bluuebunny/crossref_metadata_2025 huggingface dataset:
Cardiac Toxicology
Authors: Coull Brent A. , Wellenius Gregory A.
Published: September 2006

Cardiovascular disease is still the primary killer in the US, claiming 953 110 lives in 1997. Thus, a major goal in environmental health research is risk assessment of environmental agents having potentially detrimental effects on heart function. This article focuses on the role electrocardiography has played in the assessment of cardiac toxicity.
Change‐Point Methods
Authors: Jandhyala Venkata K. , Fotopoulos Stergios B. , El‐Shaarawi Abdel
Published: September 2006

This article reviews recent applications of change‐point methods for modeling non‐stationarities in environmental data. In particular, we emphasize maximum likelihood based methods for the detection and estimation of parameter changes at unknown times in environmental time series data.
Coastal Processes
Authors: Prandle D.
Published: September 2006

This article discusses the coastal processes in shelf seas. Tides and waves are the most evident and energetic of motions. However, seasonal or localized vertical differences in density, arising from temperature and salinity variations, may be most significant in determining ecology. Likewise background, large‐scale circulations will determine the pathways and concentrations of persistent contaminants.
Control Group
Authors: Greenland Sander
Published: September 2006

A control group is a group of subjects who are given a control (reference) exposure, such as a placebo or no exposure, to provide a baseline against which to measure effects of the exposure in an exposed group of subjects.
Data Monitoring
Authors: Rodríguez José E.
Published: September 2006

Data monitoring is the practice of sampling systematically air, water, soil or biota.
Defoliation
Authors: Candy Steven G. , Zalucki Myron P.
Published: September 2006

From ancient times, mankind has attempted either to harness or prevent defoliation of trees and plants. The positive and negative impact of defoliation by invertebrates (chiefly insects), vertebrates, plant diseases or abiotic factors such as air pollution is an integral part of agriculture, forestry, and natural resource management. Defoliation is ‘an unseasonable reduction in the foliage cover of a plant due to attacks by insects or fungal disease, or as a result of other factors such as drought, storms, or chemicals in the atmosphere’. Defoliation encompasses partial or complete loss of the plant's foliage and partial or complete loss of individual leaves. The most significant impacts of natural defoliation are crop losses in agriculture and production forestry and, for native plant communities, possible changes in structure and species composition and loss of amenity values. It is not possible to review in this article the huge amount of information available on defoliation. In terms of measurement, estimation, or prediction there are a number of commonalities across the range of activities in which quantification of defoliation is required.
Detection Limits
Authors: Van Der Voet Hilko
Published: September 2006

In analytical chemistry the
detection limit
(also called
limit of detection (LOD)
or
minimum detectable value
) is considered a fundamental performance characteristic of methods of analysis. Basically, it is the lowest level (concentration, amount) of an analyte that can be reliably detected when chemical analysis is executed according to a well‐defined operating procedure in a state of statistical control. Thus, if the analyte is present at a lower level it may well be detected on single occasions, but in replicated analyses it will fail to be detected in a sizeable percentage of attempts. However, if the analyte is present at the level of the detection limit (or a higher level) the probability of detecting the analyte is at least a specific high value (commonly 95% is used in operational definitions of the detection limit). Being a performance characteristic, the detection limit is used to determine whether the analytical method is fit for the intended purpose: it quantifies the capability of detection of the analytical method as described in the operating procedure. This can only be done if the operating procedure includes a decision rule to decide whether the analyte is declared detected or not.
Atmospheric Dispersion: Heavy Gases
Authors: Nielsen Morten
Published: September 2006

Manufacturers, distributing agents, and public authorities need to formulate safety policies for toxic and flammable gases. This involves a wide range of aspects: intrinsic process safety, equipment, alarm systems, handling procedures, personnel training, spatial planning, and the likelihood and consequences of possible accidents. Gas dispersion is an important task in the consequence analysis and in the context of industrial accidents the source buoyancy and momentum may alter the flow and turbulence fields significantly. This calls for special dispersion models.
Diversity Measures
Authors: Solow A.R.
Published: September 2006

One way in which the term diversity is used in ecology is to characterize the relative abundances of species (or other types) in a community (or other collection of organisms). The relative abundance of a species is defined as the proportion of individual organisms in the community that are of that species. Consider a community containing
s
species. In qualitative terms, the community is said to be diverse if all of the relative abundances are close to 1 /
s
. If all of the relative abundances are equal to 1 /
s
, then the community is said to be even.
Echelon Analysis
Authors: Myers W.L. , Patil G.P.
Published: September 2006

