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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 : Academic Press
Release : 2008
ISBN : 9780123740977
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

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

APPLIED HIERARCHICAL MODELING IN ECOLOGY Book
Author : MARC. ROYLE KERY (J. ANDREW.)
Publisher : Unknown
Release : 2020
ISBN : 9780128237687
Language : En, Es, Fr & De

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Book Description :

Download APPLIED HIERARCHICAL MODELING IN ECOLOGY book written by MARC. ROYLE KERY (J. ANDREW.), available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Workshop Hierarchical Models in Ecology Inference in Population Metapopulation and Community Ecology

Workshop  Hierarchical Models in Ecology  Inference in Population  Metapopulation  and Community Ecology  Book
Author : Robert M. Dorazio,J. Andrew Royle
Publisher : Unknown
Release : 2007*
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Workshop Hierarchical Models in Ecology Inference in Population Metapopulation and Community Ecology book written by Robert M. Dorazio,J. Andrew Royle, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

APPLIED HIERARCHICAL MODELING IN ECOLOGY ANALYSIS OF DISTRIBUTION ABUNDANCE AND SPECIES RICHNESS IN R AND BUGS INTERLOAN 390463

APPLIED HIERARCHICAL MODELING IN ECOLOGY  ANALYSIS OF DISTRIBUTION  ABUNDANCE AND SPECIES RICHNESS IN R AND BUGS  INTERLOAN 390463   Book
Author : Anonim
Publisher : Unknown
Release : 2021-06-15
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download APPLIED HIERARCHICAL MODELING IN ECOLOGY ANALYSIS OF DISTRIBUTION ABUNDANCE AND SPECIES RICHNESS IN R AND BUGS INTERLOAN 390463 book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

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

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

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.

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 : 2015-11-14
ISBN : 0128014865
Language : En, Es, Fr & De

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Book Description :

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

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

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 : 2020-07-02
ISBN : 9780367576714
Language : En, Es, Fr & De

GET BOOK

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.

A Robust design Formulation of the Incidence Function Model of Metapopulation Dynamics Applied to Two Species of Rails

A Robust design Formulation of the Incidence Function Model of Metapopulation Dynamics Applied to Two Species of Rails Book
Author : Benjamin Brewster Risk
Publisher : Unknown
Release : 2009
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download A Robust design Formulation of the Incidence Function Model of Metapopulation Dynamics Applied to Two Species of Rails book written by Benjamin Brewster Risk, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Occupancy Estimation and Modeling

Occupancy Estimation and Modeling Book
Author : Darryl I. MacKenzie,James D. Nichols,Larissa L. Bailey,J. Andrew Royle,Kenneth H. Pollock,James E. Hines
Publisher : Academic Press
Release : 2017-10
ISBN : 9780128146910
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

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

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.

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

Revista de biolog a tropical

Revista de biolog  a tropical Book
Author : Anonim
Publisher : Unknown
Release : 2014
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Revista de biolog a tropical book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Statistical Modeling and Inference for the Analysis of Spatial Categorical Data

Statistical Modeling and Inference for the Analysis of Spatial Categorical Data Book
Author : Anonim
Publisher : Unknown
Release : 2012
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Spatial categorical data on a lattice are becoming increasingly abundant due to the advances of geographic information systems in environmental science. In this thesis, statistical tools are developed for regression analysis of this type of data. The response variable is modeled by a multinomial distribution in a generalized linear mixed model framework. There are two additive components in the linear predictor: a linear regression on covariates and a spatial random effect such that the spatial dependence in the random effect is induced by a multivariate conditional autoregressive model. Bayesian hierarchical modeling is used for statistical inference and Markov chain Monte Carlo algorithms are devised to obtain posterior samples. The methodology is applied to analyze a northern Wisconsin land cover data set in a study that assesses the relationship between forest landscape structure and past social conditions, expanding the analytical tools available in landscape ecology and environmental history. Besides Bayesian hierarchical modeling, various other statistical methods have been developed for relating a spatial binary response to covariates in environmental and ecological studies, while properly accounting for spatial dependence. However, these methods tend to be computationally intensive and may be sensitive to model misspecification. Thus, a quasi-likelihood estimating equation is further developed for estimating regression coefficients and drawing statistical inference. In addition, a regularization method is proposed for model selection via penalized quasi-likelihood under an adaptive Lasso. A series of simulations are conducted to evaluate the performance of these new methods. For illustration, these methods are also applied to analyze the northern Wisconsin land cover data set.

Bayesian Disease Mapping

Bayesian Disease Mapping Book
Author : Andrew B. Lawson
Publisher : CRC Press
Release : 2018-05-20
ISBN : 135127175X
Language : En, Es, Fr & De

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Book Description :

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. In addition to the new material, the book also covers more conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis. After an introduction to Bayesian inference, computation, and model assessment, the text focuses on important themes, including disease map reconstruction, cluster detection, regression and ecological analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. It shows how Bayesian disease mapping can yield significant insights into georeferenced health data. The target audience for this text is public health specialists, epidemiologists, and biostatisticians who need to work with geo-referenced health data.