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Spatial capture-recapture /

"Space plays a vital role in virtually all ecological processes (Tilman and Kareiva, 1997; Hanski, 1999; Clobert et al., 2001). The spatial arrangement of habitat can influence movement patterns during dispersal, habitat selection, and survival. The distance between an organism and its competit...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Royle, J. Andrew (Editor ), Chandler, Richard B. (Editor ), Sollmann, Rahel (Editor ), Gardner, Beth (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boston : Elsevier, 2013.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Spatial capture-recapture /  |c edited by J. Andrew Royle, Richard B. Chandler, Rahel Sollmann, Beth Gardner. 
264 1 |a Boston :  |b Elsevier,  |c 2013. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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520 2 |a "Space plays a vital role in virtually all ecological processes (Tilman and Kareiva, 1997; Hanski, 1999; Clobert et al., 2001). The spatial arrangement of habitat can influence movement patterns during dispersal, habitat selection, and survival. The distance between an organism and its competitors and prey can influence activity patterns and foraging behavior. Further, understanding distribution and spatial variation in abundance is necessary in the conservation and management of populations"--  |c Provided by publisher 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
505 0 |a Half Title; Title Page; Copyright; Contents; Foreword; Preface; Acknowledgments; PART I: Background and Concepts; 1 Introduction; 1.1 The study of populations by capture-recapture; 1.2 Lions and Tigers and Bears, oh my: Genesis of Spatial; 1.2.1 Camera trapping; 1.2.2 DNA sampling; 1.2.3 Acoustic sampling; 1.2.4 Search-encounter methods; 1.3 Capture-Recapture for Modeling Encounter Probability; 1.3.1 Example: Fort Drum bear study; 1.3.2 Inadequacy of non-spatial capture-recapture; 1.4 Historical Context: a Brief Synopsis; 1.4.1 Buffering; 1.4.2 Temporary emigration. 
505 8 |a 1.5 Extension of Closed Population Models1.5.1 Toward spatial explicitness: Efford's formulation; 1.5.2 Abundance as the aggregation of a point process; 1.5.3 The activity center concept; 1.5.4 The state-space; 1.5.5 Abundance and density; 1.6 Characterization of SCR Models; 1.7 Summary and Outlook; 2 Statistical Models and SCR; 2.1 Random Variables and Probability Distributions; 2.1.1 Stochasticity in ecology; 2.1.2 Properties of probability distributions; 2.2 Common Probability Distributions; 2.2.1 The binomial distribution; 2.2.2 The Bernoulli distribution. 
505 8 |a 2.2.3 The multinomial and categorical distributions2.2.4 The Poisson distribution; 2.2.5 The uniform distribution; 2.2.6 Other distributions; 2.3 Statistical Inference and Parameter Estimation; 2.4 Joint, Marginal, and Conditional Distributions; 2.5 Hierarchical Models and Inference; 2.6 Characterization of SCR Models; 2.7 Summary and Outlook; 3 GLMs and Bayesian Analysis; 3.1 GLMs and GLMMs; 3.2 Bayesian Analysis; 3.2.1 Bayes' rule; 3.2.2 Principles of Bayesian inference; 3.2.3 Prior distributions; 3.2.4 Posterior inference; 3.2.5 Small sample inference. 
505 8 |a 3.3 Characterizing Posterior Distributions by MCMC Simulation3.3.1 What goes on under the MCMC hood; 3.3.2 Rules for constructing full conditional distributions; 3.3.3 Metropolis-Hastings algorithm; 3.4 Bayesian Analysis Using the BUGS Language; 3.4.1 Linear regression in WinBUGS; 3.5 Practical Bayesian Analysis and MCMC; 3.5.1 Choice of prior distributions; 3.5.2 Convergence and so forth; 3.5.3 Bayesian confidence intervals; 3.5.4 Estimating functions of parameters; 3.6 Poisson GLMs; 3.6.1 North American breeding bird survey data; 3.6.2 Poisson GLM in WinBUGS. 
505 8 |a 3.6.3 Constructing your own MCMC algorithm3.7 Poisson GLM with Random Effects; 3.8 Binomial GLMs; 3.8.1 Binomial regression; 3.8.2 North American waterfowl banding data; 3.9 Bayesian Model Checking and Selection; 3.9.1 Goodness-of-fit; 3.9.2 Model selection; 3.10 Summary and Outlook; 4 Closed Population Models; 4.1 The Simplest Closed Population Model: Model M0; 4.1.1 The core capture-recapture assumptions; 4.1.2 Conditional likelihood; 4.2 Data Augmentation; 4.2.1 DA links occupancy models and closed population models; 4.2.2 Model M0 in BUGS; 4.2.3 Remarks on data augmentation. 
546 |a English. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Spatial ecology  |x Research. 
650 0 |a Spatial behavior in animals  |x Research. 
650 0 |a Animal populations  |x Mathematical models. 
650 0 |a Biological models. 
650 0 |a Population density. 
650 1 2 |a Animals 
650 1 2 |a Models, Biological 
650 1 2 |a Population Density 
650 6 |a Écologie spatiale  |x Recherche. 
650 6 |a Comportement spatial chez les animaux  |x Recherche. 
650 6 |a Animaux  |x Populations  |x Modèles mathématiques. 
650 6 |a Modèles biologiques. 
650 6 |a Population  |x Densité. 
650 7 |a population density.  |2 aat 
650 7 |a SCIENCE  |x Life Sciences  |x Zoology  |x General.  |2 bisacsh 
650 7 |a Population density  |2 fast 
650 7 |a Biological models  |2 fast 
650 7 |a Animal populations  |x Mathematical models  |2 fast 
700 1 |a Royle, J. Andrew,  |e editor. 
700 1 |a Chandler, Richard B.,  |e editor. 
700 1 |a Sollmann, Rahel,  |e editor. 
700 1 |a Gardner, Beth,  |e editor  |1 http://www.wikidata.org/entity/Q88550011 
758 |i has work:  |a Spatial capture-recapture (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCFTcrCyCFfJJcjDQ8WV4hd  |4 https://id.oclc.org/worldcat/ontology/hasWork 
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