Hierarchical Modeling and Inference in Ecology Book

Hierarchical Modeling and Inference in Ecology


  • Author : J. Andrew Royle
  • Publisher : Elsevier
  • Release Date : 2008-10-15
  • Genre: Science
  • Pages : 464
  • ISBN 10 : 9780080559254

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Hierarchical Modeling and Inference in Ecology Excerpt :

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 Book

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


  • Author : Marc Kery
  • Publisher : Academic Press
  • Release Date : 2020-10-10
  • Genre: Nature
  • Pages : 820
  • ISBN 10 : 9780128097274

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

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 to people who are struggling to use complex or advanced modeling programs Synthesizes current ecological models and explains how they are inter-connected Contains numerous examples throughout the book, walking the reading through scenarios with both real and simulated data Provides an ideal resource for ecologists working in R software and in BUGS software for more flexible Bayesian analyses

Applied Hierarchical Modeling in Ecology  Analysis of distribution  abundance and species richness in R and BUGS Book

Applied Hierarchical Modeling in Ecology Analysis of distribution abundance and species richness in R and BUGS


  • Author : Marc Kery
  • Publisher : Academic Press
  • Release Date : 2015-11-14
  • Genre: Nature
  • Pages : 808
  • ISBN 10 : 9780128014868

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Applied Hierarchical Modeling in Ecology Analysis of distribution abundance and species richness in R and BUGS Excerpt :

Applied Hierarchical Modeling in Ecology: Distribution, Abundance, Species Richness offers a new synthesis of the state-of-the-art of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected in metapopulation designs. These types of data are extremely widespread in ecology and its applications in such areas as biodiversity monitoring and fisheries and wildlife management. This first volume explains static models/procedures in the context of hierarchical models that collectively represent a unified approach to ecological research, taking the reader from design, through data collection, and into analyses using a very powerful class of models. Applied Hierarchical Modeling in Ecology, Volume 1 serves as an indispensable manual for practicing field biologists, and as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields. Provides a synthesis of important classes of models about distribution, abundance, and species richness while accommodating imperfect detection Presents models and methods for identifying unmarked individuals and species Written in a step-by-step approach accessible to non-statisticians and provides fully worked examples that serve as a template for readers' analyses Includes companion website containing data sets, code, solutions to exercises, and further information

Introduction to Hierarchical Bayesian Modeling for Ecological Data Book

Introduction to Hierarchical Bayesian Modeling for Ecological Data


  • Author : Eric Parent
  • Publisher : CRC Press
  • Release Date : 2012-08-21
  • Genre: Mathematics
  • Pages : 429
  • ISBN 10 : 9781584889199

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Introduction to Hierarchical Bayesian Modeling for Ecological Data Excerpt :

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 Population Analysis using WinBUGS Book

Bayesian Population Analysis using WinBUGS


  • Author : Marc Kery
  • Publisher : Academic Press
  • Release Date : 2011-10-11
  • Genre: Science
  • Pages : 554
  • ISBN 10 : 9780123870216

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Bayesian Population Analysis using WinBUGS Excerpt :

Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS, and its open-source sister OpenBugs, is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics. Comprehensive and richly commented examples illustrate a wide range of models that are most relevant to the research of a modern population ecologist All WinBUGS/OpenBUGS analyses are completely integrated in software R Includes complete documentation of all R and WinBUGS code required to conduct analyses and shows all the necessary steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R

Introduction to WinBUGS for Ecologists Book
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Introduction to WinBUGS for Ecologists


  • Author : Marc Kery
  • Publisher : Academic Press
  • Release Date : 2010-07-19
  • Genre: Science
  • Pages : 320
  • ISBN 10 : 0123786061

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Introduction to WinBUGS for Ecologists Excerpt :

Introduction to WinBUGS for Ecologists introduces applied Bayesian modeling to ecologists using the highly acclaimed, free WinBUGS software. It offers an understanding of statistical models as abstract representations of the various processes that give rise to a data set. Such an understanding is basic to the development of inference models tailored to specific sampling and ecological scenarios. The book begins by presenting the advantages of a Bayesian approach to statistics and introducing the WinBUGS software. It reviews the four most common statistical distributions: the normal, the uniform, the binomial, and the Poisson. It describes the two different kinds of analysis of variance (ANOVA): one-way and two- or multiway. It looks at the general linear model, or ANCOVA, in R and WinBUGS. It introduces generalized linear model (GLM), i.e., the extension of the normal linear model to allow error distributions other than the normal. The GLM is then extended contain additional sources of random variation to become a generalized linear mixed model (GLMM) for a Poisson example and for a binomial example. The final two chapters showcase two fairly novel and nonstandard versions of a GLMM. The first is the site-occupancy model for species distributions; the second is the binomial (or N-) mixture model for estimation and modeling of abundance. Introduction to the essential theories of key models used by ecologists Complete juxtaposition of classical analyses in R and Bayesian analysis of the same models in WinBUGS Provides every detail of R and WinBUGS code required to conduct all analyses Companion Web Appendix that contains all code contained in the book and additional material (including more code and solutions to exercises)

Ecological Models and Data in R Book

Ecological Models and Data in R


  • Author : Benjamin M. Bolker
  • Publisher : Princeton University Press
  • Release Date : 2008-07-21
  • Genre: Computers
  • Pages : 408
  • ISBN 10 : 9780691125220

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Ecological Models and Data in R Excerpt :

Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.

