Bruce Marcot

Michael L. Morrison

William Mannan

Wildlife-Habitat Relationships goes beyond introductory wildlife biology texts to provide wildlife professionals and students with an understanding of the importance of habitat relationships in studying and managing wildlife. The book offers a unique synthesis and critical evaluation of data, methods, and studies, along with specific guidance on how to conduct rigorous studies. Now in its third edition, Wildlife-Habitat Relationships combines basic field zoology and natural history, evolutionary biology, ecological theory, and quantitative tools in explaining ecological processes and their influence on wildlife and habitats. Also included is a glossary of terms that every wildlife professional should know. Michael L. Morrison is professor and Caesar Kleberg Chair in Wildlife Ecology and Conservation in the Department of Wildlife and Fisheries Sciences at Texas A&M University in College Station. Bruce G. Marcot is wildlife ecologist with the USDA Forest Service in Portland, Oregon. R. William Mannan is professor of wildlife ecology at the University of Arizona in Tucson.

Concepts and Applications

Wildlife-Habitat Relationships

Olivier Pourret

Patrick Naïm

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.

Bruce Marcot

Books

Your next favorite book is out there