Statistical Ecology


Book Description

Covering a wide range of disciplines, this book explains the formulae, techniques, and methods used in field ecology. By providing an awareness of the statistical foundation for existing methods, the book will make biologists more aware of the strengths and possible weaknesses of procedures employed, and statisticians more appreciative of the needs of the field ecologist. Unique to this book is a focus on ecological data for single-species populations, from sampling through modeling. Examples come from real situations in pest management, forestry, wildlife biology, plant protection, and environmental studies, as well as from classical ecology. All those using this book will acquire a strong foundation in the statistical methods of modern ecological research. This textbook is for late undergraduate and graduate students, and for professionals.




WHO global air quality guidelines


Book Description

The main objective of these updated global guidelines is to offer health-based air quality guideline levels, expressed as long-term or short-term concentrations for six key air pollutants: PM2.5, PM10, ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide. In addition, the guidelines provide interim targets to guide reduction efforts of these pollutants, as well as good practice statements for the management of certain types of PM (i.e., black carbon/elemental carbon, ultrafine particles, particles originating from sand and duststorms). These guidelines are not legally binding standards; however, they provide WHO Member States with an evidence-informed tool, which they can use to inform legislation and policy. Ultimately, the goal of these guidelines is to help reduce levels of air pollutants in order to decrease the enormous health burden resulting from the exposure to air pollution worldwide.




Using R for Modelling and Quantitative Methods in Fisheries


Book Description

Using R for Modelling and Quantitative Methods in Fisheries has evolved and been adapted from an earlier book by the same author and provides a detailed introduction to analytical methods commonly used by fishery scientists, ecologists, and advanced students using the open-source software R as a programming tool. Some knowledge of R is assumed, as this is a book about using R, but an introduction to the development and working of functions, and how one can explore the contents of R functions and packages, is provided. The example analyses proceed step-by-step using code listed in the book and from the book’s companion R package, MQMF, available from GitHub and the standard archive, CRAN. The examples are designed to be simple to modify so the reader can quickly adapt the methods described to use with their own data. A primary aim of the book is to be a useful resource to natural resource practitioners and students. Featured Chapters: Model Parameter Estimation provides a detailed explanation of the requirements and steps involved in fitting models to data, using R and, mainly, maximum likelihood methods. On Uncertainty uses R to implement bootstrapping, likelihood profiles, asymptotic errors, and Bayesian posteriors to characterize any uncertainty in an analysis. The use of the Monte Carlo Markov Chain methodology is examined in some detail. Surplus Production Models applies all the methods examined in the earlier parts of the book to conducting a stock assessment. This included fitting alternative models to the available data, characterizing the uncertainty in different ways, and projecting the optimum models forward in time as the basis for providing useful management advice.




Ecological Informatics


Book Description

Ecological Informatics is defined as the design and application of computational techniques for ecological analysis, synthesis, forecasting and management. The book provides an introduction to the scope, concepts and techniques of this newly emerging discipline. It illustrates numerous applications of Ecological Informatics for stream systems, river systems, freshwater lakes and marine systems as well as image recognition at micro and macro scale. Case studies focus on applications of artificial neural networks, genetic algorithms, fuzzy logic and adaptive agents to current ecological management issues such as toxic algal blooms, eutrophication, habitat degradation, conservation of biodiversity and sustainable fishery.




Applications of Spatial Statistics


Book Description

Spatial statistics has been widely used in many environmental studies. This book is a collection of recent studies on applying spatial statistics in subjects such as demography, transportation, precision agriculture and ecology. Different subjects require different aspects of spatial statistics. In addition to quantitative statements from statistics and tests, visualization in forms of maps, drawings, and images are provided to illustrate the relationship between data and locations. This book will be valuable to researchers who are interested in applying statistics to spatial data, as well as graduate students who know statistics and want to explore how it can be applied to spatial data. With the processing part being simplified to several mouse clicks by commercial software, one should pay more attention to justification of using spatial statistics, as well as interpretation and assessment of the results. GIScience proves to be a useful tool in visualization of spatial data, and such useful technology should be utilized, as part, for the interpretation and assessment of the results.




Statistical Methods for Trend Detection and Analysis in the Environmental Sciences


Book Description

The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.




