bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing Personal Learning Environments (PLEs). An expert evaluation
Authors: Llorente Cejudo María del Carmen
Published: January 2013

On the basis of the Research Project funded by the Spanish Ministry of Education under the title “Design, production and evaluation of a 2.0 learning environment for faculty training in the use of Information and Communication Technologies (ICTs)” (EDU2009-08 893), experts have used the external competence coefficient to evaluate the different dimensions of Personal Learning Environments (PLE), namely: technical and aesthetic aspects, ease of navigation, or quality of the didactic elements that make up the environment. A quantitative methodology along with a questionnaire prepared by the author served this purpose. The results obtained highlight technical environment operation, the tools forming the PLE, or the learning object repository as being “very positive.” In conclusion, experts emphasise the user-friendliness of environment and tools alike, as well as the educational aspects of the contents available in materials guides
Absorption and Ingestion Toxicology
Authors: Sen Pranab K.
Published: January 2013

Absorption and ingestion toxicology relates to the prevalence of ambient toxins, their intake process by human being through skin (epidermal) absorption, or ingestion as foods, drinks, or drugs (narcotic or not) either taken orally or by injection, biological/neurological/behavioral reactions, related molecular and carcinogenic developments, and resulting health hazards.
Abundance: Population Size and Density Estimation
Authors: Udevitz Mark S. , Gould William R.
Published: January 2013

Estimates of population size (total number of individuals) or density (number of individuals per unit area) are some of the most basic requirements for wildlife research and management. This article provides a brief overview of approaches for wildlife population estimation. These include habitat‐based approaches such as quadrat, line intercept, distance, and repeated count methods, as well as animal‐based approaches such as capture–recapture and harvest methods. In contrast to methods that only index changes in these parameters, estimates of size or density must account for the probability that an individual will be included in the sample used for estimation. The essential differences in the approaches are in how the samples are obtained and how the sampling probabilities are estimated.
Air Quality Indicators, Pollutant Specific
Authors: Hunt William F. , Marceau Rachael , Anderson Alissa , Immen Kristen , Pigg Ryland , Mintz David
Published: January 2013

Pollutant‐specific air quality indicators can be extremely useful in communicating environmental information to the public, air pollution control officials, the private sector, the Congress, and academia. This article examines the use of National Ambient Air Quality Standard (NAAQS)‐related pollutant‐specific air quality indicators. Standard‐related statistics are used to understand (i) pollutant‐specific air quality trends, (ii) the impact of pollutant control strategies, (iii) tracking emission reductions, (iv) air quality status and the severity of the air pollution problem, and (v) the calculation of design values as required by the 1990 Clean Air Act. The traditional EPA trend methodology is compared with both meteorologically adjusted trends and population‐ and land area‐weighted trends.
American Society for Testing and Materials
Authors: El‐shaarawi Abdel H.
Published: January 2013

The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.
Aquatic Toxicology
Authors: Bailer A. John , Oris James T.
Published: January 2013

Water is the key to life, and aquatic toxicology evaluates the potential adverse outcomes associated with exposure to contaminated waters. These adverse outcomes can be observed at all trophic levels and can be framed at differing levels of ecosystem function. Statistical analysis of concentration‐response relationships provides one foundation for evaluating the impact of toxicants on aquatic systems and for setting exposure limits to such toxicants. This entry describes stressors on aquatic systems, considers ecosystem impact of stressors, reviews statistical methods that have been used for evaluating these impacts and considers current and future challenges for evaluating aquatic toxicants.
BACI
Design
Authors: Smith Eric P.
Published: January 2013

The purpose of impact assessment is to evaluate whether a stressor has changed the environment, which components are adversely affected, and to estimate the magnitude of the effects. The evaluation of impact involves comparative methods. Early approaches to impact assessment involved the use of computer simulation models to predict the impact. Decisions were then made based on the soundness of those predictions. Although the data used to interpret effects are quite varied, the methods for analysis are often quite similar and involve comparison of impact areas with control areas. When information is available prior to the potential impact, the design is often referred to as a
Before–After Control‐impact
(BACI) design. Several variations on the basic design have been proposed and are discussed in this article.
Bioabundance
Authors: Ickstadt Katja
Published: January 2013

