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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
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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
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Author : Marc Kéry
language : en
Publisher: Academic Press
Release Date : 2020-10-10

Applied Hierarchical Modeling In Ecology Analysis Of Distribution Abundance And Species Richness In R And Bugs written by Marc Kéry and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-10 with Nature categories.


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


Applied Hierarchical Modeling In Ecology Analysis Of Distribution Abundance And Species Richness In R And Bugs
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Author : Marc Kéry
language : en
Publisher: Academic Press
Release Date : 2015-11-14

Applied Hierarchical Modeling In Ecology Analysis Of Distribution Abundance And Species Richness In R And Bugs written by Marc Kéry and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-14 with Science categories.


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



Hierarchical Modeling And Inference In Ecology


Hierarchical Modeling And Inference In Ecology
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Author : J. Andrew Royle
language : en
Publisher: Elsevier
Release Date : 2008-10-15

Hierarchical Modeling And Inference In Ecology written by J. Andrew Royle and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-15 with Science categories.


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



Bayesian Population Analysis Using Winbugs


Bayesian Population Analysis Using Winbugs
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Author : Marc Kéry
language : en
Publisher: Academic Press
Release Date : 2012

Bayesian Population Analysis Using Winbugs written by Marc Kéry and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.


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


Introduction To Winbugs For Ecologists
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Author : Marc Kéry
language : en
Publisher: Academic Press
Release Date : 2010-07-19

Introduction To Winbugs For Ecologists written by Marc Kéry and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-19 with Science categories.


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)



Spatial Capture Recapture


Spatial Capture Recapture
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Author : J. Andrew Royle
language : en
Publisher: Academic Press
Release Date : 2013-08-27

Spatial Capture Recapture written by J. Andrew Royle and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-27 with Science categories.


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


Joint Species Distribution Modelling
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Author : Otso Ovaskainen
language : en
Publisher: Cambridge University Press
Release Date : 2020-06-11

Joint Species Distribution Modelling written by Otso Ovaskainen and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-11 with Nature categories.


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



Bayesian Data Analysis In Ecology Using Linear Models With R Bugs And Stan


Bayesian Data Analysis In Ecology Using Linear Models With R Bugs And Stan
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Author : Franzi Korner-Nievergelt
language : en
Publisher: Academic Press
Release Date : 2015-04-04

Bayesian Data Analysis In Ecology Using Linear Models With R Bugs And Stan written by Franzi Korner-Nievergelt and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-04 with Science categories.


Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions—including all R codes—that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types. - Introduces Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest - Written in a step-by-step approach that allows for eased understanding by non-statisticians - Includes a companion website containing R-code to help users conduct Bayesian data analyses on their own data - All example data as well as additional functions are provided in the R-package blmeco



Neotropical Mammals


Neotropical Mammals
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Author : Salvador Mandujano
language : en
Publisher: Springer Nature
Release Date : 2023-11-01

Neotropical Mammals written by Salvador Mandujano and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-01 with Science categories.


This book reviews and synthesizes studies on local and regional occupancy and abundance of Neotropical mammals from central Mexico to South America. The book focuses primarily on addressing issues of a wide array of mammalian species from a population level in different habitats and ecosystems across the Neotropical region. Occupancy and abundance analyzed through hierarchical approaches with a variety of statistical tools are the central ecological parameters treated in the chapters of this volume. This book will be an updated reference for researchers, professionals, students, wildlife managers, and people interested in mammal ecology and conservation in tropical and subtropical regions.