bluuebunny/crossref_metadata_2025_split huggingface dataset:
Time Series, Ecological
Authors: Solow Andrew R. 
Published: January 2013

AbstractThe 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

Abstract

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

Abstract
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.
E
nvironmental
J
ustice
Authors: Waller Lance A. 
Published: January 2013

Abstract
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

Abstract
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.
Escape Trajectory
Authors: Domenici Paolo 
Published: January 2013

AbstractEscape 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

Abstract

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.
Extra Risk
Authors: West R. Webster 
Published: January 2013

Abstract

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

AbstractThe 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

AbstractExtreme 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

AbstractHistorically, 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

Abstract
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.
Environmental Forensics
Authors: Johnson Glenn W. 
Published: January 2013

AbstractEnvironmental forensics is the scientific evaluation of environmental data for the purposes of evaluation of the history and sources of environmental contamination. Forensics investigations are often conducted in legal rather than purely academic context. Scientific methods that may be used in such studies are large and diverse: limited only by relevance to the problem at hand, and the degree to which the method has proved reliable and has been accepted within the scientific community. Several common data analysis methods that have seen extensive use in forensic studies are principal components analysis, receptor models, and simple graphical displays such as concentration maps.
Generalized Linear Models
Authors: Jørgensen Bent 
Published: January 2013

AbstractGeneralized linear models provide a general framework for handling regression modeling for normal and non‐normal data, including multiple linear regression, ANOVA, logistic regression, Poisson regression and log‐linear models for contingency tables. All the major statistical packages include facilities for fitting generalized linear models. A generalized linear model is defined by choosing a link function and a variance function, along with choosing a response variable and a set of explanatory variables. The link function transforms the mean of the response variable to a scale where the model is linear. The variance function describes how the variance behaves as a function of the mean. Each choice of variance function corresponds to a certain deviance function, and model fitting is accomplished by minimizing the deviance, generalizing least squares fitting. Inference on parameters and hypothesis testing is performed by means of analysis of deviance, generalizing the classical ANOVA method. Estimation and analysis of deviance are based on quasi‐likelihood methods, requiring only second‐moment assumptions, thereby providing a certain robustness against misspecification of the probability model. The choice of link and variance functions may be checked by means of residual analysis.
Geographic Information Systems (GIS), Spatial Statistics In
Authors: Cressie Noel , Liu Desheng 
Published: January 2013

AbstractA Geographic Information System (GIS) is a networked collection of hardware and software tools that recognizes georeferencing in the data and features the georeferencing in database management, data analysis, and visualization of results (principally maps) from the analysis. This combination of geography and computer science has been known as geographic information science. Spatial statistics in GIS has grown in importance, however, spatial databases in a GIS can be very large. It may be that, without some form of dimension reduction, only the most simple statistical methodologies will scale up.
Global Ecology
Authors: Lerdau Manuel 
Published: January 2013

Abstract
Global ecology began with Joseph Priestley'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.
Global Warming
Authors: North Gerald R. 
Published: January 2013

Abstract
Global warming refers to observation that the earth has been warming over the past century and the related theory that humans are responsible for the changes in global climate. The estimates of the warming are based on a global network of instrumental observations that the global average temperature of the planet has been increasing at an average rate of about 0.7 ± 0.2 °C per century over the last century. Indicators based upon paleoclimatic information stretching over the last several hundred thousand years suggest that this rate of warming is highly unusual, and not likely to be part of a pattern of natural variability internal to the system. Besides the temperature record, there are numerous other indicators of secular change in the planetary climate. A few of these include retreat of mountain glaciers, rise of sea level, melting of permafrost, reduction of sea ice, increases in heavy precipitation events, changes in growing season, as well as many others.
The cause of such a warming is now rather well established. While we do not have complete enough information on all aspects of the climate system, we do have excellent coverage of a number of the relevant factors since the 1970s – the beginning of the satellite era. During this last few decades, we have not only accurate estimates of surface temperatures, but good observations of many aspects of the system including potential perturbing causes of change to the system such as the brightness of the sun and the concentrations of trace gases that can cause warming. In this article, the case will be made that the warming is real and that we have a good theory for why it is happening.
Habitat Survey and Sampling Designs
Authors: Gould William R. 
Published: January 2013

