ISSN:0730-7268    

DOI:10.1002/etc.5620131201

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractWe have investigated the dependence ofspatial predictability, a statistical measure of the reduction in uncertainty about one spatial variable that can be gained by knowledge of another, on the spatial resolution (Rs) of the variables. While increasing resolution provides more descriptive information about the patterns in data, it also increases the difficulty of accurately modeling those patterns. By examining the variation of spatial predictability withRsin a number of case studies, we have proposed the existence of an “optimal”Rsfor specific studies, which balances these two factors. We analyzed land‐use data by resampling map data sets at several different spatial resolutions and measuring predictability at each. Spatialauto‐predictability(Pa) is the reduction in uncertainty about the state of a cell in a map given knowledge of the state of adjacent cells in that map, and spatialcross‐predictability(Pc) is the reduction in uncertainty about the state of a cell in a map given knowledge of the state of corresponding cells in other maps. ThePais a measure of the internal pattern in the data, whereasPcis a measure of the ability of some “model” to represent the transition from one map to another. We found a strong linear relationship between the log ofPdand the log ofRs(measured as the number of cells per square kilometer). WhilePagenerally increases with increasingRs(because more information is being included),Pcgenerally falls or remains stable (because it is easier to model aggregate results than fine‐grained ones). Thus, one can define an “optimal”Rsa particular modeling problem that balances the benefit in terms of increasing data predictability (measured byPa) as one increases resolution, with the cost of decreasing facility of modeling the temporal dynam

ISSN:0730-7268    

DOI:10.1002/etc.5620131202

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractThe quality of the scientific inputs to the policy process is known to be problematic. No one can claim “truth” for his results. Nor can uncertainty be banished, but good quality can be achieved by its proper management. The interaction of systems uncertainties and decision stakes can be used to provide guidance for the choice of appropriate problem‐solving strategies. When either or both of these are high, then mission‐orientedapplied scienceand client‐servingprofessional consultancyare not adequate in themselves, and an issue‐drivenpost‐normal scienceis necessary. Just as in cases with ethical complexities (as in biomedical science) there must be an “extended peer community,” including all stakeholders in the dialogue, for evaluating quality of scientific information for t

ISSN:0730-7268    

DOI:10.1002/etc.5620131203

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractEnvironmental models are often highly nonlinear, and parameters have to be estimated from noisy data. The standard approach of locally linearizing the model, which leads to ellipsoid confidence regions, is inappropriate in this situation. A straightforward technique to characterize arbitrary‐shaped confidence regions is to calculate model output on a grid of parameter values. Each parameter valuePresults in a goodness of fitG(P), which allows delineation of the set of parameters corresponding toG(P)

ISSN:0730-7268    

DOI:10.1002/etc.5620131204

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractA decision analytic approach is proposed for environmental planning and analysis under scientific uncertainty. This approach begins with the creation of a planning framework that consists of all relevant objectives and attributes, along with all feasible management options; this planning framework defines the inputs and outputs for subsequent work. Decision analysis may then be used to guide the subsequent work, beginning with the selection of predictive models linking management options to objectives. Once these models are identified, decision analysis may again be used, this time to identify environmental research and monitoring priorities. The approach is illustrated with an example concerning the management of eutrophication in Lake Okeechobee, Florida. Objectives, attributes, and management options were identified for the planning framework, and a simulation model was selected for a management objective concerned with the reduction in algal blooms. This model could then be used with uncertainty analysis to define specific scientific research and monitoring needs. Finally, once scientific analysis is complete, decision analysis can be used as the framework for decision making.

ISSN:0730-7268    

DOI:10.1002/etc.5620131205

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractA 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 millio

ISSN:0730-7268    

DOI:10.1002/etc.5620131206

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractEcological risk assessment has evolved so that the interaction among the components is now an implicit assumption. Unlike single species‐based risk assessments, it is often crucial in environmental or ecological risk assessments to be able to describe a system with many interacting components. In addition, some quantifiable description of how different biological communities respond upon the addition of a toxicant or some other stressor is required to adequately describe risk at the ecosystem level. Three methods have been applied at this level: the mean strain measurement used by K. Kersting, the state‐space analysis pioneered by A.R. Johnson, and the nonmetric clustering developed by G. Matthews for ecological data sets and for analysis of standardized aquatic microcosm data. Each method has direct application to the description of an affected ecosystem with‐out reliance upon a single specific and perhaps misleading endpoint. Each also can assign distance or probability measures in order to compare the control to treatment groups. Nonmetric clustering (NMC) has the advantage of not attempting to combine different types of scales or metrics during the multivariate analysis and is robust against interference by random variables. Applications of these methodologies into an ecological risk assessment should have the benefit of combining large interactive data sets into distinct measures to be used as a measure of risk and as a test of the prediction of risk. The primary impact of these methods may be in the selection and interpretation of assessment and measurement endpoints. Much recent debate in toxicological studies has focused on appropriate measurement endpoints for tests. Nonmetric clustering and other multivariate techniques should aid in the selection of these endpoints in ways meaningful at the ecosystem level. We suggest that the search for assessment and measurement endpoints be left to the appropriate multivariate computation algorithms in the case of multispecies situations. Application of these methods in the verification and validation process of risk assessment will serve to check the selection of endpoints during modeling exercises and to improve the presentation of assessment cri

