Quantitative Conservation Biology: Theory and Practice of Population Viability Analysis - Tapa blanda

This book is unique because it is written much like a tutorial that describes the process of PVA in a well-organized and easy-to-follow manner and does so in sufficient detail (with specific real-world examples) to serve as a starting point for more detailed treatments. The book is sure to appeal to a wide audience and should serve as a useful resource for those who wish to better understand PVAs, as well as for more experienced theoreticians and conservation practitioners." (Carlyle Brewster, American Entomologist)

William Morris and Daniel Doak have written a comprehensive volume on population viability analyses (PVA) that integrates the theory of population ecology with the analytical tools necessary to synthesize observational data on the dynamics of populations. The book is a thorough, quantitative treatment and should be approachable by conservation biologists and ecologists with an interest in learning the details and application of PVA." (William R. Clark, Landscape Ecology)

This is a book we've needed for a decade. PVA is not only a bridge between science and policy, it is the flagship technology of conservation biology. When applied to strongly interacting species, it is also a foundational tool of ecosystem conservation. Thank goodness, therefore, that this book is readable. Morris and Doak draw on a treasury of experience and eschew complexity except where necessary. Their book is truly the definitive step in making PVA accessible to students and practitioners. Hooray!" (Michael Soulé, The Wildlands Project)

Published by Sinauer Associates, an imprint of Oxford University Press.
Conservation biology relies not only on the general concepts, but on the specific methods, of population ecology to both understand and predict the viability of rare and endangered species and to determine how best to manage these populations. The need to conduct quantitative analyses of viability and management has spawned the field of "population viability analysis," or PVA, which, in turn, has driven much of the recent development of useful and realistic population analysis and modeling in ecology in general. However, despite calls for the increased use of PVA in real-world settings―developing recovery plans for endangered species, for example―a misperception remains among field-oriented conservation biologists that PVA models can only be constructed and understood by a select group of mathematical population ecologists.

Part of the reason for the ongoing gap between conservation practitioners and population modelers has been the lack of an easy-to-understand introduction to PVA for conservation biologists with little prior exposure to mathematical modeling as well as in-depth coverage of the underlying theory and its applications. Quantitative Conservation Biology fills this void through a unified presentation of the three major areas of PVA: count-based, demographic, and multi-site, or metapopulation, models. The authors first present general concepts and approaches to viability assessment. Then, in sections addressing each of the three fields of PVA, they guide the reader from considerations for collection and analysis of data to model construction, analysis, and interpretation, progressing from simple to complex approaches to answering PVA questions. Detailed case studies use data from real endangered species, and computer programs to perform all described analyses accompany the text.

The goal of this book is to provide practical, intelligible, and intuitive explanations of population modeling to empirical ecologists and conservation biologists. Modeling methods that do not require large amounts of data (typically unavailable for endangered species) are emphasized. As such, the book is appropriate for undergraduate and graduate students interested in quantitative conservation biology, managers charged with preserving endangered species, and, in short, for any conservation biologist or ecologist seeking to better understand the analysis and modeling of population data.