Quantitative spatial data are important inputs for fueling the engines of many environmental models that determine future implications of current resource use, policies, and interventions. End products of applying such models are often mappings of indexes for level of potential environmental impact, which then become guides to allocation of economic and technical resources for amelioration. Errors in quantitative spatial data will propagate through environmental models and find expression in the resulting impact indexes. However, the consequences of such errors for decision‐making may well depend upon where the errors occur. There may be relatively little confusion introduced by moderate errors occurring in a vicinity that otherwise has consistently high values of a variable. In contrast, errors compound confusion in areas that are highly variable. Errors can also substantially distort the apparent state of areas that otherwise have consistently low values of a variable. It is therefore desirable to have a systematic means of determining spatial organization in mappings of quantitative variables, both for input variables to environmental models and for indexes of potential impact generated by the models. Modern computer capabilities for visualization of surfaces are helpful in this regard, but their interpretation is subjective.
Echelons
present an innovative alternative for objectively determining quantitative spatial structure for direct mapping, either with or without computer‐assisted visualization. Thus, they can facilitate analysis of errors associated with environmental models that take quantitative layers as input, or produce quantitative output layers, or both.
Ecosystem
Authors: Kimmins Hamish
Published: September 2006

In common with many other words in the vocabulary of ecology, ‘ecosystem’ is frequently misunderstood. This reflects the short period of a few decades over which this word has been used outside of academic ecology courses, and the lack of knowledge of ecosystem ecology by many who use the word. The word ecosystem was coined in 1935 by the English plant ecologist Tansley. While studying the terrestrial vegetation of the British Isles, he concluded that plant communities can only be understood when considered in the context of the soil, the climate, and the animal and microbial communities with which they are associated. He asserted that vegetation does not exist outside of the ecological system or ecosystem of which it is a part. The science of ecology (from oikos – house or habitat; logos – study of) has been given a variety of definitions that reflect differences in the interests and scientific training of their authors. However, the most complete, yet simplest, definition of ecology is
the study of ecosystems
. Thus, the concept of an ecosystem is the foundation for all branches of ecology, and it is, therefore, important that its meaning is understood.
Ecotoxicology
Authors: Newman Michael C. , Evans David A.
Published: September 2006

Ecotoxicology is the science of contaminants in the biosphere and their effects on constituents of the biosphere. Associated environmetric issues range widely and include those describing contaminant bioaccumulation, trophic transfer, and effects to ecological entities, e.g. individuals, populations, communities, and ecosystems.
Effect Size
Authors: Umbach David M.
Published: September 2006

Broadly construed, effect size is the degree to which one distribution differs from another. While the term itself has connotations of cause and effect, the underlying idea applies to any comparison between two populations without implying causality. Suppose that one seeks to compare two populations with respect to a specified outcome. Regard the populations as a control and an exposed population. The outcome under study will have some distribution across control individuals and, if the exposure has any effect at all, a different distribution among exposed individuals. Differences between the two distributions could be assessed using any one of a number of criteria or even using several criteria simultaneously. A desire for parsimony suggests the use of a single quantity for summarizing distributional differences. Generically, such a quantity assesses the magnitude of the exposure effect, that is, the effect size.
Endocrine Disruptors
Authors: Keiding Niels
Published: September 2006

In 1996, a European Workshop with broad representation from academia, the chemical industry, national and international organizations and regulatory agencies agreed on the following definition: ‘An endocrine disrupter is an exogenous substance that causes adverse health effects in an intact organism, or its progeny, secondary to changes in endocrine function.’
Exact Randomization Technique
Authors: Moir Rob
Published: September 2006

The exact randomization technique is a distribution‐free, computationally‐intensive statistical method of dealing with small samples and uncertain distributions. The technique was first proposed by Fisher in 1935 as a method of dealing with small biological samples. Because of the computational demands, only the recent development of powerful desktop computers permits researchers to regularly use this technique. Suppose two sets of observations are recorded and labeled according to whether they come from a treatment or a control group. The concept of randomization is based on the observation that a conventional test statistic (e.g. a
t
statistic) can be interpreted as a typical draw from the distribution of test statistics that would be generated from randomly shuffling the treatment and control labels among the observed data. In fact, the exact randomization test is essentially a controlled example of bootstrapping.
Fire Risk, Industrial
Authors: Thomas Ian
Published: September 2006