ISSN:0730-7268    

DOI:10.1002/etc.5620131207

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractAn ecological risk assessment was conducted for sediments of the lower Willamette River near a wood‐treatment (creosote) facility. Both surface and subsurface sediments near the facility are contaminated by polycyclic aromatic hydrocarbons (PAHs). Limited contamination of sediments by dioxins/furans, chlorinated phenols, and arsenic was also observed. Sediment bioassays based on amphipod (Hyalella azteca) mortality and Microtox® (Photobacterium phosphoreum) bioluminescence showed toxicity within approximately 300 ft of the shoreline, with a highly toxic area (i.e., possible acute lethal effects in sedentary benthic species) near a dock used for creosote off‐loading. The relatively low concentrations of contaminants measured in crayfish muscle tissue and the absence of serious lesions in livers of large‐scale sucker collected near the site suggest that excess risk to mobile species from chronic contamination is low. Cursory observations indicate that acute toxic effects on crayfish may be associated with creosote seeps. There is no evidence of adverse biological effects throughout most of the main channel of the river. Evaluation of sediment chemistry data for PAHs relative to available sediment‐quality criteria proposed by the U.S. Environmental Protection Agency supports this co

ISSN:0730-7268    

DOI:10.1002/etc.5620131208

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractThe U.S. Environmental Protection Agency (EPA) initiated an innovative ecological risk assessment program at the Milltown Reservoir‐Clark Fork River Sediments Superfund Site in 1989. The site is located in the Clark Fork River (CFR) basin of western Montana, and consists of 160 km (100 miles) of the CFR and an 820‐acre wetland at Milltown Reservoir. The focus of the assessment was to identify chronic risks to ecological receptors from metals‐contaminated sediments that have deposited in aquatic and terrestrial habitats of the site. Lack of established sediment or soil quality criteria, the extent of habitats within the watershed, and anticipated complex sediment and soil chemistry led to a unique laboratory and field‐based approach for the baseline risk assessment. Study tasks evaluated aquatic, wetland, and terrestrial habitats across multiple trophic levels. The risk assessment integrated the results of these studies as a triad of chemical, toxicological, and ecological information. The comprehensive nature of the risk assessment was designed to help determine a remedial action for the wetland operable unit and set the basis for additional studies in the upper Clark Fork River watershed. As the problem formulation step in the EPA's risk assessment methodology, this article describes the background of the site, the approach and conceptual model for the risk assessment, and the planning process for implementing the various field and laboratory

ISSN:0730-7268    

DOI:10.1002/etc.5620131209

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY

摘要:

AbstractWetlands in mining districts in the western United States are frequently impacted by heavy metal contaminated sediments The present study summarizes a soil contamination evaluation and an ecological assessment completed for a Superfund site located at Milltown Reservoir wetlands (MRW) in western Montana For wetlands, as well as upland habitats adjacent to wetlands, biological evaluations in the field and laboratory should be considered critical components in the ecological risk assessment process Depending upon habitat type, field and laboratory methods have been developed for hazard and risk assessment that lend themselves directly to the Superfund ecological risk assessment process, and that consider contaminant bioavailability and subtle expressions of adverse biological effects associated with chronic exposures As part of an ecological risk assessment for MRW, field surveys and a variety of biological test methods (e g., terrestrial and aquatic tests) were critical to the wetland evaluation For evaluating heavy metal effects at MRW, field and laboratory methods within the ecological assessment included wetlands delineation and preliminary plant and wildlife survey, vegetation tests in emergent and upland habitats, soil macroinvertebrate (earthworm) tests, preliminary studies using amphibian and bacterial test systems, soil characterizations, and chemical analysis of soils, sediments, and biological materials In conjunction with chemical analyses, these biological and ecological evaluations yielded an integrated evaluation of ecological effects and exposure at MRW The data gathered from laboratory and field work at MRW suggested that biological and ecological effects were subtle in their expression in the wetland In conjunction with sediment contamination evaluations, these studies should reduce the uncertainty associated with the baseline ecological risk assessment forMRW

ISSN:0730-7268    

DOI:10.1002/etc.5620131210

出版商:Wiley Periodicals, Inc.    

年代:1994

数据来源: WILEY