Kelp as a Bioindicator: Does it Matter Which Part of 5 M Long Plant is Used for Metal Analysis?

Kelp may be useful as a bioindicator because they are primary producers that are eaten by higher trophic level organisms, including people and livestock. Often when kelp or other algae species are used as bioindicators, the whole organism is homogenized. However, some kelp can be over 25 m long from their holdfast to the tip of the blade, making it important to understand how contaminant levels vary throughout the plant. We compared the levels of arsenic, cadmium, chromium, lead, manganese, mercury and selenium in five different parts of the kelp Alaria nana to examine the variability of metal distribution. To be useful as a bioindicator, it is critical to know whether levels are constant throughout the kelp, or which part is the highest accumulator. Kelp were collected on Adak Island in the Aleutian Chain of Alaska from the Adak Harbor and Clam Cove, which opens onto the Bering Sea. In addition to determining if the levels differ in different parts of the kelp, we wanted to determine whether there were locational or size-related differences. Regression models indicated that between 14% and 43% of the variation in the levels of arsenic, cadmium, chromium, manganese, mercury, and selenium was explained by total length, part of the plant, and location (but not for lead). The main contributors to variability were length (for arsenic and selenium), location (mercury), and part of the plant (for arsenic, cadmium, chromium and manganese). The higher levels of selenium occurred at Clam Cove, while mercury was higher at the harbor. Where there was a significant difference among parts, the holdfast had the highest levels, although the differences were not great. These data indicate that consistency should be applied in selecting the part of kelp (and the length) to be used as a bioindicator. While any part of Alaria could be collected for some metals, for arsenic, cadmium, chromium, and manganese a conversion should be made among parts. In the Aleutians the holdfast can be perennial while the blade, whipped to pieces by winter wave action, is regrown each year. Thus the holdfast may be used for longer-term exposure for arsenic, cadmium, chromium and manganese, while the blade can be used for short-term exposure for all metals. Cadmium, lead and selenium were at levels that suggest that predators, including people, may be at risk from consuming Alaria. More attention should be devoted to heavy metal levels in kelp and other algae from Adak, particularly where they may play a role in a subsistence diets.     

Effect of imperfect detectability on adaptive and conventional sampling: simulated sampling of freshwater mussels in the upper Mississippi River

Adaptive sampling designs are recommended where, as is typical with freshwater mussels, the outcome of interest is rare and clustered. However, the performance of adaptive designs has not been investigated when outcomes are not only rare and clustered but also imperfectly detected. We address this combination of challenges using data simulated to mimic properties of freshwater mussels from a reach of the upper Mississippi River. Simulations were conducted under a range of sample sizes and detection probabilities. Under perfect detection, efficiency of the adaptive sampling design increased relative to the conventional design as sample size increased and as density decreased. Also, the probability of sampling occupied habitat was four times higher for adaptive than conventional sampling of the lowest density population examined. However, imperfect detection resulted in substantial biases in sample means and variances under both adaptive sampling and conventional designs. The efficiency of adaptive sampling declined with decreasing detectability. Also, the probability of encountering an occupied unit during adaptive sampling, relative to conventional sampling declined with decreasing detectability. Thus, the potential gains in the application of adaptive sampling to rare and clustered populations relative to conventional sampling are reduced when detection is imperfect. The results highlight the need to increase or estimate detection to improve performance of conventional and adaptive sampling designs.     