Bioabundance is a quantity that describes the number of individuals of a species in an area of interest, either directly or through other measurements such as biomass or percentage of cover. It is the underlying quantity of interest in a number of ecological investigations, such as monitoring population sizes and studying the spatial or space–time pattern of a single plant or animal species in a region or plot. It is also the key ingredient for analyzing biodiversity, the relative abundance of several or all species in an ecological community.
Biodiversity
Authors: Ver Hoef Jay M.
Published: January 2013

Biodiversity is closely related to diversity. However, biodiversity has come to be concerned with the conservation of variation of different levels of biological organization, from genes to populations, communities, ecosystems, and landscapes. Biodiversity ranges across spatial and temporal scales. For the elements of concern (genes to landscapes), biodiversity can be measured as the number of different types of elements, the relative frequencies of the different elements, or the number of different processes such as gene flow or nutrient flow. This article emphasizes methods for conserving biodiversity. Biodiversity is rarely used in a sentence without the word ‘conservation’. When discussing biodiversity, it is assumed that high biodiversity is desirable and should be preserved. The arguments for conserving biodiversity are many and varied, from aesthetic to the stability of our environment to future cures for cancer and other uses of nature's raw biological material that cannot yet be imagined.
Biomass
Authors: Parresol Bernard R.
Published: January 2013

Biomass is the mass or the weight of living tissue provided by a given area or volume of the earth's surface. It is commonly subdivided into five trophic levels forming the basic food chain. In terrestrial ecosystems, the biomass distribution resembles a pyramid, where mass progressively decreases from producer to top predator. Some aquatic systems may have a dipyramid‐shaped biomass distribution, that is, narrow at the bottom and top, and wide in the middle. Plant biomass recycles atmospheric carbon. If we replant harvested biomass, there is no net gain in atmospheric carbon to add to the greenhouse effect. Large‐scale biomass burning, that is, deliberately set fires, is a significant source of carbon dioxide and particles in our atmosphere. Bioenergy is a fuel energy that can be derived directly or indirectly from biological sources. Biomass energy from wood, crop residues (known asbagasse), and dung remains the primary source of energy in developing regions. Satellites scan the normalized difference vegetation index over terrestrial habitats, and scan sea‐surface chlorophyll levels over oceans to estimate global net primary production, which averages about 104.9 billion tonnes C per year. Local biomass resources are determined from broad‐based inventories and statistical predictions.
British Ecological Society
Authors: Norman Hazel
Published: January 2013

The British Ecological Society, established in 1913, is the oldest ecological society in the world. Its vision is to advance ecology and make it count. With a membership of about 4000 spread around the world, its core activities are the publication of the results of research in ecology, the development of scientific meetings, and the promotion of ecological awareness through education and policy initiatives.
Capture‐Recapture Methodology
Authors: Gould William R. , Kendall William L.
Published: January 2013

Capture‐recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user‐friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.
Catchment Hydrology
Authors: Croke B.F.W. , Blakers R.S. , Kelly (Nee Letcher) R.A. , Jakeman A.J.
Published: January 2013

This article examines the role that catchment hydrology plays in modern society: from understanding the behavior of catchments, to providing information for the management of water resources. This is discussed in the context of three classes of hydrological models (empirical, conceptual, and physics‐based), and considers the problems faced by hydrologists: scale, heterogeneity, ungauged catchments, and the impact of change (both land use and climate) on catchment response. This article concludes with discussion on the future directions of catchment hydrology, and the challenges that need to be met.
Center for Statistical Ecology and Environmental Statistics
Authors: Patil G. P.
Published: January 2013

The Center for Statistical Ecology and Environmental Statistics is a unit in the Department of Statistics of the Pennsylvania State University and was initiated with Professor G.P. Patil as its founding director under a cooperative agreement between the US National Oceanic and Atmospheric Administration (NOAA) and the Pennsylvania State University as a formal substitute for the earlier Penn State Program in Statistical Ecology and Environmental Statistics in operation since 1969. The Center is the first of its kind in the nation and in the world, and enjoys a national and international reputation. Broad research areas of the Center relate to statistical ecology, environmental statistics, and quantitative risk analysis with emphasis on mathematical statistics, statistical methodology, and data interpretation and improvement for future use. The adopted approach is to advance statistics for environment, ecology, and environmental health, and to advance environmental and ecological theory and practice using valid statistics.
Change‐Point Methods
Authors: El‐shaarawi Abdel H.
Published: January 2013