Fire represents both a benefit and a threat to society. Fire is essential and is used constructively in providing many of the materials and services essential to modern living. However, unwanted fires represent a threat that is generally immediately recognized and instils fear into those threatened. Fire generally represents a small but not insignificant risk in modern societies. It represented a greater risk in the past when open fires were common in domestic and industrial situations, but even today unwanted fires are responsible for considerable loss of life, property and services. The consequences of unwanted fires include injuries and death to people and animals involved, loss of contents and building structures and consequential damage to businesses and services. Many of these losses are not recorded, or alternatively, not made publicly available, and so the consequences associated with them are unable to be estimated accurately. However, in many countries considerable effort is expended in recording details of unwanted fires, including locations, causes and consequences. However, international collection of such information is restricted to very basic information such as the overall losses and costs of fires and the number of fire ‐related fatalities per annum.
Forensic Analysis
Authors: Johnson Glenn W.
Published: September 2006

Environmental forensics has been defined as the scientific investigation of criminal or civil offenses against the environment. This broad definition encompasses investigations that run the gamut from arson to poaching to chemical contamination of natural resources. The scientific methods brought to bear in these investigations are also quite broad. In cases of arson, investigators may rely on traditional criminal forensic techniques such as fingerprints and tire tread marks. Poaching investigations increasingly rely on relatively new forensic techniques such as DNA evidence. Chemometric methods are common in environmental forensic investigations, in particular, in cases involving pollutant source allocation. The challenge is to determine how cleanup costs (or in the case of natural resource damage claims, redress costs) will be split among multiple, potentially responsible, parties. Regulatory agencies and potentially responsible parties seldom agree regarding equitable cost‐allocation. Similarly, potentially responsible parties rarely agree among themselves. Each party must make their case to a regulatory agency, an arbitrator, perhaps even a jury. The case inevitably depends on the analysis of huge amounts of environmental chemical data, and that in turn depends on environmental chemometrics.
Forest Inventory
Authors: Scott Charles T. , Gove Jeffrey H.
Published: September 2006

Forest inventory is an accounting of trees and their related characteristics of interest over a well‐defined land area. It may be compared to census methods for human populations. For example, one of the goals of the periodic decennial census of the US is to enumerate its human population and to retrieve demographic variables such as age, sex and race. This is accomplished by a comprehensive survey of all households in the country. Similarly, forest inventories seek to enumerate the population of trees within a forest and ascertain other information, such as their volume, value, growth and species composition. For all but the smallest tracts of land, complete enumeration of individuals is usually infeasible and survey sampling techniques are required. Unlike human or animal populations, trees are sessile organisms and there is no immigration or emigration to consider. However, tree populations vary widely in their species composition, age, size, site requirements, potential value, longevity and growth – all factors that may influence the design of a forest inventory. In addition, the tree population of interest may exist over a wide variety of topography, making access potentially costly and sometimes even dangerous. Such variety often dictates sampling protocols that may be optimal only for some portion of the population in question. Alternatively, it may call for varying sampling intensity or strategy (the combination of the sampling design and associated estimators) between different regions within the population.
Least Squares, General
Authors: Haslett John
Published: September 2006

As with least squares (more specifically ordinary least squares, OLS), general least squares (GLS) is formally a criterion, and an extension of the OLS criterion. But, even more than OLS, GLS is most frequently discussed as a method for fitting a specific model, often referred to as the general linear model (GLM).
Global Ecology
Authors: Lerdau Manuel
Published: September 2006

Global ecology began with Joseph Priestly's experiments in the eighteenth century demonstrating that plants in effect purified air and thus allowed animals to survive. These results provided the first hard evidence that the activities of some organisms had impacts on the functioning of other organisms at spatial scales greater than that of the individual. More recently, Alfred Redfield demonstrated in the middle of the last century that the structure and behavior of marine organisms played a major role in determining the chemistry of the oceans. In the last 25 years, global ecology has expanded to include a wide range of organismal activities that affect continental and larger spatial scales.
Groundwater Monitoring
Authors: Thornton Steven F. , Lerner David N. , Davison Ruth M.
Published: September 2006

Water that exists below the earth's surface and completely fills pore spaces in the rock strata is termed groundwater. It is estimated that only 0.6% of the total amount of water on the earth is present as groundwater, the majority (97%) being seawater, with the remainder including water trapped in glaciers and polar ice‐caps, present in the atmosphere, and surface freshwater in lakes and rivers. Excluding ice, groundwater represents 97% of nonmarine water, although it is not uniformly distributed and may not be economically usable as a water supply. The proportion of drinking water derived from groundwater resources varies substantially, from only 5% in Norway to 100% in Malta and The Netherlands. This largely reflects the geographical distribution of suitable aquifers from which groundwater can be abstracted and the availability of surface water supplies. Aquifers are those rocks that are sufficiently porous to store water and permeable enough to yield groundwater in economic quantities. The exploitation of groundwater resources requires that the distribution of groundwater in aquifers can be identified and quantified and its quality monitored.
Heritability
Authors: Fry James D.
Published: September 2006

