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Sampling Strategies For Natural Resources And The Environment

Author: Timothy G. Gregoire
Publisher: CRC Press
ISBN: 1584883707
Size: 29.84 MB
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Written by renowned experts in the field, Sampling Strategies for Natural Resources and the Environment covers the sampling techniques used in ecology, forestry, environmental science, and natural resources. The book presents methods to estimate aggregate characteristics on a per unit area basis as well as on an elemental basis. In addition to common sampling designs such as simple random sampling and list sampling, the authors explore more specialized designs for sampling vegetation, including randomized branch sampling and 3P sampling. One of the book's unique features is the emphasis on areal sampling designs, including plot/quadrat sampling, Bitterlich sampling, line intersect sampling, and several lesser known designs. The book also provides comprehensive solutions to the problem of edge effect. Another distinguishing aspect is the inclusion of sampling designs for continuums, focusing on the methods of Monte Carlo integration. By presenting a conceptual understanding of each sampling design and estimation procedure as well as mathematical derivations and proofs in the chapter appendices, this text promotes a deep understanding of the underpinnings of sampling theory, estimation, and inference. Moreover, it will help you reliably sample natural populations and continuums.

Sampling Techniques For Forest Inventories

Author: Daniel Mandallaz
Publisher: CRC Press
ISBN: 9781584889779
Size: 80.91 MB
Format: PDF, ePub
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Sound forest management planning requires cost-efficient approaches to optimally utilize given resources. Emphasizing the mathematical and statistical features of forest sampling to assess classical dendrometrical quantities, Sampling Techniques for Forest Inventories presents the statistical concepts and tools needed to conduct a modern forest inventory. The book first examines design-based survey sampling and inference for finite populations, covering inclusion probabilities and the Horvitz–Thompson estimator, followed by more advanced topics, including three-stage element sampling and the model-assisted estimation procedure. The author then develops the infinite population model/Monte Carlo approach for both simple and complex sampling schemes. He also uses a case study to reveal a variety of estimation procedures, relies on anticipated variance to tackle optimal design for forest inventories, and validates the resulting optimal schemes with data from the Swiss National Forest Inventory. The last chapters outline facts pertaining to the estimation of growth and introduce transect sampling based on the stereological approach. Containing many recent developments available for the first time in book form, this concise and up-to-date work provides the necessary theoretical and practical foundation to analyze and design forest inventories.

Statistical Geoinformatics For Human Environment Interface

Author: Wayne L. Myers
Publisher: CRC Press
ISBN: 1420082876
Size: 70.37 MB
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Statistical Geoinformatics for Human Environment Interface presents two paradigms for studying both space and interface with regard to human/environment: localization and multiple indicators. The first approach localizes thematic targets by treating space as a pattern of vicinities, with the pattern being a square grid and the placement of vicinities centrically referenced. The second approach explores human/environment interface as an abstraction through indicators, neutralizing the common conundrum of how to reconcile disparate spatial structures such as points, lines, and polygons. These paired paradigms enable: The capacity to cope with complexity Systematic surveillance Visualization and communication Preliminary prioritization Coupling of GIS and statistical software Avenues for automation Illustrating the interdisciplinary nature of geoinformatics, this book offers a novel approach to the spatial analysis of human influences and environmental resources. It includes practical strategies for statistical and spatial analysis.

Introduction To Hierarchical Bayesian Modeling For Ecological Data

Author: Eric Parent
Publisher: CRC Press
ISBN: 1584889209
Size: 19.31 MB
Format: PDF, Kindle
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Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It also helps readers get started on building their own statistical models. The text begins with simple models that progressively become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the authors gradually present the concepts and techniques of the Bayesian paradigm from a practical point of view using real case studies. They emphasize how hierarchical Bayesian modeling supports multidimensional models involving complex interactions between parameters and latent variables. Data sets, exercises, and R and WinBUGS codes are available on the authors’ website. This book shows how Bayesian statistical modeling provides an intuitive way to organize data, test ideas, investigate competing hypotheses, and assess degrees of confidence of predictions. It also illustrates how conditional reasoning can dismantle a complex reality into more understandable pieces. As conditional reasoning is intimately linked with Bayesian thinking, considering hierarchical models within the Bayesian setting offers a unified and coherent framework for modeling, estimation, and prediction.

Introduction To Ecological Sampling

Author: Bryan F.J. Manly
Publisher: CRC Press
ISBN: 1466555149
Size: 80.27 MB
Format: PDF, ePub
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An Easy-to-Understand Treatment of Ecological Sampling Methods and Data Analysis Including only the necessary mathematical derivations, Introduction to Ecological Sampling shows how to use sampling procedures for ecological and environmental studies. It incorporates both traditional sampling methods and recent developments in environmental and ecological sampling methods. After an introduction, the book presents standard sampling methods and analyses. Subsequent chapters delve into specialized topics written by well-known researchers. These chapters cover adaptive sampling methods, line transect sampling, removal and change-in-ratio methods, plotless sampling, mark-recapture sampling of closed and open populations, occupancy models, sampling designs for environmental modeling, and trend analysis. The book explains the methods as simply as possible, keeping equations and their derivations to a minimum. It provides references to important, more advanced sampling methods and analyses. It also directs readers to computer programs that can be used to perform the analyses. Accessible to biologists, the text only assumes a basic knowledge of statistical methods. It is suitable for an introductory course on methods for collecting and analyzing ecological and environmental data.

Handbook Of Environmental And Ecological Statistics

Author: Alan E. Gelfand
Publisher: CRC Press
ISBN: 9781498752022
Size: 60.38 MB
Format: PDF, ePub
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This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science. About the Editors: Alan E. Gelfand is the James B. Duke Professor of Statistical Science at Duke University. He is a leader in Bayesian spatial modeling and analysis including a successful book in this area with Banerjee and Carlin. Montse Fuentes is the Dean of the Virginia Commonwealth University College of Humanities and Sciences and a Professor of Statistics. She leads a broad research program in statistical methods for spatial large scale environmental health studies. Jennifer A. Hoeting is Professor of Statistics at Colorado State University. Her research is focused on Bayesian, computational, and spatial statistics applied to address challenging problems in ecology. Richard L. Smith is the Mark L. Reed III Distinguished Professor of Statistics and Professor of Biostatistics at the University of North Carolina. His research covers theoretical and applied aspects of environmental statistics including extreme value theory, spatial statistics and applications to climate change, air pollution and health.

Environmental And Ecological Statistics With R Second Edition

Author: Song S. Qian
Publisher: CRC Press
ISBN: 1498728731
Size: 76.11 MB
Format: PDF, ePub
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Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R, Second Edition, connects applied statistics to the environmental and ecological fields. Using examples from published works in the ecological and environmental literature, the book explains the approach to solving a statistical problem, covering model specification, parameter estimation, and model evaluation. It includes many examples to illustrate the statistical methods and presents R code for their implementation. The emphasis is on model interpretation and assessment, and using several core examples throughout the book, the author illustrates the iterative nature of statistical inference. The book starts with a description of commonly used statistical assumptions and exploratory data analysis tools for the verification of these assumptions. It then focuses on the process of building suitable statistical models, including linear and nonlinear models, classification and regression trees, generalized linear models, and multilevel models. It also discusses the use of simulation for model checking, and provides tools for a critical assessment of the developed models. The second edition also includes a complete critique of a threshold model. Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical model.

The R Book

Author: Michael J. Crawley
Publisher: John Wiley & Sons
ISBN: 1118448960
Size: 31.60 MB
Format: PDF, ePub, Mobi
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Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)