This article reviews recent applications of change‐point methods for modeling nonstationarities in environmental data. In particular, maximum likelihood‐based methods for the detection and estimation of parameter changes at unknown times in environmental time series data are emphasized.
Circular Data
Authors: Otieno Bennett Sango , Anderson‐Cook Christine M.
Published: January 2013

Circular data are the simplest case of directional data, which commonly occur in environmental studies when measurements are taken from an orientation or cyclical timing application. Circular data have a single response which is not scalar, but angular or directional. Typical orientation observations are measured by a compass and indicate direction, whereas cyclical timing applications are measured by a clock or calendar. The key characteristic that differentiates circular data from data measured on a linear scale is its wrap‐around nature, with no maximum or minimum. Specific environmental applications that use directional measures include wind direction, plant or animal migration (orientation), as well as timing of meteorological or life cycle events during the day or in the calendar year (cyclical timing). These include long‐axis orientations of fieldspar laths, cross‐bed azimuths of paleocurrents, and orientations of pebbles or rock cores. Also, the repeating nature of time increments, such as days, months, or years, is captured by the wrapping around of the circle. Examples can include time of the daily maximum temperature, or occurrence of hurricanes during the year.
Classification
Authors: Simeonov Vasil D.
Published: January 2013

The aim of a classification procedure for environmental studies is to reveal similarities (or dissimilarities) between groups of objects (e.g., sampling sites or sampling periods), characterized by the values of a set of variables (e.g., chemical or physical parameters, analytes).
Clean Air Acts
Authors: El‐Shaarawi Abdel H.
Published: January 2013

National, provincial, state, or municipal authorities in most developed countries have established legislation or Acts to control air pollution emissions and to protect human health and the general environment. The US and UK Clean Air Acts are briefly summarized in this article.
Climatology
Authors: Szeto Kit K.
Published: January 2013

Climatology is the interdisciplinary study of the earth system that encompasses the atmosphere, hydrosphere, cryosphere, lithosphere, biosphere, and anthrosphere. Modern climatology includes not only these components but also importantly their interactions involving detailed global observing systems and complex computer‐based numerical models. The state of the climate system at any time is determined by the forcings acting upon it and the complex and interlocking internal feedbacks that these forcings prompt. Because of these feedback processes, the climate system does not respond to forcings, including human‐induced ones, in a smooth and gradual way and the response can be rapid and sometimes discontinuous. Climate models, with which we hope to predict future climates, must be able to capture such apparent discontinuities that have been observed in paleoclimatic records. To meet these requirements, modern climate models are composed of multiple interacting modules, which attempts to mimic components of the earth system, so that complicated feedbacks and synergisms in the climate system can be simulated faithfully. Human activities and associated needs, such as food and energy and water resources, are becoming increasingly dependent on, and even an integral part of, the climate system. With increasing evidence of the effects of human activities on the climate system, international bodies were established to coordinate scientific assessments of human influence on climate and to recommend appropriate mitigation and adaptation measures for policy makers.
Coastal Processes
Authors: Prandle David
Published: January 2013

Coastal seas are influenced by dynamical, chemical, biological, and geological processes. The predominant dynamical processes, namely, tides, waves, and density currents are described in this article. Seasonal variations in the latter two components are often important in determining biological and chemical distributions. Computer simulation models are used to link all such processes and predict pathways and concentrations of contaminants.
Community Food Webs
Authors: Deangelis Donald L.
Published: January 2013

Community food webs describe the feeding relationships, or trophic interactions, between the species of an ecological community. Both the structure and dynamics of such webs are the focus of food web research. The topological structures of empirical food webs from many ecosystems have been published on the basis of field studies and they form the foundation for theory concerning the mean number of trophic levels, the mean number of trophic connections versus number of species, and other food web measures, which show consistency across different ecosystems. The dynamics of food webs are influenced by indirect interactions, in which changes in the level of a population in one part of the food web may have indirect effects throughout the web. The mechanisms of these interactions are typically studied microcosm experiments, or sometimes in‐field experiments. The use of mathematical models is also a major approach to understanding the effects of indirect interactions. Both empirical and mathematical studies have revealed important properties of food webs, such as keystone predators and trophic cascades.
Compartmental Analysis
Authors: Becka Michael
Published: January 2013