Heritability is a central concept of quantitative genetics, the branch of genetics that deals with the inheritance of continuously‐varying traits. Most traits of agricultural and ecological importance, such as fruit weight or grain yield, are continuous traits. The heritability can be estimated by measuring the degree of resemblance, quantified by the covariance, between relatives of various types.
Interlaboratory Studies
Authors: Vangel Mark G.
Published: September 2006

Interlaboratory studies (sometimes referred to as
collaborative studies
, or
round robins
) are investigations in which measurements are made on one or several materials at several laboratories. These studies are typically conducted for one of three reasons: (i) to evaluate a measurement method; (ii) to evaluate a reference material; or (iii) to evaluate the proficiency of the laboratories themselves.
Litter Effect
Authors: Kupper Lawrence L.
Published: September 2006

It has long been recognized that humans exposed to certain drugs, chemicals, and other environmental hazards may be at increased risk of various health problems. Exposure‐related, adverse, heritable, human health outcomes currently receiving increased attention by public health professionals are fertility and pregnancy complications, birth defects, and developmental abnormalities. Well‐conducted environmental epidemiology studies on human populations would provide the most relevant data for quantifying relationships between exposure levels and adverse pregnancy‐ related outcomes. However, useful information from observational data on humans is often limited in both quantity and quality. So, despite the obvious species‐to‐species extrapolation problem, controlled laboratory experiments on rodents are commonly conducted to provide developmental toxicology data. This article focuses specifically on developmental toxicology studies, where pregnant rodents are exposed to a suspected harmful agent during the period of major fetal organogenesis and structural development. It is well known that an inherent characteristic of data from such rodent teratology studies is the so‐calledlitter effect, i.e. the tendency for littermates all to respond in the same way to stimuli, unlike animals from different litters. Litter effects seem to be present in almost all developmental toxicology studies, and data analyses that do not appropriately account for these litter effects can lead to erroneous statistical inferences.
Matric T‐Distribution
Authors: Sun Li
Published: September 2006

The
t
distribution was first introduced by W.S. Gosset in 1908. Many environmental processes are modeled by
t
instead of Gaussian distributions in order to incorporate uncertainties fully. Successful applications of this kind include air pollution, health impact and epidemiology. A random variable that possesses a
t
distribution can be represented as a ratio of an independent normal and the square root of a χ
2
random variable divided by its degrees of freedom. The degrees of freedom of the χ
2
distribution represent the uncertainty one has about the location of the distribution. In sampling theory, a
t
distribution can be derived from a sample mean and sample variance.
Meta‐Analysis
Authors: Tweedie (deceased June 2001) R.L.
Published: September 2006

The idea of combining information from different studies of the same effect is an old and appealing one. In many areas it has long been common to see reviews of an area, with an expert bringing together the different information and synthesizing a conclusion from many disparate sources. Such overviews often contain qualitative or subjective impressions of the totality of information available, and it was largely in attempts to formalize this approach that the techniques of meta‐analysis have been developed. Meta‐analysis (sometimes called a ‘quantitative synthesis’ or an ‘overview’ is the term used to describe
quantitative
methods for combining information across different studies. It has become particularly popular in situations where the studies individually do not show that an effect is statistically significant.
Model Evaluation and Performance
Authors: Beck B.
Published: September 2006

Whether the behavior of a model matches the behavior of the (real) system–sufficiently well–has always been a matter of great interest. In lay terms, these are the essential questions one would like to have answered in seeking to evaluate a model: (i) has the model been constructed of approved materials, i.e. approved constituent hypotheses (in scientific terms)? (ii) does its behavior approximate well that observed in respect of the real thing? (iii) does it work, i.e. does it fulfill its designated task, or serve its intended purpose?
Collinearity
Authors: Sundberg Rolf
Published: September 2006

Collinearity refers in a strict sense to the presence of exact linear relationships within a set of variables, typically a set of explanatory (predictor) variables used in a regression‐type model.
Multiphase Sampling
Authors: Lesser Virginia M.
Published: September 2006

Multiphase sampling is an extension of two‐phase sampling, also known as double sampling. Multiphase sampling must be distinguished from multistage sampling since, in multiphase sampling, the different phases of observation relate to sample units of the same type, while in multistage sampling, the sample units are of different types at different stages.
Transformations, Multivariate
Authors: Ruppert David
Published: September 2006

