological monitoring data collected in freshwater shortly after the original sighting significantly shaped model estimates for abundance and documented the establishment phase of the mitten crab in an area outside the spatial scope of the surveyed resource users. However, the survey data significantly enlarged mitten crab range-size estimates by 6498.01 km². By demonstrating that data integration produced an image of the invasion process that would not have emerged had we used any 1 method individually, model results provide evidence for the advantages of an interdisciplinary approach.     

On-road measures of pedestrians' estimates of their own nighttime conspicuity

PROBLEM: Most pedestrian fatalities occur at night. Although researchers have long understood that drivers have difficulty seeing pedestrians at night and that reflective clothing can dramatically enhance pedestrian conspicuity, the extent to which pedestrians understand these facts is unclear. This experiment quantified pedestrians' estimates of the ability of an approaching driver to recognize the presence of roadside pedestrians. METHOD: Ten younger and 10 older participants walked in place on the far shoulder of a closed-road circuit and pressed a button when they were confident that the approaching driver could first recognize that a pedestrian was present. RESULTS: Pedestrians overestimated their visibility and dramatically underestimated the benefit of conspicuity treatments. CONCLUSIONS: These results suggest that pedestrians fail to understand the magnitude of the nighttime conspicuity problem and the value of conspicuity treatments. Pedestrians may therefore unknowingly place themselves in danger at night. IMPACT: These results underscore the need to educate pedestrians about the dangers of interacting with traffic at night and about treatments that increase their safety.     

Using the bootstrap and fast Fourier transform to estimate confidence intervals of 2D kernel densities

Kernel density estimators are often used to estimate the utilization distributions (UDs) of animals. Kernel UD estimates have a strong theoretical basis and perform well, but are usually reported without estimates of error or uncertainty. It is intuitively and theoretically appealing to estimate the sampling error in kernel UD estimates using bootstrapping. However, standard equations for kernel density estimates are complicated and computationally expensive. Bootstrapping requires computing hundreds or thousands of probability densities and is impractical when the number of observations, or the area of interest is large. We used the fast Fourier transform (FFT) and discrete convolution theorem to create a bootstrapping algorithm fast enough to run on commonly available desktop or laptop computers. Application of the FFT method to a large (n>20,000) set of radio telemetry data would provide a 99.6% reduction in computation time (i.e., 1.6 as opposed to 444 hours) for 1000 bootstrap UD estimates. Bootstrap error contours were computed using data from a radio-collared polar bear (Ursus maritimus) in the Beaufort Sea north of Alaska.     

COST EFFECTIVENESS OF VEGETATIVE FILTER STRIPS AND INSTREAM HALF‐LOGS FOR ECOLOGICAL RESTORATION1

ABSTRACT: This paper presents the results of cost effectiveness (CE) analysis of vegetative filter strips (VFS) and instream half‐logs as tools for recovering scores on a fish Index of Biotic Integrity (IBI) in the upper Wabash River watershed (UW) in Indiana. Three assumptions were made about recovery time for IBI scores (5,15, and 30 years) and social discount rates (1, 3, and 5 percent), which were tested for sensitivity of the estimated CE ratios. Effectiveness of VFS was estimated using fish IBIs and riparian forest cover from 49 first‐order to fifth‐order stream reaches. Half‐log structures had been installed for approximately two years in the UW prior to the study and provided a basis for estimates of cost and maintenance. Cost effectiveness ratios for VFS decreased from $387 to $277 per 100 m for a 1 percent increase in IBI scores from first‐to fifth‐order streams with 3 percent discount and 30‐year recovery. This cost weighted by proportion of stream orders was $360. The ratio decreased with decreasing time of recovery and discount rate. Based on installation costs and an assumption of equal recovery rates, half‐logs were two‐thirds to one‐half as cost‐effective as VFS. Half‐logs would be a cost‐effective supplement to VFS in low order streams if they can be proven to recover IBI scores faster than VFS do. This study provides baseline data and a framework for planning and determining the cost of stream restoration.     

Resolving future fire management conflicts using multicriteria decision making

Management strategies to reduce the risks to human life and property from wildfire commonly involve burning native vegetation. However, planned burning can conflict with other societal objectives such as human health and biodiversity conservation. These conflicts are likely to intensify as fire regimes change under future climates and as growing human populations encroach farther into fire‐prone ecosystems. Decisions about managing fire risks are therefore complex and warrant more sophisticated approaches than are typically used. We applied a multicriteria decision making approach (MCDA) with the potential to improve fire management outcomes to the case of a highly populated, biodiverse, and flammable wildland–urban interface. We considered the effects of 22 planned burning options on 8 objectives: house protection, maximizing water quality, minimizing carbon emissions and impacts on human health, and minimizing declines of 5 distinct species types. The MCDA identified a small number of management options (burning forest adjacent to houses) that performed well for most objectives, but not for one species type (arboreal mammal) or for water quality. Although MCDA made the conflict between objectives explicit, resolution of the problem depended on the weighting assigned to each objective. Additive weighting of criteria traded off the arboreal mammal and water quality objectives for other objectives. Multiplicative weighting identified scenarios that avoided poor outcomes for any objective, which is important for avoiding potentially irreversible biodiversity losses. To distinguish reliably among management options, future work should focus on reducing uncertainty in outcomes across a range of objectives. Considering management actions that have more predictable outcomes than landscape fuel management will be important. We found that, where data were adequate, an MCDA can support decision making in the complex and often conflicted area of fire management.     

Spatial-Scale Effects on Relative Importance of Physical Habitat Predictors of Stream Health

A common theme in recent landscape studies is the comparison of riparian and watershed land use as predictors of stream health. The objective of this study was to compare the performance of reach-scale habitat and remotely assessed watershed-scale habitat as predictors of stream health over varying spatial extents. Stream health was measured with scores on a fish index of biotic integrity (IBI) using data from 95 stream reaches in the Eastern Corn Belt Plain (ECBP) ecoregion of Indiana. Watersheds hierarchically nested within the ecoregion were used to regroup sampling locations to represent varying spatial extents. Reach habitat was represented by metrics of a qualitative habitat evaluation index, whereas watershed variables were represented by riparian forest, geomorphology, and hydrologic indices. The importance of reach- versus watershed-scale variables was measured by multiple regression model adjusted-R² and best subset comparisons in the general linear statistical framework. Watershed models had adjusted-R² ranging from 0.25 to 0.93 and reach models had adjusted-R² ranging from 0.09 to 0.86. Better-fitting models were associated with smaller spatial extents. Watershed models explained about 15% more variation in IBI scores than reach models on average. Variety of surficial geology contributed to decline in model predictive power. Results should be interpreted bearing in mind that reach habitat was qualitatively measured and only fish assemblages were used to measure stream health. Riparian forest and length-slope (LS) factor were the most important watershed-scale variables and mostly positively correlated with IBI scores, whereas substrate and riffle-pool quality were the important reach-scale variables in the ECBP.