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Evaluating vegetation cover is an important factor in understanding the sustainability of many ecosystems. Remote sensing methods with sufficient accuracy could dramatically alter how biotic resources are monitored on both public and private lands. Idaho National Laboratory (INL), in conjunction with the University of Idaho, evaluated whether unmanned aerial vehicles (UAVs) are sufficiently accurate and more efficient than the point-frame field method for monitoring vegetative cover and bare ground in sagebrush steppe ecosystems. These values are of interest to land managers because typically there are limited natural resource scientists and funding for comprehensive ground evaluations. In this project, unmanned helicopters were used to collect still-frame imagery to determine vegetation cover during June and July 2005. The images were used to estimate percent cover for six vegetative cover classes (shrub, dead shrub, grass, forbs, litter, and bare ground). Field plots used to collect imagery and on-the-ground measurements were located on the INL site west of Idaho Falls, Idaho. Ocular assessments of digital imagery were performed using SamplePoint, and the results were compared with field measurements collected using a point-frame method. The helicopter imagery evaluation showed a high degree of agreement with field cover class values for grass, litter, and bare ground and reasonable agreement for dead shrubs. Shrub cover was often overestimated, and forbs were generally underestimated. The helicopter method took 45% less time than the field method. This study demonstrates that UAV technology provides a viable method for monitoring selective types of cover on rangelands and could save time and resources.

In this study, the use of unmanned aerial vehicles (UAVs) as a quick and safe method for monitoring biotic resources was evaluated. Vegetation cover and the amount of bare ground are important factors in understanding the sustainability of many ecosystems. Methods that improve speed and cost efficiency could greatly improve how biotic resources are monitored on western lands. Sagebrush steppe ecosystems provide important habitat for a variety of species including sage grouse and pygmy rabbit. Improved methods of monitoring these habitats are needed because not enough resource specialists or funds are available for comprehensive on-the-ground evaluations. In this project, two UAV platforms, fixed-wing and helicopter, were used to collect still-frame imagery to assess vegetation cover in sagebrush steppe ecosystems. This paper discusses the process for collecting and analyzing imagery from the UAVs to 1) estimate percentage of cover for six different vegetation types (shrub, dead shrub, grass, forb, litter, and bare ground) and 2) locate sage grouse using representative decoys. The field plots were located on the Idaho National Laboratory site west of Idaho Falls, Idaho, in areas with varying amounts and types of vegetation cover. A software program called SamplePoint was used along with visual inspection to evaluate percentage of cover for the six cover types. Results were compared against standard field measurements to assess accuracy. The comparison of fixed-wing and helicopter UAV technology against field estimates shows good agreement for the measurement of bare ground. This study shows that if a high degree of detail and data accuracy is desired, then a helicopter UAV may be a good platform to use. If the data collection objective is to assess broad-scale landscape level changes, then the collection of imagery with a fixed-wing system is probably more appropriate.

Creeping environmental changes are impacting some of the largest remaining intact parcels of shrub-steppe ecosystems in the western United States and are creating major problems for land managers. The Idaho National Laboratory (INL) is part of the largest sagebrush steppe ecosystem on the continent. Scientists at the INL and the University of Idaho have integrated existing field and remotely-sensed data with geographic information systems technology to analyze how recent fires on the INL have influenced the current distribution of terrestrial vegetation. Three different vegetation mapping and classification systems were used to evaluate the changes in vegetation due to fires between 1994 and 2003. Twenty-four percent of the sagebrush steppe community on the INL was altered by fire, mostly over a seven year period. There were notable differences between methods, especially for juniper and grasslands. One method stood out in representing the landscape because it includes playa/bare ground/disturbed...

Collaborative watershed groups have formed at a significant rate throughout the United States in the last decade. Data on these groups, however, has been largely anecdotal and lacking in rigorous examination of the relationship between group formation, membership, process, and group effectiveness. Using a mail survey, Oregon watershed group participants were asked to identify who initiated the formation of the group, how efficiently the group formed, how the group determines membership, what decision making method the group uses, and how members perceive the group's effectiveness. Findings indicated that a majority believe that, because of their participation in a watershed group, they better understand issues in the watershed and the perspectives of others, but less than half believe that relationships with government decision makers or physical conditions in the watershed have improved. Members of citizen initiated groups rated their groups higher than government initiated groups on addressing difficult or controversial issues. Members of groups that use consensus responded most positively on whether the group gives fair consideration to dissenting opinions. Overall, groups with restricted membership systems rated themselves lowest on involving key decision making groups, timeliness in addressing issues, and overall effectiveness. These results raise concerns about this type of group membership system.

Interest in mordenite as an inhalation hazard arose when it was discovered that the mineral exists in the subsurface of Yucca Mountain, NV, the site of a federally proposed nuclear waste repository. During preliminary geologic investigations at Yucca Mountain, workers performing air coring (dry-drilling) operations were potentially exposed to aerosols of mordenite. Mordenite is also increasingly used in industrial applications, such as cation exchange, molecular absorbency, and reversible dehydration. Concern that the fibrous nature of mordenite may present an inhalation hazard is supported by the ''Stanton Hypothesis," which states that the carcinogenicity of any fiber type depends upon dimension and durability rather than physicochemical properties. To date, little scientific literature is available on the inhalation health hazards of mordenite. This study initiates research in this area. Mordenite specimens collected from different geologic localities were analyzed macroscopically and microscopically. ...