Many of the classical techniques of multivariate analysis, e.g. principal components, factor analysis, canonical correlations, and linear discriminant analysis are based upon the assumption that the data have been sampled from a multivariate normal distribution. These techniques can be quite nonrobust towards some types of deviations from normality, for example heavy‐tails or skewness. When the data deviate from normality, multivariate transformation can re‐express the data as a sample closer to being multivariate normal. In principle, the methodologies developed for transformation to multivariate normality could be used to transform to other multivariate distributions. However, the normal distribution plays such a central role in multivariate analysis that transformation to other multivariate targets has not been considered as important and will not be discussed in this article.
N
ational
R
esources
I
nventory (
NRI
),
US
Authors: Breidt F. Jay
Published: September 2006

The US National Resources Inventory (NRI) is a longitudinal panel survey conducted by the US Department of Agriculture's Natural Resources Conservation Service (formerly the Soil Conservation Service) in cooperation with the Iowa State University Statistical Laboratory. In its current form, the NRI is designed to assess conditions and trends at five year intervals for soil, water, and related natural resources on nonfederal lands of the US. The survey has evolved over a period of several decades, with the specific goal of providing information to support agricultural and environmental policy development and program implementation.
Neurotoxicology, Environmental
Authors: Catalano Paul J.
Published: September 2006

Neurotoxicity testing is an important area of noncancer toxicity evaluation. This article provides a description of the functional observational battery (FOB), a frequently employed neurobehavioral assessment, and discusses some of the statistical and data analytical issues surrounding its analysis. Emphasis is given to describing the multivariate nature of the FOB data.
Occupational Mortality
Authors: Symons Michael J.
Published: September 2006

In studies of mortality of industrial workers, statistical options are limited when: (1) only a few deaths are observed; (2) exposure information at the workplace is nonexistent; (3) personal concomitant exposure data are not available. With none, some, or all of these limitations, the standardized mortality ratio (SMR) is the most frequently used statistic for occupational and environmental cohorts. The SMR is the total number of observed events,O, divided by the total number expected events,E, for those under study. The SMR, as a one‐dimensional summary statistic, is both attractive and limited in scope. It is widely used in mortality studies of industrial populations, serving to screen for excess causes of death and to test for an excess of a specific cause of mortality. A variety of study designs – commonly, proportional mortality, cohort mortality, and case‐control studies – are utilized in the further investigation of hypotheses generated or for more confirmatory tests of results from previous analyses.
Oceanographic Dispersion
Authors: Gargett Ann E.
Published: September 2006

A depth profile taken anywhere in the ocean reveals large vertical gradients of any number of oceanic water properties; for example, temperature, salinity, oxygen concentration, macronutrients such as nitrate and silicate, and micronutrients such as iron. These vertical gradients are formed at the very largest (depth/basin) scales of motion in the sea and eradicated at the very smallest scales, those associated with three‐dimensional turbulence This article first describes the tools presently used to measure and interpret characteristics of the small‐scale ocean processes that result in enhanced vertical diffusion, then reviews various processes known or believed to generate these small scales.
Oceanography
Authors: Greatbatch Richard J. , BobanoviĆ JoŠko , Sheng Jinyu , Thompson Keith
Published: September 2006

In this article we provide some background on the topic of environmetrics within the context of oceanography, and give examples applied to both the coastal ocean and the large‐scale ocean/climate system.
Parallel Computing
Authors: Kulperger Reg , Yu Hao
Published: September 2006

Parallel computing consists of a computing environment connecting many processors. A new technology of distributed processing with a more loose connection between processors is emerging. Both require some special programming methods to take advantage of the connections and communications between processors, but are well suited to certain imaging problems and other statistical problems. This article describes some of the aspects of dealing with these special programming requirements, based on our experience, as statisticians, with such technologies. The types of problems and statistical use of such computing technologies are also discussed. This article is intended to give the reader an overview of the parallel computing environment focusing on the statistical uses that can be made, as opposed to a more detailed computing or engineering description.
Pelagic Ecology
Authors: Reynolds Colin
Published: September 2006

The term ‘pelagic zone’ refers essentially to the open ocean, beyond the continental shelves. However, ‘the pelagic’ is understood by freshwater ecologists to mean simply ‘the open water’ of large lakes and reservoirs. In either instance, the notion of a liquid environment, remote from the shores and bottom of the containing basin, is clear. In extent, the marine pelagic is, by far, the greatest of the world’s major ecosystems, covering some 361 × 10
6
km
2
(or 71% of the planet’s surface) and accommodating an estimated volume of 1.35 × 10
9
km
3
. In contrast, the aggregate volume of the world’s lakes and rivers is a relatively modest 225 × 10
3
km
3
.
Piecewise linear model
Authors: Küchenhoff Helmut
Published: September 2006