Analyzing Environmental Data


Book Description

Environmental statistics is a rapidly growing field, supported by advances in digital computing power, automated data collection systems, and interactive, linkable Internet software. Concerns over public and ecological health and the continuing need to support environmental policy-making and regulation have driven a concurrent explosion in environmental data analysis. This textbook is designed to address the need for trained professionals in this area. The book is based on a course which the authors have taught for many years, and prepares students for careers in environmental analysis centered on statistics and allied quantitative methods of data evaluation. The text extends beyond the introductory level, allowing students and environmental science practitioners to develop the expertise to design and perform sophisticated environmental data analyses. In particular, it: Provides a coherent introduction to intermediate and advanced methods for modeling and analyzing environmental data. Takes a data-oriented approach to describing the various methods. Illustrates the methods with real-world examples Features extensive exercises, enabling use as a course text. Includes examples of SAS computer code for implementation of the statistical methods. Connects to a Web site featuring solutions to exercises, extra computer code, and additional material. Serves as an overview of methods for analyzing environmental data, enabling use as a reference text for environmental science professionals. Graduate students of statistics studying environmental data analysis will find this invaluable as will practicing data analysts and environmental scientists including specialists in atmospheric science, biology and biomedicine, chemistry, ecology, environmental health, geography, and geology.




Statistical Data Analysis Explained


Book Description

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis. Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.




Statistics for Censored Environmental Data Using Minitab and R


Book Description

Praise for the First Edition " . . . an excellent addition to an upper-level undergraduate course on environmental statistics, and . . . a 'must-have' desk reference for environmental practitioners dealing with censored datasets." —Vadose Zone Journal Statistics for Censored Environmental Data Using Minitab® and R, Second Edition introduces and explains methods for analyzing and interpreting censored data in the environmental sciences. Adapting survival analysis techniques from other fields, the book translates well-established methods from other disciplines into new solutions for environmental studies. This new edition applies methods of survival analysis, including methods for interval-censored data to the interpretation of low-level contaminants in environmental sciences and occupational health. Now incorporating the freely available R software as well as Minitab® into the discussed analyses, the book features newly developed and updated material including: A new chapter on multivariate methods for censored data Use of interval-censored methods for treating true nondetects as lower than and separate from values between the detection and quantitation limits ("remarked data") A section on summing data with nondetects A newly written introduction that discusses invasive data, showing why substitution methods fail Expanded coverage of graphical methods for censored data The author writes in a style that focuses on applications rather than derivations, with chapters organized by key objectives such as computing intervals, comparing groups, and correlation. Examples accompany each procedure, utilizing real-world data that can be analyzed using the Minitab® and R software macros available on the book's related website, and extensive references direct readers to authoritative literature from the environmental sciences. Statistics for Censored Environmental Data Using Minitab® and R, Second Edition is an excellent book for courses on environmental statistics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for??environmental professionals, biologists, and ecologists who focus on the water sciences, air quality, and soil science.




Urban Meteorology


Book Description

According to the United Nations, three out of five people will be living in cities worldwide by the year 2030. The United States continues to experience urbanization with its vast urban corridors on the east and west coasts. Although urban weather is driven by large synoptic and meso-scale features, weather events unique to the urban environment arise from the characteristics of the typical urban setting, such as large areas covered by buildings of a variety of heights; paved streets and parking areas; means to supply electricity, natural gas, water, and raw materials; and generation of waste heat and materials. Urban Meteorology: Forecasting, Monitoring, and Meeting Users' Needs is based largely on the information provided at a Board on Atmospheric Sciences and Climate community workshop. This book describes the needs for end user communities, focusing in particular on needs that are not being met by current urban-level forecasting and monitoring. Urban Meteorology also describes current and emerging meteorological forecasting and monitoring capabilities that have had and will likely have the most impact on urban areas, some of which are not being utilized by the relevant end user communities. Urban Meteorology explains that users of urban meteorological information need high-quality information available in a wide variety of formats that foster its use and within time constraints set by users' decision processes. By advancing the science and technology related to urban meteorology with input from key end user communities, urban meteorologists can better meet the needs of diverse end users. To continue the advancement within the field of urban meteorology, there are both short-term needs-which might be addressed with small investments but promise large, quick returns-as well as future challenges that could require significant efforts and investments.