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Hierarchical Modeling And Inference In Ecology

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Hierarchical Modeling and Inference in Ecology

Hierarchical Modeling and Inference in Ecology Book
Author : J. Andrew Royle,Robert M. Dorazio
Publisher : Elsevier
Release : 2008-10-15
ISBN : 0080559255
Language : En, Es, Fr & De

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Book Description :

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics * Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) * Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis * Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS * Computing support in technical appendices in an online companion web site

Applied Hierarchical Modeling in Ecology Analysis of Distribution Abundance and Species Richness in R and BUGS

Applied Hierarchical Modeling in Ecology  Analysis of Distribution  Abundance and Species Richness in R and BUGS Book
Author : Marc Kery,J. Andrew Royle
Publisher : Academic Press
Release : 2020-10-10
ISBN : 0128097272
Language : En, Es, Fr & De

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Book Description :

Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS, Volume Two: Dynamic and Advanced Models provides a synthesis of the state-of-the-art in hierarchical models for plant and animal distribution, also focusing on the complex and more advanced models currently available. The book explains all procedures in the context of hierarchical models that represent a unified approach to ecological research, thus taking the reader from design, through data collection, and into analyses using a very powerful way of synthesizing data. Makes ecological modeling accessible for people who are struggling to use complex or advanced modeling programs Synthesizes current ecological models and explains how they are inter-connected Contains examples throughout the book, walking the reading through scenarios with both real and simulated data Presents an ideal resource for ecologists working in R, an open source version of S known for its exceptional ecology analyses, and in BUGS for more flexible Bayesian analyses

Models of the Ecological Hierarchy

Models of the Ecological Hierarchy Book
Author : Anonim
Publisher : Newnes
Release : 2012-12-31
ISBN : 0444594051
Language : En, Es, Fr & De

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Book Description :

In the application of statistics to ecological inference problems, hierarchical models combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are applied in this book to a wide range of problems ranging from the molecular level, through populations, ecosystems, landscapes, networks, through to the global ecosphere. Provides an excellent introduction to modelling Collects together in one source a wide range of modelling techniques Covers a wide range of topics, from the molecular level to the global ecosphere

Introduction to Hierarchical Bayesian Modeling for Ecological Data

Introduction to Hierarchical Bayesian Modeling for Ecological Data Book
Author : Eric Parent,Etienne Rivot
Publisher : CRC Press
Release : 2012-08-21
ISBN : 1584889195
Language : En, Es, Fr & De

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Book Description :

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.

Bayesian Inference

Bayesian Inference Book
Author : William A Link,Richard J Barker
Publisher : Academic Press
Release : 2009-08-07
ISBN : 0080889808
Language : En, Es, Fr & De

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Book Description :

This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context. The advent of fast personal computers and easily available software has simplified the use of Bayesian and hierarchical models . One obstacle remains for ecologists and wildlife biologists, namely the near absence of Bayesian texts written specifically for them. The book includes many relevant examples, is supported by software and examples on a companion website and will become an essential grounding in this approach for students and research ecologists. Engagingly written text specifically designed to demystify a complex subject Examples drawn from ecology and wildlife research An essential grounding for graduate and research ecologists in the increasingly prevalent Bayesian approach to inference Companion website with analytical software and examples Leading authors with world-class reputations in ecology and biostatistics

Occupancy Estimation and Modeling

Occupancy Estimation and Modeling Book
Author : Darryl I. MacKenzie,James D. Nichols,J. Andrew Royle,Kenneth H. Pollock,Larissa Bailey,James E. Hines
Publisher : Elsevier
Release : 2017-11-17
ISBN : 0124072453
Language : En, Es, Fr & De

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Book Description :

Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition, provides a synthesis of model-based approaches for analyzing presence-absence data, allowing for imperfect detection. Beginning from the relatively simple case of estimating the proportion of area or sampling units occupied at the time of surveying, the authors describe a wide variety of extensions that have been developed since the early 2000s. This provides an improved insight about species and community ecology, including, detection heterogeneity; correlated detections; spatial autocorrelation; multiple states or classes of occupancy; changes in occupancy over time; species co-occurrence; community-level modeling, and more. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition has been greatly expanded and detail is provided regarding the estimation methods and examples of their application are given. Important study design recommendations are also covered to give a well rounded view of modeling. Provides authoritative insights into the latest in occupancy modeling Examines the latest methods in analyzing detection/no detection data surveys Addresses critical issues of imperfect detectability and its effects on species occurrence estimation Discusses important study design considerations such as defining sample units, sample size determination and optimal effort allocation

Hierarchical Modelling for the Environmental Sciences

Hierarchical Modelling for the Environmental Sciences Book
Author : James S. Clark,Alan E. Gelfand
Publisher : OUP Oxford
Release : 2006-05-04
ISBN : 9780191513848
Language : En, Es, Fr & De

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Book Description :

New statistical tools are changing the ways in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirement for a clear exposition of the methodology through to application for a range of environmental challenges.