In many practical regression‐type problems we cannot fit one uniform regression function to the data, since the functional relationship between the response
Y
and the regressor
X
changes at certain points of the domain of
X
. These points are usually called break points or change points. In such situations, we apply regression models that are obtained by a piecewise definition of the regression function on intervals of the domain of
X
.
Plant epidemics, models and analysis
Authors: Madden Laurence V. , Hughes G.
Published: September 2006

Plants are susceptible to many diseases; fungal, bacterial, viral, and other forms of epidemics occur commonly in agricultural systems, resulting in substantial crop yield reductions. There are two primary ways of measuring plant disease, incidence and severity. Plant disease incidence can be defined as the number of diseased plants, or plant parts expressed as a proportion of the total number of plants, or plant parts, assessed. Plant disease incidence is a binary variable, because individuals are either diseased or not. Plant disease severity, on the other hand, can be defined as the area or volume of plant tissue that is diseased, usually relative to the total plant tissue. It is a continuous variable, typically bounded by 0 and 1. In this article, emphasis is placed on incidence. Statistical issues regarding plant diseases in crops or natural systems concern the characterization of spatial patterns of disease, estimation of rates of disease increase over time, and rates of spatial spread. There is a variety of statistical tools available to quantify spatial pattern of disease incidence, which can be categorized based on the general type of analysis – point pattern or geostatistical analysis – or on whether the data consist of mapped or unmapped observations.
Quantitative Structure‐Activity Relationships (
QSARs
)
Authors: Williams Paige L.
Published: September 2006

Quantitative structure activity relationships (QSARs) have historically been used in the design and evaluation of new pharmaceutical products. With the rapid increase in modern computing power, the use of QSAR methods in the field of drug development has seen an explosive range of applications in the late 1990s. QSAR approaches have also been used in environmental risk assessment to predict the carcinogenicity or genotoxicity of toxic agents, and thus reduce the costs of conducting long‐term animal studies. The application of QSAR methods has traditionally encompassed two different approaches: the extrathermodynamic approach proposed by Hansch and Fujita, and the ‘substructural’ or ‘connectivity’ approach of Free and Wilson.
Radiation and Radiative Transfer
Authors: Essex Christopher
Published: September 2006

Radiation surrounds us, runs through us, and is even produced within us. While the term has taken on a sinister connotation since the development and use of nuclear power in the middle of the twentieth century, it is a misconception that radiation is not a natural part of the environment. There is no way to escape it entirely, neither would one want to. Sunshine is the most obvious form of radiation in our lives. Despite recent worry about it, from the standpoint of ultraviolet radiation, the world would literally die without solar radiation. Moreover, it pertains to many global environmental issues, from forecasts of global warming to ozone depletion. These topics too are burdened with misconceptions that are especially pertinent to those seeking a quantitative, environmetric outlook on radiation. Some of the most important of these will be identified in this article.
Ranks
Authors: Hallin Marc
Published: September 2006

Rank tests were introduced as a reaction against the traditional assumption of Gaussian observations. The most attractive feature of ranks and rank statistics is that they are distribution‐free, and thus, in principle, allow for exact critical values, irrespective of the underlying distribution of the observation. Their domain of application is, mainly but not exclusively, the class of semiparametric models obtained from the traditional parametric ones (location, scale, regression, autoregression, etc.) by treating the density of the underlying error or noise as an unspecified nuisance. Their popularity is explained by their success in a variety of practical situations, and their robustness against deviations from standard distributional assumptions.
Recursive Residuals
Authors: Frühwirth‐Schnatter Sylvia
Published: September 2006

Recursive residuals are used for model diagnostics, especially for time series models of continuous observations. By model diagnostics one means checking properties residuals should have under the assumption that the data were generated by the model under investigation. This check can be exploratory or formal. What distinguishes diagnostics based on recursive residuals from more conventional methods is the way the residuals are defined in a recursive manner from one‐step ahead predictive densities.
Rivers, Canals and Estuaries
Authors: Monismith Stephen
Published: September 2006