Hierarchical Modeling and Analysis for Spatial Data Book

Hierarchical Modeling and Analysis for Spatial Data


  • Author : Sudipto Banerjee
  • Publisher : CRC Press
  • Release Date : 2003-12-17
  • Genre: Mathematics
  • Pages : 470
  • ISBN 10 : 9780203487808

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Hierarchical Modeling and Analysis for Spatial Data Excerpt :

Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis,

Integrated Population Models Book

Integrated Population Models


  • Author : Michael Schaub
  • Publisher : Academic Press
  • Release Date : 2021-11-23
  • Genre: Nature
  • Pages : 638
  • ISBN 10 : 9780128209158

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Integrated Population Models Excerpt :

Integrated Population Models: Theory and Ecological Applications with R and JAGS is the first book on integrated population models, which constitute a powerful framework for combining multiple data sets from the population and the individual levels to estimate demographic parameters, and population size and trends. These models identify drivers of population dynamics and forecast the composition and trajectory of a population. Written by two population ecologists with expertise on integrated population modeling, this book provides a comprehensive synthesis of the relevant theory of integrated population models with an extensive overview of practical applications, using Bayesian methods by means of case studies. The book contains fully-documented, complete code for fitting all models in the free software, R and JAGS. It also includes all required code for pre- and post-model-fitting analysis. Integrated Population Models is an invaluable reference for researchers and practitioners involved in population analysis, and for graduate-level students in ecology, conservation biology, wildlife management, and related fields. The text is ideal for self-study and advanced graduate-level courses. Offers practical and accessible ecological applications of IPMs (integrated population models) Provides full documentation of analyzed code in the Bayesian framework Written and structured for an easy approach to the subject, especially for non-statisticians

Models of the Ecological Hierarchy Book

Models of the Ecological Hierarchy


  • Author : Ferenc Jordan
  • Publisher : Newnes
  • Release Date : 2012-11-29
  • Genre: Nature
  • Pages : 596
  • ISBN 10 : 9780444593962

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Models of the Ecological Hierarchy Excerpt :

"Based on selected papers covering the presentations at the 7th European Conference on Ecological Modelling, organized by ISEM and hosted by The Microsoft Research--University of Trento Center for Computational and Systems Biology from 30 May to 2 June, 2011 in Riva del Garde, Italy"--P. xi.

Analysis and Management of Animal Populations Book

Analysis and Management of Animal Populations


  • Author : Byron K. Williams
  • Publisher : Academic Press
  • Release Date : 2002-04-17
  • Genre: Juvenile Nonfiction
  • Pages : 837
  • ISBN 10 : 9780127544069

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Analysis and Management of Animal Populations Excerpt :

Analysis and Management of Animal Populations deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal populations. Integrates population modeling, parameter estimation and decision-theoretic approaches to management in a single, cohesive framework Provides authoritative, state-of-the-art descriptions of quantitative approaches to modeling, estimation and decision-making Emphasizes the role of mathematical modeling in the conduct of science and management Utilizes a unifying biological context, consistent mathematical notation, and numerous biological examples

Spatial Capture Recapture Book

Spatial Capture Recapture


  • Author : J. Andrew Royle
  • Publisher : Academic Press
  • Release Date : 2013-08-27
  • Genre: Science
  • Pages : 612
  • ISBN 10 : 9780124071520

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Spatial Capture Recapture Excerpt :

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

Joint Species Distribution Modelling Book

Joint Species Distribution Modelling


  • Author : Otso Ovaskainen
  • Publisher : Cambridge University Press
  • Release Date : 2020-06-11
  • Genre: Nature
  • Pages : 389
  • ISBN 10 : 9781108492461

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Joint Species Distribution Modelling Excerpt :

A comprehensive account of joint species distribution modelling, covering statistical analyses in light of modern community ecology theory.

Bayesian Models Book

Bayesian Models


  • Author : N. Thompson Hobbs
  • Publisher : Princeton University Press
  • Release Date : 2015-08-04
  • Genre: Science
  • Pages : 315
  • ISBN 10 : 9781400866557

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Bayesian Models Excerpt :

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

Occupancy Estimation and Modeling Book

Occupancy Estimation and Modeling


  • Author : Darryl I. MacKenzie
  • Publisher : Elsevier
  • Release Date : 2017-11-17
  • Genre: Science
  • Pages : 648
  • ISBN 10 : 9780124072459

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Occupancy Estimation and Modeling Excerpt :

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