Decision Making in Natural Resource Management

Decision Making in Natural Resource Management Book
Author : Michael J. Conroy,James T. Peterson
Publisher : John Wiley & Sons
Release : 2013-01-03
ISBN : 1118506235
Language : En, Es, Fr & De

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Book Description :

This book is intended for use by natural resource managers andscientists, and students in the fields of natural resourcemanagement, ecology, and conservation biology, who are confrontedwith complex and difficult decision making problems. The book takesreaders through the process of developing a structured approach todecision making, by firstly deconstructing decisions into componentparts, which are each fully analyzed and then reassembled to form aworking decision model. The book integrates common-senseideas about problem definitions, such as the need for decisions tobe driven by explicit objectives, with sophisticated approaches formodeling decision influence and incorporating feedback frommonitoring programs into decision making via adaptive management.Numerous worked examples are provided for illustration, along withdetailed case studies illustrating the authors’ experience inapplying structured approaches. There is also a series of detailedtechnical appendices. An accompanying website providescomputer code and data used in the worked examples. Additional resources for this book can be foundat: ahref="http://www.wiley.com/go/conroy/naturalresourcemanagement"www.wiley.com/go/conroy/naturalresourcemanagement/a.

Quantitative Genetics in the Wild

Quantitative Genetics in the Wild Book
Author : Anne Charmantier,Dany Garant,Loeske E. B. Kruuk
Publisher : OUP Oxford
Release : 2014-04-03
ISBN : 0191655961
Language : En, Es, Fr & De

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Book Description :

Although the field of quantitative genetics - the study of the genetic basis of variation in quantitative characteristics such as body size, or reproductive success - is almost 100 years old, its application to the study of evolutionary processes in wild populations has expanded greatly over the last few decades. During this time, the use of 'wild quantitative genetics' has provided insights into a range of important questions in evolutionary ecology, ranging from studies conducting research in well-established fields such as life-history theory, behavioural ecology and sexual selection, to others addressing relatively new issues such as populations' responses to climate change or the process of senescence in natural environments. Across these fields, there is increasing appreciation of the need to quantify the genetic - rather than just the phenotypic - basis and diversity of key traits, the genetic basis of the associations between traits, and the interaction between these genetic effects and the environment. This research activity has been fuelled by methodological advances in both molecular genetics and statistics, as well as by exciting results emerging from laboratory studies of evolutionary quantitative genetics, and the increasing availability of suitable long-term datasets collected in natural populations, especially in animals. Quantitative Genetics in the Wild is the first book to synthesize the current level of knowledge in this exciting and rapidly-expanding area. This comprehensive volume also offers exciting perspectives for future studies in emerging areas, including the application of quantitative genetics to plants or arthropods, unraveling the molecular basis of variation in quantitative traits, or estimating non-additive genetic variance. Since this book deals with many fundamental questions in evolutionary ecology, it should be of interest to graduate, post-graduate students, and academics from a wide array of fields such as animal behaviour, ecology, evolution, and genetics.

Spatial Capture Recapture

Spatial Capture Recapture Book
Author : J. Andrew Royle,Richard B. Chandler,Rahel Sollmann,Beth Gardner
Publisher : Academic Press
Release : 2013-08-27
ISBN : 012407152X
Language : En, Es, Fr & De

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Book Description :

Spatial Capture-Recapture provides a comprehensive how-to manual with detailed examples of spatial capture-recapture models based on current technology and knowledge. Spatial Capture-Recapture provides you with an extensive step-by-step analysis of many data sets using different software implementations. The authors' approach is practical – it embraces Bayesian and classical inference strategies to give the reader different options to get the job done. In addition, Spatial Capture-Recapture provides data sets, sample code and computing scripts in an R package. Comprehensive reference on revolutionary new methods in ecology makes this the first and only book on the topic Every methodological element has a detailed worked example with a code template, allowing you to learn by example Includes an R package that contains all computer code and data sets on companion website

Bayesian Disease Mapping

Bayesian Disease Mapping Book
Author : Andrew B. Lawson
Publisher : CRC Press
Release : 2008-08-05
ISBN : 9781584888413
Language : En, Es, Fr & De

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Book Description :

Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology provides an overview of the main areas of Bayesian hierarchical modeling and its application to the geographical analysis of disease. The book explores a range of topics in Bayesian inference and

Bayesian Models

Bayesian Models Book
Author : N. Thompson Hobbs,Mevin B. Hooten
Publisher : Princeton University Press
Release : 2015-08-04
ISBN : 0691159289
Language : En, Es, Fr & De