Environmentally important flows in rivers, canals and estuaries are characterized by turbulence generated at their sides and bottoms, and are capped by free surfaces that deform in response to the underlying flow, giving rise to a rich range of behavior including multiple flow depths for a given flow and a variety of wave propagation phenomena. They also have erodible and moveable beds that respond to the flow, leading to meandering channels as well as to significant transport of sediments from the land to the sea. Estuaries, where fresh river water mixes with salty ocean water, often have significant tidal motions that play an important role in sediment dynamics, mixing of pollutants, and salinity intrusion, an increase in river salinity that can render fresh water non‐potable or even unusable for irrigation. A significant aspect of the mixing in estuaries is the difference in density between salt and fresh water, a difference that leads to buoyancy forces that significantly influence flows found in estuaries.
SAS
Authors: Littell Ramon C.
Published: September 2006

The SAS
®
System is an integrated system of software for data management, analysis, and presentation.
Seemingly Unrelated Regressions
Authors: Bartels R.
Published: September 2006

Seemingly unrelated regression (SUR) is a widely used modeling approach introduced by Zellner for situations where several linear regression relationships are being investigated at the same time. Examples of the use of SUR in environmetrics include Boisvert et al., who considered separate equations for the effect of water contamination on both the purchase price and rental value of farmland, and Xu, who estimated separate equations for the impact of environmental legislation on the output of each of a number of industrial sectors. The key feature in these cases is that each of the linear equations, on its own, satisfies the classical conditions underpinning the linear regression model, and hence the ordinary least squares (OLS) estimator can be used to estimate each equation individually. However, if the error terms of the different equations are correlated across the equations, then joint estimation of the equations may be able to exploit this cross equation correlation to obtain more efficient estimates.
Shrinkage Regression
Authors: Sundberg Rolf
Published: September 2006

Shrinkage regression refers to shrinkage methods of estimation or prediction in regression situations, useful when there is multicollinearity among the regressors. With a term borrowed from approximation theory, these methods are also called regularization methods. Such situations occur frequently in environmetric studies, when many chemical, biological or other explanatory variables are measured.
Soil Surveys
Authors: Abbitt Pamela J.
Published: September 2006

Soil surveys are conducted in order to construct maps delineating soil map units (SMUs) and descriptions of the soil characteristics of each map unit. Soil survey reports are used in the areas of farming, forestry, rangeland management, conservation planning, and urban activities such as transportation planning and residential and industrial development. Information from soil surveys is needed increasingly to support analyses in the areas of soil quality and environmental research and management. Natural resource scientists need geo‐referenced data and statistical descriptions of soil characteristics in order to model the complex processes that are affected by soil properties.
Spatial Analysis in Ecology
Authors: Fortin Marie‐Josée , Dale Mark R.T. , ver Hoef Jay
Published: September 2006

The first step in understanding ecological processes is to identify patterns. Ecological data are usually characterized by spatial structures due to spatial autocorrelation.
Spatial autocorrelation
refers to the pattern in which observations from nearby locations are more likely to have similar magnitude than by chance alone. The magnitude, intensity, as well as extent of spatial autocorrelation can be quantified using spatial statistics. Most ecological data exhibit some degree of spatial autocorrelation, depending on the scale at which the data were recorded and then analyzed. Ecological phenomena are also characterized by the multiple ecological processes that act upon them; these processes often operate at more than one spatial scale. Ecological data are a composite of several spatial scales: trends at macroscales; patches, gradients and patterns at meso‐ and local scales; and random patterns at local and microscales. The different processes and patterns at different scales are not necessarily linear or additive, and this contributes to the degree of spatial dependence in the data.
Spatially Constrained Sampling
Authors: See Kyoungah , Song Sung‐Yell
Published: September 2006

Environmental epidemiology is a discipline that relies to a large extent on observational studies; even the case–control studies that are a standard tool of epidemiologists do not approach the rigor of the design of agricultural field trials. There is a very real tension in environmental epidemiology between the desire to establish a network of causation and the lack of experimental control available in observational studies. However, when the ‘signal’ is strong enough, sometimes it is possible to establish causative relationships. To make progress with noisy data and vaguely formulated hypotheses, statistical models have been developed that allow inference even down to individual levels, such as in frailty models. Many of these models are hierarchical and some are spatial, and it is on these that this article focuses.
Stochastic Model
Authors: Preisler Haiganoush K.
Published: September 2006

Environmental scientists use models – a system of assumptions presented in a mathematical framework – to study complex interrelationships in ecological processes and to assess and predict the impact of our actions on the environment, among other things. There are a variety of model types: stochastic, deterministic, numerical, to name a few. A major concept that distinguishes stochastic models from other models is the idea of probability, or randomness, that is explicit in all stochastic models.
Tessellations
Authors: Schoenberg Frederic Paik
Published: September 2006

A
tessellation
may be defined as a division of a space into convex polygonal regions; divisions of the
plane
(