Ecological, toxicological, and pharmacological research is often concerned with the answer to the question of how a substance is processed within a biological system. The exact knowledge of the corresponding kinetic pattern forms the basis for a useful answer. In order to understand and to characterize kinetic processes, as well as to identify nonlinear kinetics, compartmental analysis yields a useful approach.
Composite Sampling
Authors: Patil G.P.
Published: January 2013

The high costs of laboratory analytical procedures frequently strain environmental and public health budgets. Whether soil, water, or biological tissue is being analyzed, the cost of testing for chemical and pathogenic contaminants can be quite prohibitive. Composite sampling can substantially reduce analytical costs because the number of required analyses is reduced by compositing several samples into one and analyzing the composited sample. By appropriate selection of the composite sample size and retesting of select individual samples, composite sampling may reveal the same information as would otherwise require many more analyses. Many of the limitations of composite sampling have been overcome by recent research, thus providing more widespread potential for the use of composite sampling to reduce costs of environmental and public health assessments, while maintaining and often increasing the precision of sample‐based inference.
Concentration, Ambient
Authors: Hopke Philip K.
Published: January 2013

Data analysis of ambient atmospheric data focuses on the variations in values from the “typical” or average values of the measured variables. To provide a baseline for such studies, the concentrations of the major gaseous constituents of the atmosphere are summarized along with the physical and chemical characteristics of ambient particulate matter.
Control Group
Authors: Greenland Sander
Published: January 2013

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.
Control Theory
Authors: Young Peter C.
Published: January 2013

Control theory is concerned with the mathematical characterization and analysis of deterministic and stochastic dynamic systems for the purpose of identification, estimation and control. It emphasizes the importance of feedback processes, both as an integral aspect of all dynamic systems and as a means of artificially controlling or optimizing the behavior of such systems. In relation to environmetrics, the main importance of control theory relates to the impact that it has had on the analysis of environmental time series and the modeling of environmental systems. In addition, however, its powerful ability to improve our understanding of how dynamic systems behave in feedback terms can have a profound effect on how environmetric models are interpreted in physically meaningful terms.
CorrelatedMultinomialData
Authors: Zhu Yiliang
Published: January 2013

Correlated multinomial data, including correlated binomial, arise from clustered sampling schemes such as grouped sampling or repeated measurements. Correlation induced by clustering can be of interest in its own right, but must be accounted for in statistical analyses to avoid inaccurate or inefficient inference. This article discusses common approaches to the treatment of correlated multinomial data and illustrates dose‐response modeling via generalized estimating equations using an example from developmental toxicity experiment.
Creel Surveys
Authors: Jones Cynthia M.
Published: January 2013

Angler (or creel) surveys are used to measure the impact of recreational fishing on fisheries resources. Survey‐contact methods include mail, telephone, internet, face‐to‐face, access‐point, roving, and aerial. Choice of survey method depends on the type of information needed and the available budget. Most frequently, a combination of survey‐contact methods is used and estimation of quantities such as catch and fishing effort will depend on the survey design. When accurate catch data are necessary, surveys that are conducted on site (access‐point, roving) are preferred because catch can be observed and counted by the survey agent. In contrast, off‐site surveys (mail, telephone, and internet) rely on self‐reported data that require the angler to remember the fishing trip catch and effort accurately. Sampling frames for off‐site surveys include angler‐license lists, telephone directories, or other data containing angler contact information. Sampling frames for on‐site surveys include lists of access sites, geographic maps of water bodies, and calendars. The choice of survey method and design will depend on availability of the appropriate sampling frame, the need for accuracy in catch or effort estimation, timeliness, and cost.
Cross‐Scale Morphology
Authors: Garmestani Ahjond S. , Allen Craig R. , Holling C.S.
Published: January 2013

The scaling of physical, biological, ecological and social phenomena is a major focus of efforts to develop simple representations of complex systems. Much of the attention has been on discovering universal scaling laws that emerge from simple physical and geometric processes. However, there are regular patterns of departures both from those scaling laws and from continuous distributions of attributes of systems. Those departures often demonstrate the development of self‐organized interactions between living systems and physical processes over narrower ranges of scale.
Detection Limits
Authors: Walshaw David
Published: January 2013

