December 4, 2020

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Spatial Capture-Recapture

Spatial Capture-Recapture
Author : J. Andrew Royle,Richard B. Chandler,Rahel Sollmann,Beth Gardner
Publisher : Academic Press
Release Date : 2013-08-27
Category : Science
Total pages :612
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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
Publisher : Academic Press
Release Date : 2017-11-13
Category : Science
Total pages :612
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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 "

On the Topic of Spatial Capture-Recapture Modeling

On the Topic of Spatial Capture-Recapture Modeling
Author : Paul McLaughlin
Publisher : Unknown
Release Date : 2019
Category : Electronic dissertations
Total pages :129
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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.

Assessing the Performance of an Open Spatial Capture-recapture Method on Grizzly Bear Populations when Age Data is Missing

Assessing the Performance of an Open Spatial Capture-recapture Method on Grizzly Bear Populations when Age Data is Missing
Author : Neil Faught
Publisher : Unknown
Release Date : 2020
Category :
Total pages :86
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It is often difficult in capture-recapture (CR) studies of grizzly bear populations to determine the age of detected bears. As a result, analyses often omit age terms in CR models despite past studies suggesting age influences detection probability. This paper explores how failing to account for age in the detection function of an open, spatially-explicit CR model, introduced in Efford & Schofield (2019), affects estimates of apparent survival, apparent recruitment, population growth, and grizzly bear home-range sizes. Using a simulation study, it was found that estimates of all parameters of interest excluding home-range size were robust to this omission. The effects of using two different types of detectors for data collection (bait sites and rub objects) on bias in estimates of above parameters was also explored via simulation. No evidence was found that one detector type was more prone to producing biased parameter estimates than the other.

Analysis of Capture-Recapture Data

Analysis of Capture-Recapture Data
Author : Rachel S. McCrea,Byron J. T. Morgan
Publisher : CRC Press
Release Date : 2014-08-01
Category : Mathematics
Total pages :314
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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

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

Camera Traps in Animal Ecology

Camera Traps in Animal Ecology
Author : Allan F. O'Connell,James D. Nichols,K. Ullas Karanth
Publisher : Springer Science & Business Media
Release Date : 2010-10-05
Category : Science
Total pages :271
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Remote photography and infrared sensors are widely used in the sampling of wildlife populations worldwide, especially for cryptic or elusive species. Guiding the practitioner through the entire process of using camera traps, this book is the first to compile state-of-the-art sampling techniques for the purpose of conducting high-quality science or effective management. Chapters on the evaluation of equipment, field sampling designs, and data analysis methods provide a coherent framework for making inferences about the abundance, species richness, and occupancy of sampled animals. The volume introduces new models that will revolutionize use of camera data to estimate population density, such as the newly developed spatial capture–recapture models. It also includes richly detailed case studies of camera trap work on some of the world’s most charismatic, elusive, and endangered wildlife species. Indispensible to wildlife conservationists, ecologists, biologists, and conservation agencies around the world, the text provides a thorough review of the subject as well as a forecast for the use of remote photography in natural resource conservation over the next few decades.

Handbook of Capture-Recapture Analysis

Handbook of Capture-Recapture Analysis
Author : Steven C. Amstrup,Trent L. McDonald,Bryan F. J. Manly
Publisher : Princeton University Press
Release Date : 2010-12-16
Category : Science
Total pages :336
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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.

Capture-Recapture: Parameter Estimation for Open Animal Populations

Capture-Recapture: Parameter Estimation for Open Animal Populations
Author : George A. F. Seber,Matthew R. Schofield
Publisher : Springer
Release Date : 2019-08-13
Category : Mathematics
Total pages :663
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This comprehensive book, rich with applications, offers a quantitative framework for the analysis of the various capture-recapture models for open animal populations, while also addressing associated computational methods. The state of our wildlife populations provides a litmus test for the state of our environment, especially in light of global warming and the increasing pollution of our land, seas, and air. In addition to monitoring our food resources such as fisheries, we need to protect endangered species from the effects of human activities (e.g. rhinos, whales, or encroachments on the habitat of orangutans). Pests must be be controlled, whether insects or viruses, and we need to cope with growing feral populations such as opossums, rabbits, and pigs. Accordingly, we need to obtain information about a given population’s dynamics, concerning e.g. mortality, birth, growth, breeding, sex, and migration, and determine whether the respective population is increasing , static, or declining. There are many methods for obtaining population information, but the most useful (and most work-intensive) is generically known as “capture-recapture,” where we mark or tag a representative sample of individuals from the population and follow that sample over time using recaptures, resightings, or dead recoveries. Marks can be natural, such as stripes, fin profiles, and even DNA; or artificial, such as spots on insects. Attached tags can, for example, be simple bands or streamers, or more sophisticated variants such as radio and sonic transmitters. To estimate population parameters, sophisticated and complex mathematical models have been devised on the basis of recapture information and computer packages. This book addresses the analysis of such models. It is primarily intended for ecologists and wildlife managers who wish to apply the methods to the types of problems discussed above, though it will also benefit researchers and graduate students in ecology. Familiarity with basic statistical concepts is essential.

