Introduction History and motivation Marking Introduction to the Cormorant data set Modelling population dynamics Model fitting, averaging, and comparison Introduction Classical inference Bayesian inference Computing Estimating the size of closed populations Introduction The Schnabel census Analysis of Schnabel census data Model classes Accounting for unobserved heterogeneity Logistic-linear models Spuriously large estimates, penalized likelihood and elicited priors Bayesian modeling Medical and social applications Testing for closure-mixture estimators Spatial capture-recapture models Computing Survival modeling: single-site models Introduction Mark-recovery models Mark-recapture models Combining separate mark-recapture and recovery data sets Joint recapture-recovery models Computing Survival modeling: multi-site models Introduction Matrix representation Multi-site joint recapture-recovery models Multi-state models as a unified framework Extensions to multi-state models Model selection for multi-site models Multi-event models Computing Occupancy modelling Introduction The two-parameter occupancy model Extensions Moving from species to individual: abundance-induced heterogeneity Accounting for spatial information Computing Covariates and random effects Introduction External covariates Threshold models Individual covariates Random effects Measurement error Use of P-splines Senescence Variable selection Spatial covariates Computing Simultaneous estimation of survival and abundance Introduction Estimating abundance in open populations Batch marking Robust design Stopover models Computing Goodness-of-fit assessment Introduction Diagnostic goodness-of-fit tests Absolute goodness-of-fit tests Computing Parameter redundancy Introduction Using symbolic computation Parameter redundancy and identifiability Decomposing the derivative matrix of full rank models Extension The moderating effect of data Covariates Exhaustive summaries and model taxonomies Bayesian methods Computing State-space models Introduction Definitions Fitting linear Gaussian models Models which are not linear Gaussian Bayesian methods for state-space models Formulation of capture-re-encounter models Formulation of occupancy models Computing Integrated population modeling Introduction Normal approximations of component likelihoods Model selection Goodness of fit for integrated population modelling: calibrated simulation Previous applications Hierarchical modelling to allow for dependence of data sets Computing Appendix: Distributions reference Summary, Further reading, and Exercises appear at the end of each chapter.
Rachel S. McCrea is a NERC research fellow in the National Centre for Statistical Ecology at the University of Kent. Byron J.T. Morgan is an Emeritus Professor and honorary professorial research fellow in the School of Mathematics, Statistics and Actuarial Science at the University of Kent. He is also the co-director of the National Centre for Statistical Ecology.
"...does a great job of concisely pulling together and categorizing relevant models from historic to very recent. In addition to describing the models, the book also provides the interested reader with related readings, software, and exercises at the end of each chapter...The sheer number and diversity of modeling approaches and examples covered in the book is quite impressive. Overall, this book provides a good survey of the models available in capture-recapture analysis, starting with those around 100 years old and moving into the very recent." -Journal of the American Statistical Association, May 2016 "... a very detailed monograph covering both classical and modern-day statistical methodology used for analyzing capture-recapture data. ... very clear ... accessible to most statisticians and quantitative ecologists. ... I think Analysis of Capture-Recapture Data does a great job of detailing the nuts and bolts of capture-recapture models commonly used in practice. In particular, for the more sophisticated or specialized capture-recapture models, this book certainly points the reader in the right direction for further details. I highly recommend it for those who haven't encountered or heard of capture-recapture modeling before." -Australian & New Zealand Journal of Statistics, 2016 "This book presents an excellent and compact overview of the existing methodological approaches to what is commonly called the capture-recapture area. ... Various approaches have been developed over at least 100 years, and it is a great achievement of the authors to bring these together in a very digestible overview." -Biometrical Journal, 2015 "... an excellent, easy-to-read monograph about capture-recapture models. ... it is well organized and the writing is clear and concise. I would recommend this book as a reference for the quantitative ecologist or statistician interested in knowing what's out there. And I'm glad to have it on my bookshelf. ... a really great synthesis of much of the current capture-recapture and related population modeling literature ..." -J. Andrew Royle, Journal of Agricultural, Biological, and Environmental Statistics, Vol. 20, No. 2, 2015 "This book hits its target audience perfectly. ... an excellent basis for an advanced undergraduate course on capture-recapture methods, or by selecting sections of the book, part of a course on wildlife assessment and management methods ... impressive in its scope and breadth ... an excellent reference book for quantitative ecologists and statisticians ... The book comes with an attractive and well-organised website containing resources that are a real bonus for anyone wanting to develop teaching material on capture-recapture or take advantage of the educational material there for their own understanding of the topics covered. I highly recommend the book to anyone interested in capture-recapture methods, particularly as they relate to ecological problems." -David Borchers, University of St Andrews, Scotland "This volume will be useful as both a textbook and reference, introducing readers to the most recent methodological developments in drawing inferences about animal population dynamics from the study of marked individuals. In a rapidly changing discipline, this book does a good job of surveying the current `art of the possible'." -Jim Nichols, Patuxent Wildlife Research Center, U.S. Geological Survey "Analysis of Capture-Recapture Data is an invaluable companion to the modern theory and practice of capture-recapture modelling. It is a text with multifaceted appeal, ranging in coverage from traditional models to cutting-edge developments, and flowing effortlessly from practical model-fitting advice to advanced technical topics such as parameter redundancy. It is presented throughout in a concise, accessible style that strikes an impeccable balance between illumination of concepts and succinct mathematical detail. This book is a must-have for all statisticians working with ecological data and is also suitable for ecologists with a mild quantitative bent or as a course companion for students from senior undergraduate years onwards. The text can be used either as a dip-in reference or as a cover-to-cover read. Anyone who completes the latter can feel confident that they are up to date with everything that matters in this vibrant and expanding field." -Rachel Fewster, Associate Professor, University of Auckland, New Zealand