In analytical chemistry, the
detection limit
is the lowest level of an analyte that can reliably be detected by a well‐defined operating procedure. It is often confused with the
decision limit
, which is a threshold of measurement used to determine whether or not the analyte is present in a particular study. We discuss the history and confusion relating to the definition in a univariate context. We consider the detection limit as a function of the sources of variation within an operating procedure. Estimation of the detection limit assuming constant variance in one‐level designs and calibration designs is described, as well as a brief treatment of the assumption of non‐constant variance. We outline modifications for multiple future detection decisions. Finally we consider approaches to multivariate detection, when decisions are based on more than one quantitative signal.
Disease Mapping
Authors: Waller Lance A.
Published: January 2013

Maps of disease reveal patterns of incidence and prevalence. Such patterns often suggest possible associations between disease and potential risk factors mapped over the same area. We briefly review the historical use of maps in the study or disease and classify different types of geographic data available (geostatistical, point, and lattice data). For each data type, we outline the analytic methods available and the types of questions the methods can address.
Disease Registry
Authors: Darnell Ross
Published: January 2013

A disease registry defines a process that manages registers, which comprise cases of a particular disease that have occurred in a population. The registry may include demographic information about the cases (e.g., age, gender, and place of residence), dates of disease diagnosis, and perhaps additional information such as dates of death, or exposure and risk factor information. Registers are multipurpose being used to improve patient care, reviewing of patients with chronic illness, public health reporting, surveillance of diseases within a population, planning and provision of health care, and research. There is a tension between the increasing demands for personal autonomy and the need for society to recover as much information as possible to learn how best to control disease. There is a real need for maintaining confidentiality of individual health data and for informed consent before these data are used for research.
Dispersion Parameter
Authors: Piegorsch Walter W.
Published: January 2013

To describe the stochastic nature of an outcome variable, environmetricians use probability distributions. A crucial feature of many simple probability models is that structural relationships may be required between the population mean and other components of the model. Many environmental sampling and experimental settings occur, however, where such a mean/variance structure is too restrictive: the data often exhibit variation larger than or, in some instances, smaller than that required under these simpler models. Such occurrences are known collectively as overdispersion or underdispersion, respectively. We quantify the extent of the over/underdispersion by dedicating a model parameter to it in the variance term. The resultingdispersion parametercan be used to identify, study, test, or otherwise account for the excess variation. This entry reviews statistical aspects of modeling and estimation for such dispersion parameters.
Distance Sampling
Authors: Thomas Len , Buckland Stephen T. , Burnham Kenneth P. , Anderson David R. , Laake Jeffrey L. , Borchers David L. , Strindberg Samantha
Published: January 2013

Distance sampling is a widely used group of closely related methods for estimating the density and/or abundance of biological populations. The main methods areline‐transect samplingandpoint‐transect sampling. In both cases, observer(s) perform a standardized survey along a series of randomly located lines or points, searching for objects of interest (usually animals or clusters of animals). For each object detected, they record the distance from the line or point to the object. Not all objects will be detected, but a fundamental assumption of the basic methods is that all objects that are actually on the line or point are detected. The key to distance sampling analyses is to use the observed distances to fit adetection functionthat describes how detectability decreases with increasing distance from the transect. The fitted function is used to estimate the average probability of detecting an object; from here, one can readily obtain point and interval estimates for the density and abundance of objects in the survey area. Various extensions to the basic methods allow assumptions to be relaxed, and include methods that integrate capture‐recapture and distance sampling, as well as methods to model spatial variation in density.
Diversity Measures
Authors: Solow Andrew R.
Published: January 2013

One way in which the term diversity is used in ecology is to characterize the evenness of the relative abundances of species (or other types) in a community (or other collection of organisms). A variety of measures that have been proposed for this purpose are reviewed.
Diversity Profiles
Authors: Patil G. P.
Published: January 2013

Community diversity, diversity measurement, and diversity comparisons have been important in community ecology studies for more than four decades.
Diversity
is a generic term referring to the condition of being different; a useful synonym for diversity is variety. It summarizes for qualitative characteristics (e.g., tree species) what the variance summarizes for quantitative measurements (e.g., tree diameter). Diversity is looked upon as a community property and, accordingly, the trophic, taxonomic or structural levels that comprise the community must be specifically delimited in making diversity comparisons, it is not uncommon to find that diversity has increased according to one index, but decreased according to a second index. This merely reflects the fact that diversity is a complex multidimensional property of a community. To view diversity through the lens of a single index is to project that multidimensional complexity onto a one‐dimensional ordinal scale. In view of the inadequacy of a single index, it is desirable to quantify diversity by means of
diversity profiles
. A diversity profile is a curve depicting the simultaneous values of a large collection of diversity indices. Thus, the profile portrays the views of diversity from many different vantage points simultaneously. Today in the age of indicators, however, multiple indicators of multidimensional diversity may replace the traditional diversity indices.
DNA
A
dducts
Authors: Thurston Sally W.
Published: January 2013