Remediation aspect of microbial changes of plant rhizosphere in mercury contaminated soil

Phytoremediation, an approach that uses plants to remediate contaminated soil through degradation, stabilization or accumulation, may provide an efficient solution to some mercury contamination problems. This paper presents growth chamber experiments that tested the ability of plant species to stabilize mercury in soil. Several indigenous herbaceous species and Salix viminalis were grown in soil collected from a mercury-contaminated site in southern Poland. The uptake and distribution of mercury by these plants were investigated, and the growth and vitality of the plants through a part of one vegetative cycle were assessed. The highest concentrations of mercury were found at the roots, but translocation to the aerial part also occurred. Most of the plant species tested displayed good growth on mercury contaminated soil and sustained a rich microbial population in the rhizosphere. The microbial populations of root-free soil and rhizosphere soil from all species were also examined. An inverse correlation between the number of sulfur amino acid decomposing bacteria and root mercury content was observed. These results indicate the potential for using some species of plants to treat mercury contaminated soil through stabilization rather than extraction. The present investigation proposes a practical cost-effective temporary solution for phytostabilization of soil with moderate mercury contamination as well as the basis for plant selection.     

Potential Economic Benefits of Adapting Agricultural Production Systems to Future Climate Change

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO₂ emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.     

Valuing the benefits of the urban forest: a spatial hedonic approach

This paper measures the benefits of the urban forest by examining its effect on housing prices. A Geographic Information System is used to develop a measure of the urban forest, the Normalised Difference Vegetation Index, from satellite imagery and to construct other variables from a variety of sources. Spatial hedonic housing price models for the Indianapolis/Marion County area are estimated. The models indicate that greener vegetation around a property has a positive, significant effect on housing price, holding everything else constant. This effect is dominated by measures at the neighborhood level. These findings indicate that property owners value the urban forest, at least in part, by the premium they pay to live in neighborhoods with greener, denser vegetation. These findings also indicate that public action to maintain and enhance the urban forest may be warranted. Planners and urban foresters can use these findings to inform public and policy debates over urban forestry programs and proposals.     

What kinds of injuries do OSHA inspections prevent?

Objective

OSHA's enforcement program is one of the major public efforts to protect American workers. We examine both the scope of injury prevention that inspections can contribute and the types of standards that contribute the most.

Methods

We linked Pennsylvania Department of Labor and Industry files for lost-time injuries and employment to calculate injury rates for 1998-2005 for all single-establishment manufacturing firms. We linked these to OSHA inspection records.

Results

Inspections with penalties did affect injury types unrelated to standards as well as those related. We also found again that citations for violations of the standard requiring personal protective equipment had the largest impact on preventing injuries.

Impact on Industry

Programs requiring protective equipment use deserve added attention from consultants and inspectors. In addition, some inspections spur managers to undertake safety measures that go beyond compliance with standards.     

Estimating trend precision and power to detect trends across grouped count data

Ecologists commonly use grouped or clustered count data to estimate temporal trends in counts, abundance indices, or abundance. For example, the U.S. Breeding Bird Survey data represent multiple counts of birds from within each of multiple, spatially defined routes. Despite a reliance on grouped counts, analytical methods for prospectively estimating precision of trend estimates or statistical power to detect trends that explicitly acknowledge the characteristics of grouped count data are undescribed. These characteristics include the fact that the sampling variance is an increasing function of the mean, and that sampling and group-level variance estimates are generally estimated on different scales (the sampling and log scales, respectively). We address these issues for repeated sampling of a single population using an analytical approach that has the flavor of a generalized linear mixed model, specifically that of a negative binomial-distributed count variable with random group effects. The count mean, including grand intercept, trend, and random group effects, is modeled linearly on the log scale, while sampling variance of the mean is estimated on the log scale via the delta method. Results compared favorably with those derived using Monte Carlo simulations. For example, at trend = 5% per temporal unit, differences in standard errors and in power were modest relative to those estimated by simulation (< or = /11/% and < or = /16/%, respectively), with relative differences among power estimates decreasing to < or = /7/% when power estimated by simulations was > or = 0.50. Similar findings were obtained using data from nine surveys of fingernail clams in the Mississippi River. The proposed method is suggested (1) where simulations are not practical and relative precision or power is desired, or (2) when multiple precision or power calculations are required and where the accuracy of a fraction of those calculations will be confirmed using simulations.