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Book Description :

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management. Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticians Covers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and more Deemphasizes computer coding in favor of basic principles Explains how to write out properly factored statistical expressions representing Bayesian models

Community Ecology

Community Ecology Book
Author : Anonim
Publisher : Unknown
Release : 2008
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Community Ecology book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Hierarchical Modeling and Analysis for Spatial Data Second Edition

Hierarchical Modeling and Analysis for Spatial Data  Second Edition Book
Author : Sudipto Banerjee,Bradley P. Carlin,Alan E. Gelfand
Publisher : CRC Press
Release : 2014-09-12
ISBN : 1439819181
Language : En, Es, Fr & De

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Book Description :

Keep Up to Date with the Evolving Landscape of Space and Space-Time Data Analysis and Modeling Since the publication of the first edition, the statistical landscape has substantially changed for analyzing space and space-time data. More than twice the size of its predecessor, Hierarchical Modeling and Analysis for Spatial Data, Second Edition reflects the major growth in spatial statistics as both a research area and an area of application. New to the Second Edition New chapter on spatial point patterns developed primarily from a modeling perspective New chapter on big data that shows how the predictive process handles reasonably large datasets New chapter on spatial and spatiotemporal gradient modeling that incorporates recent developments in spatial boundary analysis and wombling New chapter on the theoretical aspects of geostatistical (point-referenced) modeling Greatly expanded chapters on methods for multivariate and spatiotemporal modeling New special topics sections on data fusion/assimilation and spatial analysis for data on extremes Double the number of exercises Many more color figures integrated throughout the text Updated computational aspects, including the latest version of WinBUGS, the new flexible spBayes software, and assorted R packages The Only Comprehensive Treatment of the Theory, Methods, and Software This second edition continues to provide a complete treatment of the theory, methods, and application of hierarchical modeling for spatial and spatiotemporal data. It tackles current challenges in handling this type of data, with increased emphasis on observational data, big data, and the upsurge of associated software tools. The authors also explore important application domains, including environmental science, forestry, public health, and real estate.

Ecological Statistics

Ecological Statistics Book
Author : Gordon A. Fox,Simoneta Negrete-Yankelevich,Vinicio J. Sosa
Publisher : OUP Oxford
Release : 2015-01-29
ISBN : 0191652881
Language : En, Es, Fr & De

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Book Description :

The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics. This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.

Canadian Journal of Fisheries and Aquatic Sciences

Canadian Journal of Fisheries and Aquatic Sciences Book
Author : Anonim
Publisher : Unknown
Release : 2012
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Canadian Journal of Fisheries and Aquatic Sciences book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Maximum Likelihood Estimation and Inference

Maximum Likelihood Estimation and Inference Book
Author : Russell B. Millar
Publisher : John Wiley & Sons
Release : 2011-07-26
ISBN : 1119977711
Language : En, Es, Fr & De

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Book Description :

This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statistical paradigm. Key features: Provides an accessible introduction to pragmatic maximum likelihood modelling. Covers more advanced topics, including general forms of latent variable models (including non-linear and non-normal mixed-effects and state-space models) and the use of maximum likelihood variants, such as estimating equations, conditional likelihood, restricted likelihood and integrated likelihood. Adopts a practical approach, with a focus on providing the relevant tools required by researchers and practitioners who collect and analyze real data. Presents numerous examples and case studies across a wide range of applications including medicine, biology and ecology. Features applications from a range of disciplines, with implementation in R, SAS and/or ADMB. Provides all program code and software extensions on a supporting website. Confines supporting theory to the final chapters to maintain a readable and pragmatic focus of the preceding chapters. This book is not just an accessible and practical text about maximum likelihood, it is a comprehensive guide to modern maximum likelihood estimation and inference. It will be of interest to readers of all levels, from novice to expert. It will be of great benefit to researchers, and to students of statistics from senior undergraduate to graduate level. For use as a course text, exercises are provided at the end of each chapter.

Ecological Inference

Ecological Inference Book
Author : Gary King,Martin A. Tanner,Ori Rosen
Publisher : Cambridge University Press
Release : 2004-09-13
ISBN : 9780521542807
Language : En, Es, Fr & De

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Book Description :

Drawing upon the explosion of research in the field, a diverse group of scholars surveys strategies for solving ecological inference problems, the process of trying to infer individual behavior from aggregate data. The uncertainties and information lost in aggregation make ecological inference one of the most difficult areas of statistical inference, but these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, marketing research by business, and policy analysis by governments. This wide-ranging collection of essays, first published in 2004, offers many important contributions to the study of ecological inference.

Journal of the Royal Statistical Society

Journal of the Royal Statistical Society Book
Author : Anonim
Publisher : Unknown
Release : 2004
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Journal of the Royal Statistical Society book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.