AbstractHabitat measurements will always be an important component of ecological studies. Traditionally, researchers have used methods applied to relatively small areas using either plot‐based or plotless methods. Variables such as percent cover, density, and biomass are commonly used together as a means of quantifying habitat in a particular area. The efficacy of habitat measurements depends on observer effects, vegetation form, and spatial pattern, and the scale at which measurements are made. In all cases, choice of variables and measurement techniques directly impact accuracy of results and must be carefully considered prior to data collection. Regardless of technique, random sampling strategies such as simple or stratified designs are essential for valid statistical inference. Recent advances in satellite and radar technology have resulted in a myriad of additional methods for collecting and analyzing habitat data. Such technology has also altered the scale and types of questions being asked. However, these technological advances are not without error and still require careful use and in many cases, ground‐truthing.
Healthy Worker Effect
Authors: Eisen Ellen A. , Picciotto Sally , Robins James M. 
Published: January 2013

Abstract
Epidemiologic studies of occupationally exposed cohorts are useful in identifying and quantifying environmental risks because workers are generally exposed to higher levels of toxic materials than the general population. Although higher exposures make it easier to detect and characterize modest elevations in risk, such studies are plagued by a particularly pervasive form of selection bias, referred to as the healthy worker effect (HWE). The HWE is reflected in better health status of exposed workers relative to the general population. This bias arises from two sources: (i) workers were initially healthy enough to be hired, whereas the general population includes persons unfit for work, and (ii) workers who stay healthy (survivors) remain exposed, whereas less healthy coworkers reduce exposure via time off work, job transfer, or early termination. Unlike standard methods, G‐estimation has been shown to reduce healthy worker survivor bias.
Hierarchy Theory, Ecological
Authors: Allen Timothy F.H. 
Published: January 2013

Abstract
Hierarchy theory looks at and announces the decisions of the observer of complex systems. It deals with the first compression down to the universe in which is the second compression that translates experience into models. It does not predict, but rather organizes the arena in which normal science does predict. Bio‐social hierarchies are richer than physical hierarchies because coding stabilizes more levels. Hierarchies put part/whole dual structures, holons, at particular levels that are ordered on five principles, in three basic hierarchical types. Hierarchies describe emergence. Hierarchy theory is robust to realism which looks for ontologically real hierarchies, or constuctivist philosophies that are agnostic as to a real material external world. It can also tolerate anti‐realist philosophies that assert that hierarchies are only human constructions.
Hormesis
Authors: Calabrese Edward J. 
Published: January 2013

Abstract

This article provides a general description of the hormesis dose–response model. Hormetic dose–responses have become reported more frequently in the literature with advances in measuring chemicals at progressively lower doses and with the extensive use of
in vitro
methods, which permits an evaluation of more doses/concentrations that has been typically used in
in vivo
studies. It is expected that the hormesis concept will play a progressively more significant role in the hazard assessment process and in drug discovery and development in forthcoming years.
Impact Assessment: Assessing a Local Biological Effect With Before and After Data
Authors: Stewart‐oaten Allan 
Published: January 2013

AbstractThe design and analysis of monitoring studies to assess chronic biological effects of anthropogenic environmental change when data can be gathered before the change are discussed. Intervention Analysis compares Before and After time series at an Impact site. A special case, sometimes useful when the anticipated effects are “local,” is Before‐After, Control‐Impact (BACI), using comparison sites as covariates to reduce extraneous variance and serial correlation. Both sampling error and natural temporal processes cause uncertainty in inferences: both must be modeled. The models are themselves uncertain. The Impact site is not randomly selected, so these are observational studies, not experiments. Whether and how the change caused the “effects” must be based on their timing and on studies of mechanisms.
Inhalation Toxicology
Authors: Sen Pranab K. 
Published: January 2013

AbstractInhalation toxicology relates to the composite assemblage of ambient toxins with respect to their prevalence, uptake sites, and intake process by inhalation, mode of biological, molecular, and carcinogenic reactions, and consequential health hazards. From a statistical perspective, the major task is to arouse our awareness of potential and asserted toxic substances, to gather scientific evidence of their impact on human life and on our ecosystem as a whole, and to appraise (statistically as well as epidemiologically) the risk due to the aggregation of such toxic and carcinogenic (overt or not) effects of our own bioenvironment. This risk assessment has emerged as an interdisciplinary one, where toxicology, molecular biology, pharmacology, epidemiology, and environmental health sciences all have major shares; nevertheless, statistics plays a key role in this crucial assessment task.
I
nternational
B
iometric
S
ociety
Authors: Billard Lynne 
Published: January 2013

Abstract

The International Biometric Society (IBS) plays a leading role in the advancement of biometry, biostatistics, and statistics at the international level by fostering the exchange of new ideas and relevant methodologies for a wide range of separate disciplines, including the important areas of environmental biology and ecology. This article briefly reviews the formation and structure of the IBS, and provides an historical record of its international leadership and editors of its journals
Biometrics
and
JABES
.