R
2

) are most often discussed. While geometrists centuries ago reserved the term tessellation merely for divisions of the plane into
regular
polygons of equal size, most authors now define tessellations very broadly so as to include any arrangements of nonoverlapping shapes covering

R
d

, as well as partitions of other metric spaces.
Trawl Surveys
Authors: Nordahl Victor , Clark Steve
Published: September 2006

Trawl surveys for fishery resources are conducted throughout the world by government and non‐government agencies. Modern fishery management requires standard time series of data on management units or ‘stocks’ and their response to exploitation: trends in abundance and biomass; spawning success; biological parameters; distribution; and environmental factors that can be provided only through standardized sampling programs. Trawl surveys provide the opportunity for controlled sampling in space and time.
Up‐and‐Down Designs
Authors: Flournoy Nancy
Published: September 2006

Up‐and‐down designs are useful for evaluating and comparing the toxicity of pesticides and other chemical compounds. In particular, the primary goal of an up‐and‐down design in toxicity studies is to estimate the dose having a prespecified toxicity rate γ, 0 > γ > 1. A secondary goal is to limit the experimental subjects that are given highly toxic exposure. Up‐and‐down designs can be sequential or group sequential.
Wavelets
Authors: Percival Donald B.
Published: September 2006

Wavelets are a special class of functions (or sequences) that are widely used for analyzing time‐ series. Just as Fourier analysis is based upon the notion of representing (or re‐expressing) a time series as a linear combination of sinusoids, the idea underlying wavelet analysis is to represent the series as a linear combination of wavelets. In Fourier analysis, each sinusoid is associated with a particular frequencyf, so what frequencies are important in a particular time series can be deduced by studying the magnitudes of the coefficients of the various sinusoids in the linear combination. In contrast, each wavelet is associated with two independent variables, namely, timetand scaleτ, because each wavelet is essentially nonzero only inside a particular interval of times, namely, [t – τ,t + τ]. Within that interval, the wavelet spends roughly an equal amount of time above and below zero, so it appears to be a ‘small wave’ centered at timetand having a width of 2τ. We can thus learn how a time series varies on particular scales across time if it is re‐expressed using wavelets.
Weibull Distribution
Authors: Fotopoulos Stergios B. , Jandhyala Venkata K.
Published: September 2006

The article brings together various results on the Weibull distribution in a unified manner. The introduction contains numerous references regarding applications of the Weibull distribution and subsequent sections address a variety of theoretical developments. Some of the theoretical developments covered include characterization, extreme value theory, parameter estimation and goodness of fit. The estimation and goodness of fit methods are illustrated by modeling the data on minimum temperatures in Uppsala, Sweden.
Whole Effluent Toxicity
Authors: Fox John F. , Denton Debra L.
Published: September 2006

Whole effluent toxicity (WET) tests are designed to estimate the toxicity of aqueous chemical mixtures, effluents, ambient (receiving) waters or stormwaters. WET tests use freshwater or marine plants, invertebrates or vertebrates to measure the aggregate toxicity of such waters. Tests for acute toxicity (‘acute tests’) measure mortality, usually after 24, 48 or 96 hours. Tests of chronic toxicity (‘chronic tests’) usually run longer and measure sublethal effects, such as reduced reproduction, growth, fertilization or larval development, in addition to mortality. Regulatory authorities recommend testing wastewaters with organisms from several phyla to determine the most sensitive test species for routine testing.
Lost in transition: Challenges in the expanding field of adult genetics
Authors: Taylor Matthew R.G. , Edwards Janice G. , Ku Lisa
Published: October 2006

It is increasingly clear that medical genetics has broad relevance in adult clinical medicine. More adult patients with genetic conditions are being recognized, genetic testing for adult‐onset genetic conditions is expanding, and children with genetic conditions are now more likely to survive to adulthood. While the number of patients who could benefit from medical genetic services increases, adult care providers are less well educated about clinical genetics and are not sufficiently prepared to meet the growing needs of this population. Genetics professionals may also be ill‐suited for this challenge, since geneticists and genetic counselors have traditionally had greater experience in pediatric and prenatal settings. Communication between primary care physicians who treat adults and the genetics community is currently suboptimal and the identification and subsequent referral of adult patients for genetic services need improvement. Finally, published guidelines that address how to deliver genetic services to adult patients are unavailable for many genetic conditions. In this article we address the challenges of transitioning genetics services from traditional, and largely pediatric‐based models to paradigms that can best address the needs of adult patients with genetic conditions. Potential solutions and the practicality of implementation of a team‐based approach to adult genetic medicine, including the application of genetic counseling, are also discussed. © 2006 Wiley‐Liss, Inc.