Bayesian Population Analysis Using WinBUGS A Hierarchical Perspective

Name: Bayesian Population Analysis Using WinBUGS A Hierarchical Perspective
Availability: InStock
ISBN: 9780123870209

ISBN-10: 0123870208

ISBN-13: 9780123870209

Edition: 2012

Authors: Marc Kï¿½ry, Michael Schaub

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Book details

List price: $150.00
Copyright year: 2012
Publisher: Elsevier Science & Technology
Publication date: 10/11/2011
Binding: Paperback
Pages: 554
Size: 5.94" wide x 9.00" long x 1.00" tall
Weight: 1.980

Dr KÃ©ry is a Population Ecologist with the Swiss Ornithological Institute and a courtesy professor ("Privatdozent") at the University of ZÃ¼rich/Switzerland, from where he received his PhD in Ecology in 2000. He is an expert in the estimation and modeling of abundance, distribution and species richness in "metapopulation designs" (i.e., collections of replicate sites). For most of his work, he uses the Bayesian model fitting software BUGS and JAGS, about which he has published three books with Academic Press (2010, 2012 and 2016). He has authored/coauthored over 100 peer-reviewed articles and book chapters and is teaching statistical modeling workshops about the methods in this book at…



Foreword


Preface


Acknowledgments



Introduction



Ecology: The Study of Distribution and Abundance and of the Mechanisms Driving Their Change



Genesis of Ecological Observations



The Binomial Distribution as a Canonical Description of the Observation Process



Structure and Overview of the Contents of this Book



Benefits of Analyzing Simulated Data Sets: An Example of Bias and Precision



Summary and Outlook



Exercises



Brief Introduction to Bayesian Statistical Modeling



Introduction



Role of Models in Science



Statistical Models



Frequentist and Bayesian Analysis of Statistical Models



Bayesian Computation



WinBUGS



Advantages and Disadvantages of Bayesian Analyses by Posterior Sampling



Hierarchical Models



Summary and Outlook



Introduction to the Generalized Linear Model: The Simplest Model for Count Data



Introduction



Statistical Models: Response = Signal + Noise



Poisson GLM in R and WinBUGS for Modeling Time Series of Counts



Poisson GLM for Modeling Fecundity



Binomial GLM for Modeling Bounded Counts or Proportions



Summary and Outlook



Exercises



Introduction to Random Effects: Conventional Poisson GLMM for Count Data



Introduction



Accounting for Overdispersion by Random Effects-Modeling in R and WinBUGS



Mixed Models with Random Effects for Variability among Groups (Site and Year Effects)



Summary and Outlook



Exercises



State-Space Models for Population Counts



Introduction



A Simple Model



Systematic Bias in the Observation Process



Real Example: House Martin Population Counts in the Village of Magden



Summary and Outlook



Exercises



Estimation of the Size of a Closed Population from Capture-Recapture Data



Introduction



Generation and Analysis of Simulated Data with Data Augmentation



Analysis of a Real Data Set: Model M<sub>tbh</sub> for Species Richness Estimation



Capture-Recapture Models with Individual Covariates: Model M<sub>t+X</sub>



Summary and Outlook



Exercises



Estimation of Survival from Capture-Recapture Data Using the Cormack-Jolly-Seber Model



Introduction



The CJS Model as a State-Space Model



Models with Constant Parameters



Models with Time-Variation



Models with Individual Variation



Models with Time and Group Effects



Models with Age Effects



Immediate Trap Response in Recapture Probability



Parameter Identifiability



Fitting the CJS to Data in the M-Array Format: The Multinomial Likelihood



Analysis of a Real Data Set: Survival of Female Leisler's Bats



Summary and Outlook



Exercises



Estimation of Survival Using Mark-Recovery Data



Introduction



The Mark-Recovery Model as a State-Space Model



The Mark-Recovery Model Fitted with the Multinomial Likelihood



Real-Data Example: Age-Dependent Survival in Swiss Red Kites



Summary and Outlook



Exercises



Estimation of Survival and Movement from Capture-Recapture Data Using Multistate Models



Introduction



Estimation of Movement between Two Sites



Accounting for Temporary Emigration



Estimation of Age-Specific Probability of First Breeding



Joint Analysis of Capture-Recapture and Mark-Recovery Data



Estimation of Movement among Three Sites



Real-Data Example: The Showy Lady's Slipper



Summary and Outlook



Exercises



Estimation of Survival, Recruitment, and Population Size from Capture-Recapture Data Using the Jolly-Seber Model



Introduction



The JS Model as a State-Space Model



Fitting the JS Model with Data Augmentation



Models with Constant Survival and Time-Dependent Entry



Models with Individual Capture Heterogeneity



Connections between Parameters, Further Quantities and Some Remarks on Identifiability



Analysis of a Real Data Set: Survival, Recruitment and Population Size of Leisler's Bats



Summary and Outlook



Exercises



Estimation of Demographic Rates, Population Size, and Projection Matrices from Multiple Data Types Using Integrated Population Models



Introduction



Developing an Integrated Population Model (IPM)



Example of a Simple IPM (Counts, Capture-Recapture, Reproduction)



Another Example of an IPM: Estimating Productivity without Explicit Productivity Data



IPMs for Population Viability Analysis



Real Data Example: Hoopoe Population Dynamics



Summary and Outlook



Exercises



Estimation of Abundance from Counts in Metapopulation Designs Using the Binomial Mixture Model



Introduction



Generation and Analysis of Simulated Data



Analysis of Real Data: Open-Population Binomial Mixture Models



Summary and Outlook



Exercises



Estimation of Occupancy and Species Distributions from Detection/Nondetection Data in Metapopulation Designs Using Site-Occupancy Models



Introduction



What Happens When p 1 and Constant and p is Not Accounted for in a Species Distribution Model?



Generation and Analysis of Simulated Data for Single-Season Occupancy



Analysis of Real Data Set: Single-Season Occupancy Model



Dynamic (Multiseason) Site-Occupancy Models



Multistate Occupancy Models



Summary and Outlook



Exercises



Concluding Remarks



The Power and Beauty of Hierarchical Models



The Importance of the Observation Process



Where Will We Go?



The Importance of Population Analysis for Conservation and Management



A List of WinBUGS Tricks



Two Further Useful Multistate Capture-Recapture Models


References


Index