A Continuous-time Formulation for Spatial Capture-recapture Models

A Continuous-time Formulation for Spatial Capture-recapture Models
Author : Greg Distiller
Publisher : Unknown
Release Date : 2017
Category :
Total pages :129
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Estimating Animal Abundance

Estimating Animal Abundance
Author : D.L. Borchers,Stephen T. Buckland,Walter Zucchini
Publisher : Springer Science & Business Media
Release Date : 2013-03-09
Category : Mathematics
Total pages :314
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The first accessible introduction to the many various wildlife assessment methods! This book uses a new approach that makes the full range of methods accessible in a way that has not previously been possible. Accompanied by free, user-friendly software to get some "hands-on" experience with the methods and how they perform in different contexts.

Integrated Population Biology and Modeling

Integrated Population Biology and Modeling
Author : Anonim
Publisher : Elsevier
Release Date : 2018-09-26
Category : Mathematics
Total pages :633
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Integrated Population Biology and Modeling: Part A offers very complex and precise realities of quantifying modern and traditional methods of understanding populations and population dynamics. Chapters cover emerging topics of note, including Longevity dynamics, Modeling human-environment interactions, Survival Probabilities from 5-Year Cumulative Life Table Survival Ratios (Tx+5/Tx): Some Innovative Methodological Investigations, Cell migration Models, Evolutionary Dynamics of Cancer Cells, an Integrated approach for modeling of coastal lagoons: A case for Chilka Lake, India, Population and metapopulation dynamics, Mortality analysis: measures and models, Stationary Population Models, Are there biological and social limits to human longevity?, Probability models in biology, Stochastic Models in Population Biology, and more. Covers emerging topics of note in the subject matter Presents chapters on Longevity dynamics, Modeling human-environment interactions, Survival Probabilities from 5-Year Cumulative Life Table Survival Ratios (Tx+5/Tx), and more

On the Estimation of Animal Density from Spatial Capture-recapture Data

On the Estimation of Animal Density from Spatial Capture-recapture Data
Author : Callum Kwun Yuen Young
Publisher : Unknown
Release Date : 2018
Category : Animal population density
Total pages :164
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Spatial capture-recapture (SCR) methods can estimate the density of animal populations. SCR contains elements of both capture-recapture, and distance sampling methods. Data are obtained through repeated detections of individuals by detectors at known locations, allowing the incorporation of the detection function in the SCR model. Naturally, individuals whose home ranges are centred nearer to a detector have a greater probability of being detected. Data obtained from SCR surveys are commonly presented as capture histories, which may contain either counts of detections, or binary indications of a detection (or non-detection). As counts can be converted into binary data, either model may be fitted to SCR data. Some advocate fitting models to the binary data, as incorrectly assuming the underlying statistical (count) distribution produces biased estimates; others suggest modelling the full counts, as the magnitudes of the counts provide supplementary information over and above that of the binary capture histories. We introduce the "scr" package for R, and describe its main features. A simulation study is performed to assess the performance of each model fitted to data from various underlying distributions. We show that both models give very similar inferences in all cases, regardless of the model type or true distribution. Additionally, the inference appears to be appropriate, even when the data are significantly overdispersed. Existing methods cannot sufficiently model acoustically detected data without making a number of assumptions that are often violated in practice. We thus present a new model circumventing the issues present in existing methods, whilst improving on them such that there may be a reduction in survey effort and cost. We further extend the application of this new model to situations where clustering of individuals' activity centres creates dependence problems with the data, and describe how our model accounts for this lack of independence.

Occupancy Estimation and Modeling

Occupancy Estimation and Modeling
Author : Darryl I. MacKenzie
Publisher : Academic Press
Release Date : 2006
Category : Nature
Total pages :324
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Occupancy in ecological investigations; Fundamental principles of statistical inference; Single-species, single-season occupancy models; Single-species, single-season models with heterogeneous detection probabilities; Design of single-season occupancy studies; Single-species, multiple-season occupancy models; Occupancy data for multiple species: species interactions; Occupancy in community-level studies; Future directions.

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