DNA adducts are DNA‐chemical complexes that can cause DNA mutations which eventually lead to cancer. Adducts are typically formed after exposure to compounds in cigarette smoke, aflatoxins, benzene, or other agents. DNA adducts are considered a biomarker of the biologically effective dose, that is, the amount of the agent or its metabolite that has bound to DNA. Among current smokers, DNA adducts counts in mononuclear blood cells are much larger on average in subjects with lung cancer than in controls. Blood adduct levels are also a reasonable surrogate for adduct levels in the lung. Thus, the number of DNA adducts in blood cells have the potential to be extremely useful for predicting lung cancer risk.
D
ose‐
R
esponse
M
odeling for
C
lustered
D
ata
Authors: Chen James J.
Published: January 2013

Clustered data refer to a set of correlated responses. For example, different animals represent different genetic values inherited from parents that may also be nested within herds or spatial entities. Clustered data also result from study designs, such as repeated observations on the same subject or sampling from correlated subsamples. A great deal of statistical research on dose response modeling of clustered data is devoted to animal reproductive and developmental toxicity studies. In developmental toxicity experiments, chemicals are administered to the dam (female animal), but the observations are made on individual fetuses. The clustering of fetuses within the litters induces the cluster (litter) effect. Modeling the clustered data should account for the correlation among the individual responses within a cluster to draw valid and efficient inferences. Two common approaches for fitting dose response models to clustered data are the likelihood‐based and generalized estimating equations (GEE) (or quasi‐likelihood) approaches.
E
chelon
A
nalysis
Authors: Patil G. P.
Published: January 2013

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
are a method 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.
Environmental and Ecological Statistics
Authors: Patil G.P.
Published: January 2013

The emphasis of
Environmental and Ecological Statistics
is, as its title declares, on statistics, ecology, and the environment. It acts as a forum for multidisciplinary communication and discussion on statistics, ecology, environment, and society.
E
cological
S
ociety of
A
merica
Authors: Porter John H.
Published: January 2013

The Ecological Society of America (ESA) is a 10 000‐member scientific society that focuses on improving communication among ecological scientists and between ecologists and society in general. Membership in the society is open to anyone with an interest in the advancement of ecology. The society has as its goals to (i) promote ecological science by improving communication among ecologists; (ii) raise the public's level of awareness of the importance of ecological science; (iii) increase the resources available for the conduct of ecological science; and (iv) ensure the appropriate use of ecological science in environmental decision making by enhancing communication between the ecological community and policy‐makers. The society achieves these goals through annual meetings, the publication of scientific journals and special publications, supporting regional chapters and topic‐based sections, and operating a public affairs office.
Ecological Statistics
Authors: Smith Eric P.
Published: January 2013

Statistical applications in ecology are numerous and encompass many of the classical and modern methods, as well as some novel methodology. Because of the breadth of the topic, this article focuses on several important methods that are outside the realm of standard statistical texts with application to environmental problems. Some of the methods that are used in statistical ecology are described, along with references to additional material.
Time Series, Ecological
Authors: Solow Andrew R.
Published: January 2013

The most common situation in which time series data are the central object of ecological analysis is in population dynamics/population modeling. LetXtbe the size or density of a population in periodt. A general deterministic model of the dynamics of this population is the first‐order nonlinear difference equation:Xt = Xt−1F(Xt−1) whereFis a nonnegative function.
E
cosystem
Authors: Feist Blake E.
Published: January 2013

