Spatial Capture Recapture

Spatial Capture Recapture
Author: J. Andrew Royle,Richard B. Chandler,Rahel Sollmann,Beth Gardner
Publsiher: Academic Press
Total Pages: 612
Release: 2013-08-27
Genre: Science
ISBN: 9780124071520

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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

Spatial Capture Recapture

Spatial Capture Recapture
Author: J. Andrew Royle,Richard B. Chandler,Rahel Sollmann,Beth Gardner
Publsiher: Academic Press
Total Pages: 612
Release: 2017-11-13
Genre: Science
ISBN: 0128100125

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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 anR 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 "

Analysis of Capture Recapture Data

Analysis of Capture Recapture Data
Author: Rachel S. McCrea,Byron J. T. Morgan
Publsiher: CRC Press
Total Pages: 314
Release: 2014-08-01
Genre: Mathematics
ISBN: 9781439836606

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An important first step in studying the demography of wild animals is to identify the animals uniquely through applying markings, such as rings, tags, and bands. Once the animals are encountered again, researchers can study different forms of capture-recapture data to estimate features, such as the mortality and size of the populations. Capture-rec

Handbook of Capture Recapture Analysis

Handbook of Capture Recapture Analysis
Author: Steven C. Amstrup,Trent L. McDonald,Bryan F. J. Manly
Publsiher: Princeton University Press
Total Pages: 336
Release: 2010-12-16
Genre: Science
ISBN: 9781400837717

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Every day, biologists in parkas, raincoats, and rubber boots go into the field to capture and mark a variety of animal species. Back in the office, statisticians create analytical models for the field biologists' data. But many times, representatives of the two professions do not fully understand one another's roles. This book bridges this gap by helping biologists understand state-of-the-art statistical methods for analyzing capture-recapture data. In so doing, statisticians will also become more familiar with the design of field studies and with the real-life issues facing biologists. Reliable outcomes of capture-recapture studies are vital to answering key ecological questions. Is the population increasing or decreasing? Do more or fewer animals have a particular characteristic? In answering these questions, biologists cannot hope to capture and mark entire populations. And frequently, the populations change unpredictably during a study. Thus, increasingly sophisticated models have been employed to convert data into answers to ecological questions. This book, by experts in capture-recapture analysis, introduces the most up-to-date methods for data analysis while explaining the theory behind those methods. Thorough, concise, and portable, it will be immensely useful to biologists, biometricians, and statisticians, students in both fields, and anyone else engaged in the capture-recapture process.

Hierarchical Modeling and Inference in Ecology

Hierarchical Modeling and Inference in Ecology
Author: J. Andrew Royle,Robert M. Dorazio
Publsiher: Elsevier
Total Pages: 464
Release: 2008-10-15
Genre: Science
ISBN: 9780080559254

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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

Measuring Abundance

Measuring Abundance
Author: Graham Upton
Publsiher: Pelagic Publishing Ltd
Total Pages: 229
Release: 2020-10-12
Genre: Science
ISBN: 9781784272333

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Measuring the abundance of individuals and the diversity of species are core components of most ecological research projects and conservation monitoring. This book brings together in one place, for the first time, the methods used to estimate the abundance of individuals in nature. The statistical basis of each method is detailed along with practical considerations for survey design and data collection. Methods are illustrated using data ranging from Alaskan shrubs to Yellowstone grizzly bears, not forgetting Costa Rican ants and Prince Edward Island lobsters. Where necessary, example code for use with the open source software R is supplied. When appropriate, reference is made to other widely used programs. After opening with a brief synopsis of relevant statistical methods, the first section deals with the abundance of stationary items such as trees, shrubs, coral, etc. Following a discussion of the use of quadrats and transects in the contexts of forestry sampling and the assessment of plant cover, there are chapters addressing line-intercept sampling, the use of nearest-neighbour distances, and variable sized plots. The second section deals with individuals that move, such as birds, mammals, reptiles, fish, etc. Approaches discussed include double-observer sampling, removal sampling, capture-recapture methods and distance sampling. The final section deals with the measurement of species richness; species diversity; species-abundance distributions; and other aspects of diversity such as evenness, similarity, turnover and rarity. This is an essential reference for anyone involved in advanced undergraduate or postgraduate ecological research and teaching, or those planning and carrying out data analysis as part of conservation survey and monitoring programmes.

A Continuous time Formulation for Spatial Capture recapture Models

A Continuous time Formulation for Spatial Capture recapture Models
Author: Greg Distiller
Publsiher: Unknown
Total Pages: 135
Release: 2017
Genre: Electronic Book
ISBN: OCLC:1063706571

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On the Topic of Spatial Capture Recapture Modeling

On the Topic of Spatial Capture Recapture Modeling
Author: Paul McLaughlin
Publsiher: Unknown
Total Pages: 135
Release: 2019
Genre: Electronic dissertations
ISBN: OCLC:1196364456

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Over the past two decades there have been many advancements in modeling capture-recapture (CR) data to account for emerging data collection technology and techniques. Spatial capture-recapture (SCR) models have been introduced to estimate population size and numerous other demographic parameters from spatially explicit CR data. Here we offer a comprehensive review of the development of CR modeling up to and including SCR models. We then introduce a new SCR model which allows for attractions between individuals via their daily movements. A simulation study is used to demonstrate accounting for these attractions can improve population size estimation. Additionally, we apply our model to an iconic SCR dataset to estimate the population size and attraction parameters of a Bengal tiger (\textit{Panthera tigris tigris}) population. To conclude we present a reversible-jump Markov chain Monte Carlo (RJMCMC) approach for parameter estimation which has not previously been extended to SCR models. Simulation studies are presented to show the superior computational efficiency of this proposed approach. We also demonstrate the application of this RJMCMC method to SCR data by estimating the size of an American black bear (Ursus americanus) population.