June 12, 2021

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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
Author : Marc Kery,J. Andrew Royle
Publisher : Academic Press
Release Date : 2020-10-10
Category : Nature
Total pages :820
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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

APPLIED HIERARCHICAL MODELING IN ECOLOGY

APPLIED HIERARCHICAL MODELING IN ECOLOGY
Author : MARC. ROYLE KERY (J. ANDREW.)
Publisher : Unknown
Release Date : 2020
Category :
Total pages :129
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Applied Hierarchical Modeling in Ecology

Applied Hierarchical Modeling in Ecology
Author : Manuel Marton Marc Kéry,J. Andrew Royle
Publisher : Unknown
Release Date : 2016
Category :
Total pages :129
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Hierarchical Modeling and Inference in Ecology

Hierarchical Modeling and Inference in Ecology
Author : J. Andrew Royle,Robert M. Dorazio
Publisher : Elsevier
Release Date : 2008-10-15
Category : Science
Total pages :464
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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
Author : Marc Kéry,J. Andrew Royle
Publisher : Academic Press
Release Date : 2015-12-10
Category : Science
Total pages :808
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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

Models of the Ecological Hierarchy

Models of the Ecological Hierarchy
Author : Anonim
Publisher : Newnes
Release Date : 2012-12-31
Category : Science
Total pages :594
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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
Author : Eric Parent,Etienne Rivot
Publisher : CRC Press
Release Date : 2012-08-21
Category : Mathematics
Total pages :427
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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.

Current Index to Statistics, Applications, Methods and Theory

Current Index to Statistics, Applications, Methods and Theory
Author : Anonim
Publisher : Unknown
Release Date : 1999
Category : Mathematical statistics
Total pages :129
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Basic and Applied General Systems Research

Basic and Applied General Systems Research
Author : Robert Trappl,Werner Horn,George J. Klir
Publisher : Hemisphere Pub
Release Date : 1985
Category : Computers
Total pages :348
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Individual-Based Models and Approaches in Ecology

Individual-Based Models and Approaches in Ecology
Author : Donald DeAngelis
Publisher : Springer
Release Date : 1992-08-06
Category : Science
Total pages :525
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This volume contains contributions from leading ecologists on the use of individual-based modelling approaches to address ecological issues at the population and community scales.

Applied Ecology Abstracts

Applied Ecology Abstracts
Author : Anonim
Publisher : Unknown
Release Date : 1979
Category : Applied ecology
Total pages :129
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De structuur van wetenschappelijke revoluties

De structuur van wetenschappelijke revoluties
Author : Thomas S. Kuhn
Publisher : Boom Koninklijke Uitgevers
Release Date : 1972
Category : Science
Total pages :238
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Bayesian Analysis for Population Ecology

Bayesian Analysis for Population Ecology
Author : Ruth King,Byron Morgan,Olivier Gimenez,Steve Brooks
Publisher : Chapman and Hall/CRC
Release Date : 2010
Category : Mathematics
Total pages :442
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Emphasising model choice and model averaging, this book presents up-to-date methods for analysing complex ecological data.

Terrestrial and Aquatic Ecosystems

Terrestrial and Aquatic Ecosystems
Author : O. Ravera
Publisher : Ellis Horwood Limited
Release Date : 1991
Category : Science
Total pages :613
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