The concept of an ecosystem has been around for many decades in the field of ecology. From its humble beginnings as an idea or construct to its current state as a rich and at times all encompassing subdiscipline of ecosystem ecology, the term
ecosystem
took nearly 35 years to be properly defined and another 35 to reach its current status. Ecology is the study of how living things interact with their environment, and it could be argued that community and ecosystem ecology are two general subdisciplines of ecology that address complex ecological systems. While community ecology is not the focus of this article, it is intimately tied to the field of ecosystem ecology in that communities are a component of ecosystems. Ecosystems are complex and dynamic, with clearly defined structure and function, and their components are interdependent and interact with each other. The ecosystem concept lends itself well to the management and conservation of Earth's resources, given the dynamic and complex nature of their interactions, including those with humans. Indeed, the terms
ecosystem‐based management, ecosystem services, ecosystem assessments
, and
whole ecosystem experiments
have become powerful tools for assessing and managing the Earth's resources.
E
cosystem
E
lement
C
ycling
Authors: Mcguire A. David
Published: January 2013

Ecosystem dynamics are changes in the biological and physical characteristics of ecosystems through time. The biological organisms in an ecosystem are responsible for a number of processes that affect ecosystem dynamics. For example, plants obtain carbon as carbon dioxide from the atmosphere through the process of photosynthesis, herbivores obtain carbon by consuming plants in an ecosystem, carnivores obtain carbon by eating animals in an ecosystem, and decomposers obtain carbon from dead organisms in an ecosystem. Physical processes also affect ecosystem dynamics. For example, the leaching of dissolved organic carbon in water flowing through the soil of an ecosystem is one path through which terrestrial ecosystems may lose carbon to aquatic ecosystems like rivers and lakes. In this article, ecosystem element cycling refers to the cycling of elements such as carbon within an ecosystem, as well as the flow of elements into and out of an ecosystem. This article has several purposes: (i) to provide some basic biological and physical background on processes responsible for ecosystem element cycling; (ii) to briefly describe generalized carbon and nitrogen cycles in terrestrial ecosystems, and (iii) to discuss human modification of the global carbon and nitrogen cycles.
Ecotoxicology
Authors: Newman Michael C. , Evans David A.
Published: January 2013

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, for example, individuals, populations, communities, and ecosystems.
Encountered Data
Authors: Smith Eric P.
Published: January 2013

Data that are obtained in ecological and environmental data is often not collected via an experimental or sampling design but rather is observed. Examples include fish that are collected via a net, plants that are observed when walking a transect line and birds heard in a wetland survey. Data arising from these types of studies are sometimes referred to as
encountered data.
Impact, Environmental
Authors: Smith Eric P.
Published: January 2013

Environmental impact refers to the potential or realized effect of a planned or existing project or anthropogenic displacement on the environment. Impact assessment is the analysis of the impact and is an integral part of environmental impact assessment and statements, and the strategic environmental assessment that is an essential component of environmental decision making and policy.
E
nvironmental
J
ustice
Authors: Waller Lance A.
Published: January 2013

Environmental justice refers to the equitable treatment and involvement of all people irrespective of race, ethnicity, income, national origin, or education level with respect to development, enforcement and outcomes of environmental regulations, policy, implementation, exposures, and their consequences. We briefly review the historical development of the environmental justice movement and outline key statistical issues involved.
E
nvironmental
P
rotection
A
gency,
U
.
S
.
Authors: Nussbaum Barry D. , Olsen Anthony R.
Published: January 2013

The U.S. Environmental Protection Agency (EPA) was established in December, 1970, to protect human health and the environment. It was formed by the merger of many scattered federal agencies. Operating under many statutes, it develops and enforces regulations, distributes grants, studies environmental issues, sponsors partnerships with state and local governments, and teaches people about environmental issues and publishes environmental information and data. This article provides a discussion on some history, perspective, organization, and activities at the EPA.
EnvStats, anRPackage forEnvironmentalStatistics
Authors: Millard Steven P.
Published: January 2013

EnvStatsis a comprehensiveRpackage for environmental statistics and is the successor to theS‐PLUSmoduleEnvironmentalStats for S‐PLUS. EnvStatsprovides a set of powerful functions for performing graphical and statistical analyses of environmental data.
E
nvironmetrics, the
J
ournal of the
I
nternational
E
nvironmetric
S
ociety
Authors: Piegorsch Walter W.
Published: January 2013

Environmetrics
is the official journal of The International Environmetrics Society (TIES). It is a multidisciplinary journal that publishes papers on the development and application of quantitative methods in environmental sciences.
Escape Trajectory
Authors: Domenici Paolo
Published: January 2013