An important application of decision analysis is determining the value that information has to a decision maker. The expected value of information (EVOI) is the expected increase in the value (or decrease in the loss) associated with obtaining more information about quantities relevant to the decision process. The EVOI can be thought of as a measure of the importance of the uncertainty about a quantity in terms of the expected improvement in the decision that might be obtained from having additional information about it. Examples of EVOI quantities useful in risk management situations include the expected value of including uncertainty (EVIU), the expected value of perfect information (EVPI), and the expected value of sample information (EVSI). Value of information (VOI) analysis is useful because it makes the losses associated with decision errors explicit, balances competing probabilities and costs, helps identify the decision alternative that minimizes the expected loss, prioritizes spending on researc...

Confidence interval construction for central tendency is a problem of practical consequence for those who must analyze air contaminant data. Determination of compliance with relevant ambient air quality criteria and assessment of associated health risks depend upon quantifying the uncertainty of estimated mean pollutant concentrations. The bootstrap is a resampling technique that has been steadily gaining popularity and acceptance during the past several years. A potentially powerful application of the bootstrap is the construction of confidence intervals for any parameter of any underlying distribution. Properties of bootstrap confidence intervals were determined for samples generated from lognormal, gamma, and Weibull distributions. Bootstrap t intervals, while having smaller coverage errors than Student's t or other bootstrap methods, under-cover for small samples from skewed distributions. Therefore, we caution against using the bootstrap to construct confidence intervals for the mean without first considering the effects of sample size and skew. When sample sizes are small, one might consider using the median as an estimate of central tendency. Confidence intervals for the median are easy to construct and do not under-cover. Data collected by the Northeast States for Coordinated Air Use Management (NESCAUM) are used to illustrate application of the methods discussed.

Environmental decision making involving trace-levels of contaminants can be complicated by censoring, the practice of reporting concentrations either as less than the limit of detection (LOD) or as not detected (ND) when a test result is less than the LOD. Censoring can result in data series that are difficult to meaningfully summarize, graph, and analyze through traditional statistical methods. In spite of the relatively large measurement errors associated with test results below the LOD, simple and meaningful analyses can be carried out that provide valuable information not available if data are censored. For example, an indication of increasing levels of contamination at the fringe of a plume can act as an early warning signal to trigger further study, an increased sampling frequency, or a higher level of remediation at the source. This paper involves the application of nonparametric trend analyses to uncensored trace-level groundwater monitoring data collected between March 1991 and August 1994 on dissolved arsenic and chromium for seven wells at an industrial site in New York.

A methodology that simulates outcomes from future data collection programs, utilizes Bayesian Monte Carlo analysis to predict the resulting reduction in uncertainty in an environmental fate-and-transport model, and estimates the expected value of this reduction in uncertainty to a risk-based environmental remediation decision is illustrated considering polychlorinated biphenyl (PCB) sediment contamination and uptake by winter flounder in New Bedford Harbor, MA. The expected value of sample information (EVSI), the difference between the expected loss of the optimal decision based on the prior uncertainty analysis and the expected loss of the optimal decision from an updated information state, is calculated for several sampling plan. For the illustrative application we have posed, the EVSI for a sampling plan of two data points is $9.4 million, for five data points is $10.4 million, and for ten data points is $11.5 million. The EVSI for sampling plans involving larger numbers of data points is bounded by the expected value of perfect information, $15.6 million. A sensitivity analysis is conducted to examine the effect of selected model structure and parametric assumptions on the optimal decision and the EVSI. The optimal decision (total area to be dredged) is sensitive to the assumption of linearity between PCB sediment concentration and flounder PCB body burden and to the assumed relationship between area dredged and the harbor-wide average sediment PCB concentration; these assumptions also have a moderate impact on the computed EVSI. The EVSI is most sensitive to the unit cost of remediation and rather insensitive to the penalty cost associated with under-remediation.

A methodology for incorporating uncertainty in model predictions into a risk-based decision for environmental remediation is illustrated, considering polychlorinated biphenyl (PCB) sediment contamination and uptake by winter flounder in New Bedford Harbor, Massachusetts. Sensitivity and uncertainty analyses are conducted for a model that predicts the sediment remediation volume required to meet a biota tissue concentration criterion. These evaluations help to identify the variables that most significantly contribute to uncertainty in the model prediction and allow for calculations of the expected value of including uncertainty (EVIU) and the expected value of perfect information (EVPI) for the remediation decision. The EVIU is the difference between the expected loss of a management decision based solely on a deterministic analysis and the expected loss of the optimal management decision that considers uncertainty. For the illustrative application to New Bedford Harbor, the expected loss avoided from performing an uncertainty analysis and using the resulting information to make the optimal management decision is approximately $20 million. The EVPI, the expected decrease in loss that can be achieved by having all uncertainty eliminated, is approximately $16 million.