Hierarchical Modelling for the Environmental Sciences

Preface Part I. Introduction to hierarchical modeling 1: Bradley P. Carlin, James S. Clark and Alan E. Gelfand: Elements of hierarchical Bayesian influence 2: Kent Holsinger: Bayesian hierarchical models in geographical genetics Part II. Hierarchical models in experimental settings 3: James S. Clark and Shannon LaDeau: Synthesizing ecological experiments and observational data with hierarchical Bayes 4: Janneke Hille Ris Lambers, Brian Aukema, Jeff Diez, Margaret Evans and Andrew Latimer: Effects of global change on inflorescence production: a Bayesian hierarchical analysis Part III. Spatial modeling 5: Alan E. Gelfand, Andrew Latimer, Shanshan Wu and John A. Silander, Jr.: Building statistical models to analyse species distributions 6: Kiona Ogle, Maria Uriarte, Jill Thompson, Jill Johnstone, Andy Jones, Yiching Lin, Eliot J. B. McIntire and Jess K. Zimmmerman: Implications of vulnerability to hurricane damage for long-term survival of tropical tree species: a Bayesian hierarchical analysis Part IV. Spatio-temporal modeling 7: Li Chen, Montserrat Fuentes and Jerry M. Davis: Spatial temporal statistical modeling and prediction of environmental processes 8: Christopher K. Wikle and Melvin B. Hooten: Hierarchical Bayesian spatio-temporal models for population spread 9: Eric Gilleland, Douglas Nychka and Uli Schneider: Spatial models for the distribution of extremes References Index