Escape responses consist of sudden accelerations as reactions to threatening stimuli and are present in most animals as a means of avoiding predation. Escape responses are currently receiving increased attention as valuable models for animal behavior, ecology, and neurobiology. The path along which an animal moves during an escape response (its escape trajectory) has attracted the interest of ecologists and behaviorists in relation to its functional role in predator–prey interactions. Escape trajectories (ETs) as considered in this article refer to the initial prey response to a predator's attack. Such a trajectory should be measured at the end of the main rotational motion present during the escape response, which usually corresponds to a specific kinematic stage of the animal's locomotion. Beyond this stage, prey may continue escaping along a zigzag path, especially if predators follow up their attack with a chase.
Exact Randomization Technique
Authors: Moir Rob
Published: January 2013

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.
E
xceedance
P
robability
Authors: Drees Holger
Published: January 2013

The probability that a future observation exceeds a high threshold is approximated and estimated using an extreme value approach.
Extra Risk
Authors: West R. Webster
Published: January 2013

To properly quantify the toxic effect of a toxin, the
background risk
of no exposure to the toxin,
R
(0), must first be specified. The excess risk incurred by exposure to a dose,
d
, of the toxin is then viewed as the added risk at this dose relative to the rate of nonadverse responses, 1 − 
R
(0), in the unexposed population.
ExtremalEvents
Authors: Katz Richard W.
Published: January 2013

The term extremal event is commonly used in relation to environmental occurrences that impact greatly on day‐to‐day life, for example, storms and floods. Although it is clear that such events are extremal events, it is not clear, more generally, what an extremal event is, or what an extremal event is not for that matter. We discuss the role of extremal events in extreme value theory and in several application areas so that we may identify any common underlying themes.
Extreme Value Analysis
Authors: Padoan Simone A.
Published: January 2013

Extreme value theory concerns the behavior of the extremes of a process or processes. The fundamentals of this probability theory have been known since about the beginning of the twentieth century, but the relevant statistical methods for modeling extreme values emerged in the literature only in the past three decades. In fact, since 1980 the literature has seen a flood of applications of statistical extreme values, covering a wide range of areas. These application areas include environmental sciences, including climate, engineering and hydrology, performance assessment as in sports or policing, astronomy, finance, chemometrics, mortality studies, and outlier detection. Further references to specific applications are noted throughout this article.

The aim of this article is to review some fundamentals of extreme value theory and the relevant statistical methods. The emphasis will be on the latter and the applications it has attracted in the literature so far. The article is in two parts. The first part considers univariate extremes and the remainder is for multivariate extremes. Each part begins with a discussion of fundamental theoretical results. This is then followed by a discussion of relevant statistical models, inference, and simulation.
Generalized Extreme Value Distribution
Authors: Walshaw David
Published: January 2013

Historically, flood frequency analysis constitutes the prime important example in environmental sciences where annual maxima‐based inference on return levels is the ultimate research goal. Meanwhile other ecological variables such as wind, temperature, air pollution concentration, or the thickness of the ozone layer have also become intensive research topics for extreme value analysis in view of possible negative impacts as a result of extremes.

For these purposes the (generalized) extreme value (GEV) distribution is the basic distributional tool. This is in contrast to most statistical inference, which focuses on central measures of a distribution, and where the normal distribution is the most standard model. We review the GEV model, its mathematical motivation, and the statistical estimation of the parameters under the assumption of independent random sample from the model. Our ultimate aim in this respect is the accurate estimation of return levels. The idea of GEV models for block maxima is extended to allow for (short‐range) dependence and clusters in the data, bringing in the idea of theextremal indexas a measure of the degree of clustering at extreme levels.

Throughout the text a practical example illustrates the application of the GEV method. We finish with a brief discussion of the software which we believe will be the most relevant for some time to come, and the related literature.
Factor Analysis
Authors: Graffelman Jan
Published: January 2013

Factor analysis is a multivariate statistical method for data reduction that originated in psychometrics and has found applications in many branches of science. The method aims to describe the correlation structure between a large set of observed variables in terms of a few underlying latent variables called factors. Factor analysis employs a specific model, where observed variables are modelled as linear combinations of common factors plus a specific error term. This model can be estimated by using principal components, by using the iterative principal factor method, or by maximum likelihood. After estimation, factors may be rotated in order to improve their interpretation. An example of the application of factor analysis to a set of pollutants in an environmental monitoring study is discussed.