Applied Hierarchical Modeling in Ecology - Analysis of Distribution, Abundance and Species Richness in R and BUGS Volume 1, Prelude and Static Models (Relié)

Applied Hierarchical Modeling in Ecology : Analysis of datnbution, abundance, and species eeriness in R and BUGS otters a new synthesis of hierarchical modeling in studies of plant and animal distribution, abundance, and community characteristics such as species richness using data collected in meta-population designs. This type of site-stratified data is extremely widespread in ecology and its applications in such areas as biodiversity monitoring, conservation biology, and fisheries, and wildlife management.
This first volume begins by explaining the basic concepts of distribution and abundance, hierarchical models and their Bayesian and likelihood analysis, linear and generalized linear models, data simulation, and use of R and BUGS software for fitting traditional linear, generalized linear, and simple mixed models. The second part of the volume presents six "monographs" on the hierarchical modeling of distribution and abundance for single and multiple species, using classical and Bayesian inference and based an such common data as counts, capture/recapture, distance sampling, and detection/ncndetection ("presence/absence").
Applied Hierarchical Modeling in Ecology, Volume 1 serves as an indispensable manual for practicing field biologists, as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields, and as an overview of this field for statisticians. This book : Provides a synthesis of important classes of hierarchical models about distribution, abundance, and species richness while explicitly accommodating measurement error (imperfect detection) ; Emphasizes data simulation as a way of studying and understanding stochastic processes and statistical models ; Takes a dual inference paradigm approach by the seamless integration of both likelihood-based and Bayesian inference ; Uses the dominant software for likelihood and Bayesian analyses in ecology : R and BUGS ; Is written in a very accessible style with a large number of tulip worked examples that will kick-start your analyses al your own data ; Includes access to a companion website containing data sets, code , errata, solutions to exercises, and further information, and is supported by two e-mail lists maintained by the authors ; Lays the foundation for Volume 2 of Applied Hierarchical Modeling in Ecology, wherein dynamic and more advanced versions of these models will be presented